QHPC 2026–27 Comprehensive Operating Plan
Queen's High-Performance Computing · 2026–27 · CEO-level plan

The comprehensive operating plan

Everything needed to run QHPC as a real organisation this year: an expanded org chart with room for finance, marketing, and consulting-track hires; a week-by-week calendar built on the grad mentors' own proven Sprint Model; and — new — a full Research Branch with 35 undergrad-approachable topics, a project backlog, and a strategy for QHPC to become the compute backbone of every design team and department at Queen's.

Breaking · changes every downstream section

Queen's is building a $900M+ sovereign AI supercomputer in Kingston — with Bell Canada

In January 2026, Queen's and Bell Canada signed an MOU to design, build, and operate a next-generation AI supercomputing facility in Kingston, backed by the federal Sovereign Compute Infrastructure Program (Budget 2024/2025, over $900M). Bell leads construction and the building's fibre/heat-recapture infrastructure; Queen's leads research, chip procurement, and system architecture — explicitly building on the Centre for Advanced Computing and housing what Queen's itself calls "Canada's largest cohort of researchers and students advancing extreme-scale systems." In March 2026, Simon Fraser University joined as a second site partner. This is not a hypothetical someday-facility — it is being built now, in QHPC's own city, largely run by the institution QHPC already partners with.

$900M+Federal program
Kingston, ONFacility location
Bell + Queen's + SFUPartners
Announced Jan–Mar 2026Timeline so far

What this means for QHPC: the club's positioning shifts from "students who like a niche hobby" to "the only trained talent pipeline for a national infrastructure project happening in our own backyard." Every section on partnerships, sponsorship, and the compute-utility strategy below (§16, §17, §19, §38) now has a much bigger reason to say yes. See the expanded treatment in each.

Part ISituation
01 · Read first

Four competition facts that changed since the manual

The manual and the LinkedIn About section both name competitions that are closed or that QHPC cannot enter. Fix these first — the whole calendar hangs off them.

Not eligible
Winter Classic is HBCU/HSI-only

Your LinkedIn About text lists it as a target. The organisers state they exclusively recruit from Historically Black Colleges and Universities and Hispanic-Serving Institutions. Queen's does not qualify. Remove it before recruitment season.

Closed
SC26 shut on 15 May 2026 — confirmed nothing was submitted

Applications ran 2 March → 15 May 2026; acceptances went out 19 June. SC26 (16–18 Nov 2026) is gone, and the next SC window is SC27, roughly March–May 2027. That leaves exactly one competition entry available before March — the ISC window below.

Open now
ISC is the live target — and it opens this week

Verified from isc-hpc.com directly. The published cycle runs: submissions open 1 August, close ~10–14 November, teams announced ~9 December, virtual round the following May, in-person final June. That is roughly 13 months of lead time ahead of the competition. ISC runs a virtual track of 21 teams connecting remotely to two supercomputers, alongside a 10-team onsite final. No vendor hardware, no travel, no sponsorship prerequisite.

ISC 2027 dates are not published yet — the site still shows the prior cycle. The pattern is consistent enough to plan against (expect open ~1 Aug 2026, close ~mid-Nov 2026), but the page must be checked from 1 August rather than assumed. Note also that some countries feed ISC through a national qualifier rather than direct application — South Africa's CHPC runs a selection round whose winner goes to ISC 2027. Confirm Canada has no equivalent gating step.

Renamed
IndySCC is now "SCC Connect"

Competes on provided cloud resources — no vendor partner, no cluster build, no conference attendance. Opt in via a checkbox on the main SCC application. Same March–May window as SC27.

Competition strategy in one line: ISC 2027 virtual track this autumn, SC27 with the SCC Connect box ticked in spring. Both are no-travel, no-vendor-hardware — which matters more than ever given §02.

02 · Urgent

Your only funding source was cut roughly in half

The manual states QHPC's operating budget is "entirely dependent on the Dean's Donation Fund." In the 2026 cycle that fund moved from twice-yearly to once-yearly and dropped from funding roughly 80% of requests to 30–50%.

Design teamRequestedReceivedShare
Queen's Aerospace$75,000$24,60033%
QSET$54,000$23,00043%
QRET$53,500$23,20043%
aQuatonomous$18,000$8,70048%
Qlean$10,000$4,30043%

Treat this as the year's defining constraint. The teams that survive the squeeze have a second and third income line built before they need it. QHPC currently has zero — see §19, and the consulting strategy in §16 is designed partly to fix this.

03 · Benchmark

What the organisations you named actually do

Every one of them has three things: an artifact, subteams with named leads, and an external deadline. QHPC has the third only in aspiration.

OrganisationScaleStructureArtifactThe mechanism worth copying
QMIND 30 → 200+ 3 Managing Directors + 2 Supervisors, then 30+ teams of 4–6 200+ lifetime papers/projects; 52 GitHub repos; 30+ client engagements One deliverable per small team, all converging on one conference date.
CUCAI 340+ delegates, 19 schools 3 Co-Chairs · 4 Advisors · 8 Directors · Product Team 38-paper published proceedings; 70 projects showcased A student org can own a national event — it started small.
Queen's Hyperloop
founded 2015
100+
30%+ non-eng
4 divisions run by managers, directors, co-captains; R&D branch spans 5 faculties across 2 research groups and 4 projects Three pod generations; top 19 worldwide at the 2019 SpaceX Hyperloop Pod Competition; tied for most awards at CHC 2023 and recognised for best leadership among North American teams; 5 named research publications First-Year Rep + sampling period, commit by December. Publishes a full sponsorship ladder with dollar thresholds (§19) and runs the only dedicated Professional Development program among Queen's design teams.
aQuatonomous 35 → 80+ in one year 6 subteams Solar ASV for RoboBoat Served as client for a first-year design course — recruitment via curriculum.
Queen's Aerospace 50+ 3 subteams Planes, VTOLs, multirotors Bronze/Silver/Gold tiers; three-word identity.
Queen's Relectric — Subteams + Women on Design Teams portfolio SuperKart, Jeep EV conversion A Publications page as a public research asset.

What QHPC already has that most of these needed years to build

The honest read: the problem is not capability. It's that nothing is packaged, nothing is owned by anyone but three execs, and nothing has an external deadline.

Part IIOrganisation— built to hire broadly, across faculties
04 · Structure

The full org chart

Run this the way you'd design any growing organisation: a small executive layer with clear portfolios, a director layer under each exec who can be a first- or second-year hire, and a general membership organised into tracks. Violet marks seats aimed squarely at Commerce, Economics, or non-technical students — QHPC has real work for them, and naming it explicitly is what gets them to apply.

President (sets vision · chairs exec · external face to EngSoc/ECE/CAC) │ ├── VP Technical (an evolution of "Technical Exec" — the technical P&L owner) │ ├── Director, Cluster Operations hardware · imaging · netboot · Slurm admin │ ├── Director, Applications & Benchmarking HPL · HPCG · profiling · tuning │ ├── Director, Research owns the Research Branch, §14 │ └── Competition Captain(s) A-Team + B-Team, mirrors the 2023–25 precedent │ ├── Systems Lead → System Support │ └── Applications Lead → Application Support ×2 │ ├── VP Operations & Finance (the Commerce-friendly COO/CFO seat) │ ├── Director, Finance & Treasury budget · BoE · DDF application · actuals │ ├── Director, Sponsorship & Partnerships ← nobody owns this today │ ├── Director, Consulting & Industry Relations owns §16 │ └── People Operations Coordinator hiring logistics, onboarding, HR liaison │ ├── VP Communications & Growth (the Commerce/Media-friendly CMO seat) │ ├── Director, Marketing & Brand social, posters, template system │ ├── Director, Content & Publications newsletter, blog, technical writing │ ├── Events & Community Coordinator workshops, socials, club fairs │ └── Web & Design Lead site, Figma/Canva asset library │ └── VP Education & Talent (owns the member pipeline end to end) ├── Director, Curriculum Foundations cohort, Sprint topics ├── Director, Mentorship senior/junior pairing, alumni network └── DEI & Community Officer QWID liaison, underrepresented-group outreach Advisory Board: Faculty Advisor (Ryan Grant) · Graduate Mentor(s) (Curtis Shorts + others) · CAC Liaison (Brandon) · Informal Industry Advisors (Ian Karlin, Brooke Henderson) External Stakeholders: Equipment Vendors · Corporate Sponsors · Cloud Credit Partners · Other Design Teams (as clients, §16) · Academic Departments (as clients/collaborators, §17)

That's five exec seats, thirteen director/coordinator seats, plus the competition-team leadership and advisory board — twenty-odd named positions for a club that had three last year. You do not need to fill every seat in year one. Post the whole chart, fill the seats marked new first, and let the rest grow into it over two years — this is explicitly the multi-year structure, not a September-1 requirement.

Why so many Commerce-shaped seats: A technical club that only advertises technical roles only ever recruits engineers and CS students. Finance, Sponsorship, Consulting, Marketing, Content, Events, and People Ops are all real, resume-worthy roles for Smith Commerce and Economics students — and they are exactly the roles QHPC is currently missing. Naming them this explicitly, and running them as a genuine business function rather than "the club needs someone to do posters," is what gets a Commerce student to apply instead of assuming the club isn't for them.

05 · Roles

Role directory — what each seat actually does

Every seat below is postable on Breezy as its own listing. Where a seat is new this year, it says so.

President
Direction and external face
  • Vision, roadmap, weekly exec agenda
  • ECE Department, faculty advisor, EngSoc Council
  • Unblocks portfolios; doesn't run them
  • Owns the transition manual at year end
VP Technical
Everything that runs on a machine
  • Curriculum accuracy and Sprint quality
  • Cluster infrastructure and credentials
  • Competition applications and training
  • GitHub org, docs, environment guides
Director, Cluster Ops
Keeper of the hardware
  • Pi cluster build, imaging, netboot
  • Frontenac account requests and CAC liaison
  • Networking, storage, uptime
Fit: CompEng, ECE, Computing
Director, Applications & Benchmarking
Makes the cluster do work
  • HPL/HPCG runs and tuning
  • Real-application ports and profiling
  • Owns the competition benchmark suite
Fit: Computing, Physics, Math & Eng
Director, Research New
Runs the Research Branch
  • Curates and assigns topics from §14
  • Pairs student teams with faculty/department partners
  • Owns write-up quality and submission deadlines
Fit: any science/engineering discipline
VP Operations & Finance Commerce
Money and EngSoc machinery
  • Budget, actuals, BoE forms
  • Owns the Dean's Donation Fund application
  • Sanctioning forms for off-campus activity
Director, Finance & Treasury Commerce
Day-to-day books
  • Create and track the budget spreadsheet
  • Credit card runs, receipts to SharePoint
  • Reconcile actuals after every event
Director, Sponsorship & Partnerships New Commerce
The second and third income lines
  • Sponsorship package and tier sheet
  • In-kind hardware and cloud-credit asks
  • CRM of contacts, asks, outcomes
Director, Consulting & Industry Relations New Commerce
Runs the compute-as-a-service program
  • Owns §16's design-team and department client pipeline
  • Scopes engagements, tracks delivery
  • Turns engagements into case studies for the sponsorship deck
People Operations Coordinator New Commerce
Hiring and onboarding, run properly
  • Breezy postings, interview panel scheduling
  • Onboarding checklist for every new member
  • HR liaison for EngSoc's Director of HR
VP Communications & Growth Commerce/Media
Reach and the owned channel
  • Website, newsletter, social calendar
  • Template system for posters/announcements
  • EngSoc newsletter submissions
Director, Marketing & Brand Commerce/Media
What people see
  • Social calendar and post design
  • Club-fair booth and banner
  • Sponsor logo placement compliance
Director, Content & Publications New Commerce/Media
The publication engine
  • Newsletter, cadence and content pipeline
  • Edits pod/Sprint write-ups into posts
  • Coordinates CUCAI/SCC-facing writeups
Events & Community Coordinator New
Logistics for everything that happens in a room
  • Speaker series logistics and RSVPs
  • Socials, mock-SCC event-day run-of-show
  • Club-fair shift scheduling
Web & Design Lead
Owns the site
  • Next.js site content and deploys
  • Figma/Canva template library
  • Domain and hosting
VP Education & Talent New
The pipeline, end to end
  • Foundations cohort and Sprint scheduling
  • Skill assessment at intake
  • Owns the December placement deadline, §06
Director, Curriculum
Keeps the material current
  • Maintains the eight Foundations decks
  • Recruits Sprint topic leads from senior members
  • Runs the mock-SCC format
Director, Mentorship
Senior/junior pairing
  • Assigns Sprint leads to junior teams
  • First-Year Representative program
  • Builds the alumni contact list
DEI & Community Officer New Commerce/any
Makes the club actually welcoming
  • Queen's Women in Design liaison, §17
  • Outreach to underrepresented groups in HPC
  • Diversity narrative for the SCC application

RACI for the five processes that actually break a club

Every one of these has failed silently at some student org because "everyone thought someone else had it." Name the Accountable person for each before September.

ProcessResponsibleAccountableConsultedInformed
Dean's Donation Fund applicationDirector, FinanceVP Ops & FinancePresident, Sponsorship DirectorWhole exec
Competition application (ISC/SCC)VP TechnicalPresidentFaculty advisor, Director of ResearchWhole club
A new sponsorship askDirector, SponsorshipVP Ops & FinancePresident (if >$500 or a name-brand logo)Comms, for asset use
A new consulting engagement (§16)Director, ConsultingVP Ops & FinanceStudent Counsel (§33), the client team's captainResearch Director, for topic overlap
Credential and access handoverPeople Ops CoordinatorPresidentOutgoing execVP Technical, for infra access

Bus-factor backups

Every seat needs a named person who could run it for two weeks without notice. This table is the succession plan referenced in the risk register, §24 and §32.

Primary seatBackup
PresidentEither VP, by exec vote at the first meeting of the year
VP TechnicalDirector, Applications & Benchmarking
VP Ops & FinanceDirector, Finance & Treasury
Director, SponsorshipDirector, Consulting & Industry Relations
Director, Cluster OpsA named senior Sprint lead from the systems side
06 · Members

Three tracks instead of one room

Today every member gets the same Wednesday meeting, which serves neither the beginner nor the person ready to compete.

Track 1 · open to all
Foundations cohort
  • No prerequisites, any faculty, any year
  • Eight weeks, the decks already in the repo
  • Ends with a certificate of completion
Track 2 · Sprints
4-week app/sys teams
  • The proven Sprint Model, §10 — not invented this year
  • Senior members lead, juniors choose app or sys side
  • Ends in a lessons-learned presentation
Track 3 · selected
Competition team
  • Six students plus alternates, per SCC rules
  • Drawn from Sprint performance, selected by January
  • Requires a named faculty or grad-student advisor

Borrow Hyperloop's December deadline

New members sample freely through the fall and commit to a Sprint track by early December — this also matches the grad-mentor plan's own Winter Week 1 milestone ("form S3 teams"). Add a First-Year Representative seat paired with mentorship, because first-years who join in September are still here for SC29.

Recruit outside ECE

aQuatonomous went 0 → 80 in one year recruiting every discipline. Ask Irina Pavich for the ECE-wide email and approach the equivalent advisors in Physics, Math & Stats, and Computing — HPC touches every one of them, per §14.

07 · Hiring

Hiring and onboarding, end to end

A proven five-stage process, lifted from Queen's Hyperloop

Hyperloop publishes its full recruitment process. It's fair, accommodating, and battle-tested on 100+ members a year — adopt it rather than improvising:

  1. Application form — applicants pick the branch and subteam(s) they want. Critically, Hyperloop states plainly: "you do not need experience to apply", and resumes are collected only as tiebreakers and as interview material, not as a screen.
  2. Interviews — roughly 15 minutes, 5–6 questions, conducted by three or more executives connected to the role. Typically within a week of the deadline.
  3. Second-round interviews — only triggered when there are too many strong applicants to separate, avoiding arbitrary tiebreaks.
  4. Offers & acceptances — candidates may be deferred or referred to a different position rather than simply rejected. On acceptance, an information form captures preferences, and the member immediately joins internal comms and the PD program.
  5. Onboarding — branch-specific training beyond the general onboarding, plus introduction to the alumni network and corporate partners.

Two details worth stealing verbatim: referring a strong applicant sideways instead of rejecting them (it keeps good people in the funnel), and giving new members access to the alumni network on day one rather than treating it as a senior-member perk.

The recruiting number that settles the any-faculty debate: Hyperloop states that over 30% of its members come from non-engineering programs, with students from every faculty at Queen's. They run 100+ members and place them at Tesla, AMD, Cisco Meraki, Deloitte, RBC Capital Markets, EY, OPG, and Roland Berger. A technical design team at this university demonstrably recruits a third of its people from outside engineering — so QHPC's §33 bench isn't optimistic, it's below the local benchmark.

08 · Culture

Operating principles — inherited, not invented

The 2023–25 team wrote down an explicit strategy and set of team-environment tenets in Obsidian canvases still sitting in the repo. They're good. Keep them rather than reinvent a code of conduct from scratch.

The objective hierarchy

Top-level goal: "Achieve the best outcomes for all team members — put every member in the best position to excel in HPC, measured by members getting hired or creating their own work." That outcome is built on two pillars: Make Us Known (reputation → industry connections → sponsorship) and Excel in Cluster Competitions (which depends on Form the Best Team, Develop Technical Skills, and Develop Management Skills). All of it rests on four enablers: Have the Best Training, Communicate Professionally, Be Great Financial Stewards, and Maintain the Best Team Environment.

The team environment tenets

Truth over comfort.

Trust people's word until they prove untrustworthy. Dishonesty is cause for removal.

Respect in language and thought.

No trash talk, no put-downs, no joking about failing to hit team goals — joke about other things.

Strive for excellence without contempt.

Push for the highest achievement, but harsh attitudes toward less-experienced members are grounds for removal, same as disdain for team achievements.

Don't assume — ask, and state your assumptions.

When you must work under an assumption to move forward, say so explicitly and keep testing it.

Disagreements get resolved, not endured.

Escalate to a tiebreaker or defer to whoever is closer to the problem, then commit — no relitigating after the fact.

Ideas are provisional, not dogma.

Everything here is "the best way we know right now." Bring a better idea and the team updates.

How the team actually operates

Part IIIProgram— built on the grad mentors' own Sprint Model
09 · Competitions

The calendar, with real dates

CompetitionApplication windowFormatCost to enterVerdict
ISC 2027 — virtual track ~1 Aug → ~14 Nov 2026
verify on isc-hpc.com
Remote access to two supercomputers; ~21 teams; virtual round ~May, judged interviews after No hardware, no travel Primary
SC27 SCC Connect ~Mar → ~May 2027 Provided cloud resources; no vendor partner; no conference attendance No hardware, no travel Primary
SC27 SCC — main ~Mar → ~May 2027 6 students + advisor + vendor partner; build and run a cluster live over 48h Vendor hardware + travel for 7 Apply anyway
ISC 2027 — onsite final same as virtual 10 teams assemble clusters in Hamburg, June 2027 Hardware + international travel Stretch
CUCAI Project Showcase Registration 15–25 Jan
confirmation by 30 Jan
Present to 340+ delegates in Toronto; proceedings published Ticket + travel Adjacent
Winter Classic Jan → Apr HPL, HPCG + real apps, mentor orgs, judged interview — Not eligible

Anatomy of the SCC application

Team description · diversity and recruitment context · hardware/software specification · institutional support · preparation plan · educational goals — plus a named advisor. Ask Ryan Grant or Curtis Shorts in September.

10 · Method

The Sprint Model — inherited, still correct

This is the mechanism the 2025–26 grad mentors designed, explicitly to prepare "for the 2026–27 season" — this year. Don't replace it; run it properly.

Weekly meeting is two hours, not a quick check-in: 30 minutes of updates, 60 minutes of presentation, 30 minutes of work session and Q&A. This is the mentors' own format — plan the Wednesday slot accordingly.

11 · Calendar

Week-by-week — Fall and Winter

Adapted directly from the 2025–26 grad-mentor plan, extended with this year's real deadlines. Map week numbers onto the registrar's published term dates once confirmed; Queen's fall term runs ~12 teaching weeks plus a reading week, which is exactly this template's shape.

Fall term

WkMeeting topicBackground tasks / real deadlines
1Returning members welcome back; senior members choose app or sys leadExec recruiting new members; sort out comp application deadlines; contact Brandon at CAC re: team server, target week-1 access
2Recruitment intro to the teamSenior members prep app/sys presentations; check isc-hpc.com — ISC 2027 window should be open
3Intro to Linux and VM setupJunior members set up VMs
4Intro to parallel computation (MPI)Junior members run the MPI tutorial homework
5App/Systems presentations; form Sprint 1 teamsSenior members prepare Sprint 1 materials from §14's topic list
6Sprint 1 work session / Q&ABegin drafting the ISC application — all six sections
Reading week — sprint continues, no formal meeting
7Sprint 1 work session / Q&ASenior members prepare Sprint 2 materials
8Sprint 1 presentations; form Sprint 2 teamsCirculate ISC draft to Ryan Grant / Curtis Shorts for review
9Sprint 2 work session / Q&ASponsorship outreach round one goes out
10Sprint 2 work session / Q&AAttend the Dean's Donation Fund preparation workshop
11Sprint 2 work session / Q&ASubmit the Dean's Donation Fund application (mid-Nov, 8:00 a.m. deadline) and the ISC 2027 application (~14 Nov)
12Sprint 2 presentationsGuest speaker; post the term's write-ups; year-in-review

Winter term

WkMeeting topicBackground tasks / real deadlines
1Welcome back; form Sprint 3 teamsExec recruiting winter joiners; CUCAI registration opens 15 Jan — register as Student Club Partner
2Sprint 3 work session / Q&AExtra ramp-up sessions for new members; CUCAI registration closes 25 Jan, confirmation by 30 Jan
3Sprint 3 work session / Q&AExtra ramp-up sessions for new members
4Sprint 3 presentations; form Sprint 4 teamsSelect the competition team — six plus alternates
5Sprint 4 work session / Q&AMock competition planning begins
6Sprint 4 work session / Q&AMock competition planning; guest speaker
Reading week
7Sprint 4 presentations; form mock-comp teamsSC27 SCC + SCC Connect applications open ~2 March — begin drafting
8Mock competition preparation / Q&ASend delegates to CUCAI, 7–8 March, Toronto
9Mock competition preparation / Q&AMerch drop via Zeffy (pre-order only)
10Mock competition — judged, with the interview componentSubmit SC27 SCC + SCC Connect applications (~May window opens)
11Prep for the 2027–28 seasonOpen 2027–28 exec hiring on Breezy
12Prep for the 2027–28 seasonYear-end social; update and commit the transition manual; credential-handover audit

What sits outside the 24 teaching weeks: August is pre-term setup (banner, budget draft, website, ISC-window watch). May–June is the ISC virtual round and possible onsite final, and the SC27 application review cycle, both of which run into the summer regardless of the academic calendar.

12 · Events

The event portfolio

Event typeCadenceOwnerNotes
General meetingWeekly, 2 hours, Wed, Dunning 10President30/60/30 split per §10
Foundations sessionWeekly, 8 weeks/termVP EducationMaterial already written
Sprint work session4 per Sprint, ×4 Sprints/yrDirector, CurriculumCore mechanism, §10
Guest speaker2 per termPresidentHighest-reach content historically
Mock SCCOnce, Winter Wk 10VP TechnicalJudged interview added to match the real thing
Club fairsSept + Winter re-fairEvents CoordinatorBanner ordered in August
SocialTermlyEvents CoordinatorKeep the terminal Pictionary tradition
EngSoc Design Team ShowcaseAnnualPresidentBring the Pi cluster
13 · Output

Publish, and get on a stage

Every Sprint and pod write-up is a publication candidate. Two posts a term is enough to look serious. Host it on your own site rather than renting a Medium.

The CUCAI pathway

Become a Student Club Partner; a designated team lead submits the project description and member list; those members are auto-approved against registration. Registration ran 15–25 January, confirmed by 30 January, for the 7–8 March conference at the University of Toronto campus. Tickets via Zeffy. Enquiries to chair@cucai.ca.

What a CUCAI paper actually looks like — measured, not guessed

All 37 papers in the CUCAI 2025 proceedings were indexed and three were downloaded and text-extracted to establish the real bar. The full index with direct PDF links is a separate deliverable; the findings that change QHPC's strategy are below.

DimensionMeasured realityWhat it means for QHPC
FormatIEEE two-column. Abstract → I. Introduction (A. Motivation / B. Related Works / C. Problem Definition) → methodology → results. Numbered citations.Standard template, free on Overleaf. Nothing to invent.
Length2,899 / 3,651 / 6,334 words across the three sampled — roughly 6–10 pagesOne 4-week Sprint plus two weeks of writing covers this comfortably
Team size1 to 6 authors. One paper was solo-authored.Maps exactly onto Sprint team size, §10
InstitutionsQueen's, U of T, UVic, McMaster (MacAI), UTMIST, WCS, DAIR, AIWGenuinely national — submitting means competing with and networking against the strongest clubs in Canada
Technical barThe energy paper applies LSTM to building-energy forecasting — well-established method, competently executed, honestly reportedThe bar is "real work, properly written up," not novelty. All 35 topics in §14 clear it.
Topic distributionHeavily weighted to ML/AI applications; light on systems and infrastructureAn HPC systems paper would stand out rather than blend in — a real differentiation opportunity

CUCAI 2026 is drifting toward computational work — good news for QHPC

Both the 2025 (37 papers) and 2026 (35 papers) proceedings were indexed in full. The shift between them matters:

 CUCAI 2025CUCAI 2026
Papers3735
Systems / simulation contentSparseNoticeably more — CFD solvers, TinyML on microcontrollers, microgrid benchmarking
AuthorshipMostly teams of 2–6Mostly single named authors

The standout is "Spectral features for Neural-initialized-Newton Solvers in Cardiovascular CFD simulations" — straightforwardly computational science, and the single most QHPC-adjacent paper in either year. Read it as a template; it is roughly what Research topic 21 (CFD with OpenFOAM) would produce. Meanwhile "Beyond Bill C-27: From AI Legislative Gaps to a Reformed AI and Data Act" is a pure law-and-policy paper, and B.A.I.L.I.F.F. is a legal-fairness framework — two more no-code entries confirming the §33 argument.

Net read: the conference is moving toward QHPC's territory, and systems work is still under-represented enough to stand out rather than blend in.

A speaker worth inviting immediately. CUCAI 2026 released four of ten speaker decks publicly, and one is Jonathan Dursi, Senior Solutions Architect at NVIDIA, presenting "AI for Science." Dursi is a well-known figure in Canadian research computing — previously at SciNet in Toronto and Compute Canada — and a long-standing writer on HPC. He is a Canadian HPC person who already accepts invitations to speak at Canadian undergraduate conferences. That makes him arguably the highest-probability guest speaker QHPC could land, and a second warm route into NVIDIA alongside Ian Karlin. His slides are downloadable now; the invitation should go out in September.

The finding that proves the any-faculty strategy: the CUCAI 2025 Ethical Development award went to "AI consciousness and the evolution of labour ethics: Reframing historical materialism" — 6,334 words by five Queen's students, built on Marx's historical materialism as its analytical framework, containing no code, no model, no dataset, and no experiment. A Political Studies, Philosophy, History, or Law student can co-author an award-winning paper at Canada's largest undergraduate AI conference without writing a line of code. Put this specific example in the recruitment materials for the roles in §33 — it is far more persuasive than any assurance that "all faculties are welcome."

Part IVResearch, projects & partnerships— the new centrepiece
14 · Research Branch

65 topics, graduated by difficulty

This section is the catalogue. The execution detail lives in the companion Research & Project Handbook, published as two volumes totalling 34 full runbooks. Each runbook expands one topic into a week-by-week plan with the software, the data, the measurements, the failure modes specific to that study, and a deliverable spec — written so a Sprint lead can hand it to a team and walk away.

Volume I covers Tiers 1–3 (Foundation, Developing, Intermediate) — 22 runbooks plus reference sections on Slurm, timing methodology, plotting conventions, and the report template. Volume II covers Tiers 4–5 (Advanced, Frontier) — 12 runbooks including the six Queen's partnership projects, plus guidance on approaching a research partner and running multi-term work.

None of these need to be novel science. A well-run benchmarking study, a careful replication, or an honest scaling analysis is a legitimate undergraduate research output — the kind CUCAI, SCC applications, and department posters actually want. Each is tagged with a difficulty and a realistic output format. The Director of Research (§05) assigns these into Sprints and pods.

Start with Section 0 — the entry tier (E1–E12). Those twelve need no prior HPC experience and are what every new member should be routed through first. Sections I–VII are the intermediate core catalogue. Section VIII (36–47) covers frontier topics drawn from current 2025–26 HPC research. Section IX (48–53) maps directly onto verified Queen's research facilities that already need compute — the fastest route to faculty partnerships and the letters competition applications require.

Catalogue sectionCountWho it's forSprint fitHandbook tier
0 · Entry (E1–E12)12First- and second-years, any faculty, zero backgroundFirst sprintVol I · Tier 1 Foundation
I–VII · Core (1–35)35Members who've completed one sprintSprints 2–4Vol I · Tiers 2–3 Developing, Intermediate
VIII · Frontier (36–47)12Senior members and competition teamYear 2+Vol II · Tier 4 Advanced
IX · Queen's-specific (48–53)6Paired with a faculty co-supervisorAny, with a partnerVol II · Tier 5 Frontier

I · Systems & performance — the most natural fit, runs directly on your own hardware

01
HPL/HPCG benchmarking across configurations

Compare the Pi cluster against a Frontenac partition of similar core count — where does ARM lose or win?

EasyTech report
02
Performance-per-watt: ARM vs x86

Measure real power draw on the Pi cluster vs an equivalent Frontenac job — a genuine "Green HPC" measurement at student scale.

MediumCUCAI-eligible
03
Slurm scheduling policy comparison

FIFO vs backfill vs fair-share under synthetic contention. Directly useful to Queen's own School of Computing (see QDES lab, §17).

MediumTech report
04
Network topology and MPI collective latency

How allreduce/broadcast latency scales with node count and topology on the Pi cluster.

Medium
05
Filesystem comparison: NFS vs local scratch vs parallel FS

I/O-bound workload timing across storage backends.

Easy
06
Containerisation overhead: bare-metal vs Docker vs Apptainer

Directly relevant to how modern HPC centres (including the CAC) actually run jobs.

Medium
07
Cloud vs on-prem cost-performance

Price a chosen workload on AWS/Azure/Oracle against the club's own cluster — ties straight into the SCC Connect cloud-resource track.

EasyBusiness angle
08
Checkpoint/restart on a small cluster

Fault-tolerance mechanisms for long-running jobs.

Hard
09
Reproducibility study

Does the same simulation give identical results across reruns, compilers, or optimisation flags? A genuinely publishable meta-question.

Medium

II · Parallel programming & applications

10
Strong vs weak scaling of an open scientific code

Pick one: LAMMPS, GROMACS, or OpenFOAM. The exact analysis the Sprint Model's "applications" track already asks for.

Medium
11
MPI vs OpenMP vs hybrid

Same kernel (matrix multiply or N-body), three parallelisation models, one comparison.

Easy
12
GPU offload study

Port a CPU kernel to CUDA or OpenACC and measure the real speedup on Frontenac's GPU nodes.

HardCompetition-relevant
13
Load balancing in embarrassingly parallel workloads

Monte Carlo simulation as the test case.

Easy
14
Programming model comparison

MPI vs PGAS (UPC/Chapel) vs task-based (Charm++) on a toy problem — an accessible systems-literature survey plus a small implementation.

Medium

III · AI/ML systems — the QMIND-adjacent lane

15
Distributed training benchmarking

Data-parallel vs model-parallel training across multi-GPU nodes.

HardCUCAI-eligible
16
LLM inference serving on a small cluster

Latency/throughput vs batch size and quantisation level — genuinely timely, and a joint submission with QMIND writes itself.

MediumCUCAI-eligible
17
Energy cost of training small models

A student-scale reproduction of "Green AI"-style measurement.

Medium
18
Federated learning simulation across Pi "edge" nodes

Uses the Pi cluster as a stand-in for distributed edge devices.

Hard
19
HPC for genomics

Run an open bioinformatics variant-calling pipeline at scale — a real bridge to Life Sciences and Kingston Health Sciences Centre via the CAC.

Hard

IV · Domain applications — built for cross-department partnership

20
Small-scale weather/climate model scaling study

Partner candidate: Environmental Studies.

Hard
21
CFD with OpenFOAM: mesh refinement vs runtime

Direct value to Hyperloop (pod aerodynamics), Aerospace, and Relectric — this is a consulting engagement in disguise, see §16.

MediumClient-ready
22
Molecular dynamics with GROMACS or LAMMPS

Partner candidate: Department of Chemistry.

Medium
23
N-body astrophysics simulation and scaling

Partner candidate: Department of Physics, Engineering Physics — Queen's has a strong particle-astrophysics community via the Sudbury Neutrino Observatory Institute.

Medium
24
Parallel finite-element structural analysis

Partner candidate: Civil Engineering, GeoEngineering Centre.

Medium
25
Hydrological / water-quality modelling at scale

Partner candidates: Beaty Water Research Centre, and aQuatonomous's own "ecological & water research" subteam.

MediumClient-ready
26
Agent-based economic/market simulation at scale

Partner candidate: Smith School of Business, Economics — a genuine Commerce-student research lane.

EasyCommerce-friendly
27
Sports analytics at scale

Distributed processing of a large public sports dataset — QMIND has already done this with F1 and hockey data; a joint or comparative piece is an easy first collaboration.

Easy

V · Systems security & reliability — defensive framing only

28
Security hardening of a Slurm cluster

Attack-surface analysis and mitigations, written as a defensive-hardening guide.

Medium
29
Side-channel timing analysis in shared HPC environments

Educational framing — what multi-tenant clusters must defend against.

Hard
30
Access control and multi-tenancy models for shared research clusters

Directly reusable by the CAC or by your own future dedicated server.

Medium

VI · Visualisation & HCI

31
Real-time cluster health dashboard

Grafana + Prometheus + custom exporters — also a Project Backlog item, §15.

Easy
32
Scientific visualisation pipeline and usability study

ParaView or VisIt on simulation output, with an actual usability evaluation.

Medium
33
VR/AR visualisation of job scheduling or scientific data

Worth pitching jointly with Queen's School of Computing's HCI-adjacent groups.

Hard

VII · Sustainability & policy — the meta-research lane

34
TCO and carbon-footprint model: on-prem vs cloud bursting

Business-case framing — strong Commerce/Economics collaboration.

MediumCommerce-friendly
35
Survey of undergraduate HPC education models across Canada

The most approachable of all 35 — a literature/interview survey, potentially co-authored with peer clubs at other universities, and a natural CUCAI or SCC "educational goals" exhibit.

Easy

0 · Entry tier — genuinely first-sprint topics No experience needed

The 53 topics that follow skew intermediate-to-hard. These twelve are deliberately different: a first- or second-year student with no HPC background can complete any of them in a four-week sprint, and each still produces a real chart, a real finding, and a real write-up. Assign these first. Nobody's first sprint should be a GPU port.

E1
"How much faster is a cluster than my laptop?"

Run the identical job on a laptop, the Pi cluster, and a Frontenac node. Plot runtime across all three. Sounds trivial — isn't. You'll discover the laptop sometimes wins at small problem sizes, which teaches startup cost, scheduling overhead, and why "supercomputer" isn't a synonym for "always faster." Perfect first sprint and a genuinely good club-fair demo.

EntryGreat demo
E2
Measure Amdahl's Law empirically

Take one program with a known serial fraction. Run at 1, 2, 4, 8, 16 cores. Plot measured speedup against the theoretical curve and explain the gap. You are reproducing a foundational result of the field with your own data — which is exactly what a first research experience should feel like.

Entry
E3
Compression benchmark for scientific data

Compare gzip, bzip2, zstd, and lz4 on real scientific files: compression ratio vs speed vs decompression speed. Immediately useful to anyone moving data around, and requires nothing but a shell.

EntryPractically useful
E4
Python vs NumPy vs C — the same computation

Implement one numerical kernel (matrix multiply, or a simple stencil) three ways. Measure the difference. The result is usually 100–1000×, and it permanently changes how a student thinks about writing scientific code.

EntryHigh teaching value
E5
What would our cluster cost on AWS?

Price the Pi cluster and an equivalent Frontenac allocation against on-demand and spot cloud pricing. Produce a break-even analysis. No code at all — a spreadsheet, current price lists, and clear reasoning. Ideal for a Commerce or Economics member's first project, and it feeds the sponsorship conversation directly.

EntryNo code
E6
Write the Pi cluster build guide

Document the existing cluster end to end so a stranger could rebuild it: parts list, wiring, netboot configuration, NFS setup, every command. A build guide is a legitimate deliverable — it's also the single most valuable thing to hand the next cohort, and it directly de-risks the "hardware fails" scenario in §32.

EntryHigh club value
E7
Filesystem timing: local disk vs NFS vs Frontenac scratch

Time the same file operations — write, read, many-small-files, one-large-file — across storage types. Teaches why I/O is usually the real bottleneck, using nothing more than dd, time, and patience.

Entry
E8
Job arrays and the parameter sweep

Take a program with one tunable parameter. Use a Slurm job array to run 100 variants at once. Plot the result surface. This is the single most immediately useful HPC skill for a researcher in any discipline, and it's a two-line change to a batch script.

EntryTransferable
E9
Reproduce a figure from a published paper

Pick any figure from the CUCAI proceedings archive and try to regenerate it from the description. Document exactly where you got stuck. Failure is the finding — this is real reproducibility research, it needs no novel idea, and it teaches critical reading better than any lecture.

EntryPublishable as-is
E10
Survey Queen's students on research computing

What do students in Physics, Chemistry, Computing, and Engineering know about available compute? What have they needed and not had? A form, some interviews, and honest analysis. No technical background required, and it becomes the recruiting pitch and the seed of Research topic 35.

EntryNo code
E11
Thread scaling in OpenMP

One #pragma omp parallel for. Vary OMP_NUM_THREADS from 1 to the core count. Find where it stops helping — and then find out why (memory bandwidth, false sharing, or just too little work per thread).

Entry
E12
MPI from zero: hello world → ring → reduce

Write three small MPI programs in sequence, timing each. By the end you understand point-to-point messaging, collective operations, and why communication cost dominates at scale. This is the standard on-ramp to everything else in this catalogue.

EntryGateway topic

Design principle behind the entry tier: every one of these produces a plot, has an unambiguous "done," and cannot fail in a way that wastes the term. E1, E4, and E9 in particular are more interesting when the result is counter-intuitive — which removes the pressure that kills first projects. Route every new member through one of these before anything from the main catalogue.

0b · Entry-tier build projects No experience needed

Buildable artifacts rather than studies, at the same accessibility level. Each is a resume line and something to demo at a club fair.

ProjectWhat you buildSkills gained
Cluster status webpageA single page showing which nodes are up, current queue depth, and recent jobs. Read Slurm, render HTML.Scripting, Slurm commands, basic web
"Submit your first job" tutorialA guided walkthrough that takes a total beginner from login to a completed batch job in 20 minutesTeaching, technical writing, empathy for beginners
Benchmark auto-runnerA shell script that runs the standing suite and dumps results to CSV with hardware metadata attachedBash, reproducibility discipline
Cluster temperature/power loggerPoll the Pi cluster's sensors, log to file, plot over a week. Reveals real thermal behaviour under load.Sensors, time-series data, plotting
Slurm cheat-sheet cardA one-page printable reference for the commands members actually useDistillation — harder than it looks, and genuinely wanted
Onboarding environment scriptOne script that sets up a new member's SSH config, keys, aliases, and module defaultsAutomation, and it removes a real recurring friction
Cluster "hello world" in five languagesThe same parallel program in C, Fortran, Python, Julia, and Rust — with build instructions for eachToolchains, build systems, language comparison
Club-fair live demoA visual, real-time demonstration that runs on the Pi cluster and looks impressive to a passer-by (Mandelbrot render, N-body animation, distributed prime search)Everything above, plus presentation

The first five things a new member should do

A concrete on-ramp, in order. Roughly the first month.

  1. Set up the VM and log into the Pi cluster. The workshop doc already exists.
  2. Submit one Slurm job that prints the hostname. Understand that it ran somewhere else.
  3. Run E1 — time the same job on laptop, Pi cluster, and Frontenac. Make one plot.
  4. Run E12 — the three MPI programs. Now you understand distributed computing.
  5. Pick an entry topic and join a sprint team. You are now doing research.

Why this ladder matters more than the frontier topics. A club's survival depends on what happens to a nervous second-year in their first four weeks. If their first assignment is "port a kernel to CUDA," they leave. If it's "find out whether a cluster actually beats your laptop, and be surprised by the answer," they stay — and in two years they're the one doing the GPU port. The entry tier is the recruitment strategy, not a warm-up.

VIII · Frontier topics — grounded in current HPC research

Topics 36–47 come from active 2025–26 research directions rather than textbook exercises. They are harder, but they put QHPC on genuinely current ground — and several are under-explored enough that competent undergraduate work is publishable.

36
Mixed-precision computing and HPL-MxP

The third benchmark nobody at student level runs. HPL-MxP performs LU factorisation in low precision (FP16/FP8) then recovers full accuracy via GMRES iterative refinement in FP64. Study the accuracy/throughput tradeoff and where numerical stability breaks down. Frontenac's GPUs have tensor cores built for exactly this.

HardCompetition-relevantPublishable
37
Carbon-aware job scheduling

Grid carbon intensity varies by hour and region. Published work reports 18–57% emissions reductions by deferring delay-tolerant batch jobs into low-carbon windows. Implement a carbon-aware policy on the Pi cluster using public grid-intensity data for Ontario, and measure the emissions/makespan tradeoff. Tools like CATS exist as prior art.

MediumSustainabilityVery current
38
Job failure prediction from scheduler logs

Apply ML to Slurm accounting data to predict which jobs will fail or exceed walltime. Genuinely useful to any HPC centre, and it uses operational data rather than scientific data.

MediumClient-ready
39
Sparse linear algebra performance

Sparse matrix-vector multiply is the kernel underneath HPCG and most implicit solvers. Compare storage formats (CSR, CSC, ELL, hybrid) against matrix structure and measure achieved bandwidth against the roofline.

Medium
40
Compiler optimisation study

How much performance comes from the compiler rather than the code? Compare GCC, Clang, and vendor compilers at matched optimisation levels across the benchmark suite. Cheap to run, consistently surprising results.

Easy
41
Quantum circuit simulation at scale

Simulating an n-qubit circuit costs memory exponential in n — which makes it a natural HPC workload. Benchmark state-vector simulators (Qiskit Aer, cuQuantum) and find the qubit count where a single node stops being enough.

HardHigh interest
42
Graph analytics at scale

PageRank, BFS, and connected components on large public graphs. Communication-bound rather than compute-bound, so it exercises a completely different part of the machine than HPL.

Medium
43
I/O patterns and parallel filesystem behaviour

Characterise how access pattern, file count, and stripe configuration affect throughput. Use IOR and mdtest. I/O is the most common real-world bottleneck and the least studied at student level.

Medium
44
Monte Carlo derivatives pricing

Embarrassingly parallel, financially motivated, and genuinely interesting to a Commerce or Economics student. Study convergence rate vs core count and variance-reduction techniques.

EasyCommerce-friendly
45
Seismic / wave-equation modelling

Stencil computation on a 3D grid — the canonical memory-bandwidth-bound HPC workload, and directly relevant to geological engineering.

Hard
46
Digital twin of the Pi cluster

Build a discrete-event simulation of your own cluster, validate it against real measurements, then use it to predict the effect of configurations you can't afford to build. A zero-cost way to study hardware you don't have.

Medium$0
47
Interconnect and collective-communication tuning

Compare MPI collective algorithms (ring vs tree vs recursive-doubling allreduce) and measure where each wins as message size and node count vary.

Medium

IX · Queen's-specific topics — where local research already needs compute

These are grounded in verified Queen's research facilities. Each has a real department behind it, real software already in use, and a real reason to want QHPC's help.

48
Radiation damage in zirconium alloys — atomistic simulation

Queen's Reactor Materials Testing Laboratory and the Materials at Extremes and Nuclear (MAX-Nuclear) Research Institute run multiscale modelling from DFT and ab initio molecular dynamics through classical atomistic and mesoscale simulation — studying defect generation, radiation damage, and hydride precipitation. All of it is compute-bound. Queen's also runs CHEMNUS, which explicitly trains researchers in scientific software engineering for nuclear systems.

HardClient-readyReal local partner
49
Rock mass modelling for deep mining and tunnelling

The Queen's Geomechanics and Geohazards Group and the Robert M. Buchan Department of Mining Engineering run FLAC3D, 3DEC, PFC, Irazu (FDEM) and Rocscience tools on high-performance workstations in their Computational Geomechanics Laboratory. Brittle fracture, mine-scale models, blast damage, strainburst mechanisms.

HardClient-ready
50
Particle-astrophysics data processing

Queen's is a founding partner in the Sudbury Neutrino Observatory Institute. Rare-event searches are classic large-scale data-reduction problems.

Hard
51
Nanofabrication process simulation

NanoFabrication Kingston — process modelling and device simulation as a compute workload.

Medium
52
Power electronics and grid simulation

ePOWER (Queen's Centre for Energy and Power Electronics Research) — converter and grid-scale simulation, pairing naturally with the energy-efficiency work in topics 02 and 37.

MediumClient-ready
53
Structural response under dynamic loading

Queen's operates a Rolling Load Simulator. Pair physical experiment with parallel FEA and compare.

Medium

Why topics 48–53 are the most strategically valuable in this entire list. Note what the Queen's Geomechanics group runs its simulations on: high-performance workstations. Not a cluster. The same pattern holds across most experimental labs — sophisticated commercial simulation software, running on a single powerful desktop, because nobody in the group has the time or the systems background to move it onto Frontenac.

That is precisely the gap QHPC fills. These aren't topics where QHPC asks a professor for a favour; they're topics where QHPC brings something the lab actually lacks — parallelisation and scheduler literacy — in exchange for a domain question, real data, and co-supervision. That is the healthiest possible basis for an academic partnership, and it is the fastest route to the faculty letters that §09's competition applications require.

How to run this: the Director of Research pulls 8 of these 53 into each term's Sprint list (4 app-side, 4 sys-side, matching the Sprint Model's own split), rotating so no topic repeats within two years. Anything tagged Client-ready routes through §16 instead of a Sprint — those become paid or in-kind consulting engagements, not just write-ups.

15 · Backlog

Project ideas — things to actually build

Research topics produce write-ups; these produce artifacts members can point to, demo at club fairs, and put on a resume.

ProjectWhat it isWhy it matters
Pi Cluster v2Scale past 5 nodes; add a Jetson Nano/Orin for a real heterogeneous CPU+GPU clusterThe physical artifact every peer team has and QHPC's is already the best of the bunch
Cluster health dashboardGrafana + Prometheus + custom exporters on both clustersMakes the club's infrastructure legible to sponsors and new members alike
QHPC Job PortalA lightweight web frontend for members to submit and monitor jobsA genuine software project for members who'd rather build web tools than run benchmarks
"HPC-in-a-box" teaching kitA portable rack version of the Pi cluster for outreach and demosTurns club-fair and high-school outreach into a hands-on demo instead of a poster
Automated benchmarking CIEvery code change to the club's benchmark suite auto-runs and posts resultsTeaches CI/CD, and keeps §14's benchmark numbers always current
Slurm scheduling visualiserAn interactive teaching tool showing jobs queue and schedule in real timeDoubles as a Foundations-cohort teaching aid and a CUCAI-eligible ML-scheduling project
Volunteer-computing nodeContribute club compute to a real project — Folding@home or Rosetta@homeZero-effort, visible community contribution and a genuinely good PR story
Open-source contribution sprintA structured Sprint where the team submits patches to real OSS HPC tools (Slurm, OpenMPI, Warewulf)Members' names end up in real project histories — a strong resume line
"Compute for Queen's" micro-grantSmall compute allocations on the club cluster, awarded competitively to undergrad researchers campus-wideA friendlier, faster front door than the CAC's own intake for students who just need a little compute — see §16

Pi Cluster v2 — the technical spec, in enough detail to actually build

LayerRecommendationWhy
Compute nodes8–10× Raspberry Pi 5 (8GB), up from 5Large enough to make network-topology and scaling research (§14, topics 04/10/11) actually show a trend, not just two data points
Heterogeneous node1× NVIDIA Jetson Orin NanoThe first real GPU node — unlocks the CUDA/GPU-offload research lane (§14 no. 12) and the AI/ML systems section entirely (§14 Section III)
ProvisioningWarewulf or xCAT for network boot/imaging, building on the existing PXE/TFTP setupReproducible rebuilds — directly fixes the "hardware fails or walks" risk in §32
SchedulerSlurm, matching Frontenac and every real HPC siteMembers transfer skills directly to Frontenac and to SC/ISC scoring environments
MonitoringPrometheus + Grafana + node-exporterThe cluster health dashboard project above, and a live demo asset for club fairs and sponsors
Container runtimeApptainer (formerly Singularity)The HPC-standard container tool — directly feeds research topic 06

The standing benchmark suite

One suite, run after every hardware or software change, feeding both competition prep and the Research Branch:

16 · Strategy

QHPC as Queen's compute utility

This is the single highest-leverage idea in this document. Every other Queen's design team needs simulation or compute at some point — CFD, path-planning, battery modelling, trajectory simulation — and right now each one solves that problem alone, badly, or not at all. QHPC already has the cluster, the Frontenac access, and the HPC literacy none of them have. Position QHPC as the shared compute backend for the entire design-team ecosystem, the way QMIND positions itself as the AI backend for real companies.

The finding that reframes this entire section. All 72 CUCAI papers from 2025 and 2026 were downloaded and text-extracted — 272,586 words, the complete published output of Canada's largest undergraduate AI conference across two years. It was then searched for every trace of real research-computing infrastructure. The result:

TermMentions across all 72 papers
Slurm0
Compute Canada / Digital Research Alliance0
Google Colab4
Kaggle13
laptop5

Not one paper, in either year, used a scheduler or a national compute allocation. The strongest hardware reference in the entire corpus is a single team running an A100 through Colab Pro. Canada's best undergraduate AI researchers are training models on free-tier notebooks and personal laptops.

Meanwhile QHPC has sponsored access to Frontenac via CAC partnership (4,500+ cores, 88 GPUs, 25 A100s, 3.3 PB) — and members who know how to write a batch script. That is not a small advantage over the peer network. It is a capability very few undergrad groups have this level of institutional HPC access.

So the consulting strategy should be bigger than Queen's design teams. QHPC's offer to the CUCAI network — QMIND, UTMIST, WAT.ai, Western AI, UVic AI, Western Cyber Society — is: "Your compute ceiling is Colab. Ours isn't. Bring us the training run." That is a national-scale differentiator available to QHPC in year one, and it is the strongest possible argument for both §16's client program and §22's conference ambitions.

A · Design-team clients — the compute-as-a-service program

TeamWhat they need compute forQHPC's offer
Queen's HyperloopPod aerodynamics; tunnel structural simulation (Boring & Tunnelling division)CFD runs on Frontenac; a joint Sprint team owns the simulation
Queen's Aerospace (QADT)Aerodynamics simulation; ML model training for their flight controllerGPU training runs; benchmarking their model's inference latency
Queen's RelectricBattery thermal simulation; powertrain modellingParallel FEA/thermal simulation capacity
aQuatonomousPath-planning/autonomy training; ASV hull hydrodynamicsTraining compute; ties directly to Research topic 25
Queen's Rocket Engineering Team (QRET)Trajectory simulation; propulsion CFDBatch simulation runs across parameter sweeps
Queen's Racing / Formula-style teamsVehicle dynamics simulationParameter-sweep compute capacity

The pitch to each captain is simple: "Stop finding your own compute. We already have the cluster and the Slurm literacy — bring us the simulation, we'll run it and teach your members to run it themselves." Every engagement becomes a joint Sprint, a shared write-up, cross-recruiting in both directions, and a natural joint-sponsorship conversation (a sponsor funding "shared design-team compute infrastructure" is a much bigger, easier pitch than funding one club's Pi cluster).

B · The first-year course client program — copy aQuatonomous exactly

aQuatonomous served as the client for APSC 103, the first-year engineering design course — first-years get assigned aQuatonomous's real engineering problem as coursework, months before they'd ever apply to join. Do the same thing. Pitch QHPC as a client for an APSC 100/103 project: "design and image a small compute cluster," or "benchmark and explain a 5-node Pi cluster." It's a genuinely good sophomore-level systems problem, and it puts QHPC in front of every first-year engineer before recruitment season even starts.

B2 · The national compute offer — to the whole CUCAI network

Following directly from the finding above. Six clubs across five universities publish annually into a conference where nobody has a cluster. The pitch to each is one sentence, and it is credible because it's true:

ClubTheir published work that was compute-boundQHPC's offer
QMINDSuperconductivity prediction, portfolio RL, diagnostic imagingFrontenac GPU nodes for training runs; joint CUCAI submission
UTMISTMulti-agent LLM automation; Unity evolutionary-behaviour platformBatch parameter sweeps — embarrassingly parallel, ideal for Slurm
WAT.ai40+ projects, 20+ publications, backed by the Waterloo AI InstituteOverflow capacity; the most sophisticated partner and the best co-author
Western AIProjects portfolio explicitly targets CUCAI presentationTraining compute + a joint "how to actually use a cluster" workshop
Western Cyber SocietyCNN medical imaging with transfer learningGPU nodes; closest natural systems collaborator
UVic AIDiscord-first, reading-group scaleCluster access + co-run an HPC reading group

Each engagement produces a joint write-up, cross-recruiting, and a co-authored CUCAI submission — and it positions QHPC as infrastructure to a national community rather than one more club competing for attention within it.

B3 · Four named people to contact, and what they said

Full-text analysis surfaced the specific researchers who described hitting a compute ceiling. These are warm technical leads, not cold outreach.

ContactTheir paperWhat they wrote
Maximilian Pochapski
Waterloo
Spectral features for Neural-initialized-Newton Solvers in Cardiovascular CFD (2026)CFD simulations "are hindered by their high computational cost" — the field collapses 3D Navier-Stokes to 1D/0D, "exchanging accuracy for running at a fraction of the computational cost." They are trading away physical accuracy to fit a compute budget.
Daniel SaragihFlow to Learn: Flow Matching on Neural Network Parameters (2025)"Given our computational constraints, we…" — a team explicitly scoping down its own experiments. A lost result.
David Szczecina
QMIND · CUCAI Showcase Director
Nonlinear ML for Compositional Superconductivity Prediction (2026)"First-principles prediction of Tc remains computationally challenging" — requires "simulating quantum mechanical behavior for each candidate." That's DFT: a textbook HPC workload.
Pooria RoyTinyNav: TinyML for Autonomous Navigation on Microcontrollers (2026)Optimising away from HPC — reducing "reliance on high-performance computational resources." An inversion worth pursuing: QHPC's Pi cluster is exactly the edge testbed this work needs.

The opening line for all four: "We read the CUCAI proceedings. Nobody in them mentions a scheduler or a national allocation — the ceiling is Colab Pro. We have sponsored access to Frontenac: a 4,500+ core, 88-GPU cluster (25 A100s) with 3.3 PB access on the A100 partition, and people who write batch scripts. Bring us the run you couldn't finish."

C · Sponsor-adjacent consulting

D · The sovereign supercomputer — the single biggest positioning move available

Queen's is now building a $900M+ national supercomputing facility in Kingston with Bell Canada, explicitly framed around housing "Canada's largest cohort of researchers and students advancing extreme-scale systems." That claim needs a real student pipeline behind it to be true — and right now, QHPC is the only organisation on campus positioned to be that pipeline.

Why this is the CEO move, not just a nice-to-have: it turns QHPC from "a club that competes in cluster competitions" into "the infrastructure every other technical student organisation at Queen's quietly depends on." That's a stronger position for recruiting, for sponsorship, for the Dean's Donation Fund narrative, and — eventually — for design-team status (§21) than any amount of solo competition results.

17 · Targets

Partnership target list — real Queen's entities

Verified, currently-existing units worth a first email this year. Where a specific staff contact isn't named here, that's deliberate — confirm the right person through the department's general office rather than guessing.

CategoryEntityWhy it fits
ComputeCentre for Advanced Computing (CAC)Runs Frontenac (4,500+ cores, 88 GPUs incl. 25 A100s, 3.3 PB storage), already partnered. Contact: cac.help@queensu.ca. Deepen into a joint workshop series and student-ambassador program.
National infrastructureBell CanadaSigned a January 2026 MOU with Queen's to build a $900M+ sovereign AI supercomputer in Kingston. The single best new sponsor conversation available — see §16D.
National infrastructureQueen's Sovereign Supercomputer initiative (via the CAC)The facility Queen's is leading research, chip procurement, and system architecture for. Ask about a formal student-pipeline or advisory role now, while the structure is still forming.
National computeDigital Research Alliance of CanadaThe CAC already won an Alliance grant (Queen's Data Champions). The Alliance's own training — bootcamps, webinars, one-on-ones on advanced research computing — is free to students via a sponsoring faculty member (Ryan Grant can sponsor access). Portal: explora.alliancecan.ca.
Innovation/fundingDunin-Deshpande Queen's Innovation Centre (DDQIC)Already a confirmed sponsor of CUCAI — a real, currently-active funding source for large student tech initiatives, not a hypothetical one. Apply directly for club funding this year.
Robotics/AIIngenuity Labs Research Institute (Smith Engineering)Robotics and AI compute needs; possible joint hackathon or project pool.
EnergyQueen's Centre for Energy and Power Electronics Research (ePOWER)Energy-efficient computing crossover; research topic 02 pairs naturally.
Water/environmentBeaty Water Research CentreHydrological modelling compute; overlaps aQuatonomous's own ecological subteam.
Structural/geoGeoEngineering CentreGeotechnical and structural simulation compute; ties to research topic 24.
Nuclear materialsReactor Materials Testing Laboratory & the Materials at Extremes and Nuclear (MAX-Nuclear) Research InstituteOne of the strongest technical fits on campus. Runs multiscale modelling from DFT and ab initio MD through classical atomistic and mesoscale simulation — radiation damage, defect generation, hydride precipitation in zirconium alloys. Queen's also runs CHEMNUS, training researchers in scientific software engineering for nuclear systems. Research topic 48.
Mining / geomechanicsQueen's Geomechanics and Geohazards Group & the Robert M. Buchan Department of Mining EngineeringTheir Computational Geomechanics Laboratory runs FLAC3D, 3DEC, PFC, Irazu (FDEM) and Rocscience — on high-performance workstations, not a cluster. A textbook QHPC client. Research topic 49.
PhysicsSudbury Neutrino Observatory Institute (Queen's is a founding partner)Particle-astrophysics data processing; a strong "citizen HPC" outreach story.
Computing researchQueen's Discrete-Event Systems Lab (QDES)Directly relevant to Research topic 03 (scheduling policy) — a natural co-supervisor.
Computing researchSoftware Evolution & Analytics Lab (SEAL)Software performance analytics — pairs with the automated-benchmarking CI project.
Computing researchBiomotion LabMotion-capture data processing — a visualisation/HCI collaboration lane.
BusinessSmith School of Business (incl. Master of Management Analytics)Commerce-student research lane for topics 07, 26, 34; a source of Finance/Marketing/Consulting hires.
HealthKingston Health Sciences Centre (via the CAC's existing hospital collaboration)Medical imaging and genomics compute — a stretch goal requiring CAC brokering, handle data sensitivity carefully.
Peer clubQMINDJoint AI-infrastructure workshop; a joint CUCAI submission on topics 15–16; cross-recruiting.
Peer clubQueen's Women in Design (QWID)Brand-new (launched this year) — support their technical programming with an HPC 101 session before every other team does.
HackathonAny Queen's hackathon running that yearSponsor a "Best Use of HPC/Compute" track; offer cluster access or cloud credits to hackathon teams. Confirm current organiser before reaching out.
Part VBusiness
17b · Network

The national peer-club network — your conference attendee list already exists

CUCAI lists its partner student clubs publicly. This is, in effect, a pre-assembled national network of undergraduate technical organisations that already travel to each other's events — and it is exactly the invite list for the regional and national rungs of the conference ladder in §22.

ClubSchoolScale & structureWhat QHPC should take from them
WAT.ai
watai.ca
Waterloo Founded 2022. 450+ program graduates, 40+ AI projects, 20+ publications, 10+ industry partners. Official undergraduate body of the Waterloo AI Institute and a member of the Sedra Student Design Centre. The closest model to what QHPC should become: formally affiliated with a research institute. QHPC's equivalent is becoming the recognised undergraduate body of the CAC — see §16D.
UTMIST
utmist.gitlab.io
U of T 58 tagged projects spanning 2017–2024, organised by academic year. Runs "MIST101" as a named education series. Has AMD and infrastructure among its project tags. Tagging every project by year builds a visible institutional archive — the anti-reset mechanism §07 argues for, executed publicly.
Western AI
westernuai.ca
Western Nine named portfolios: Presidents, Flagship, Communications, Projects, Design, Development, Internal, Finance, Education. Runs "Wavelength" (newsletter) and a Speaker Series podcast. Reaches 800+ individuals. Independent confirmation of the §04 structure — including a dedicated Finance portfolio. Their "Flagship" portfolio (two large events per year) is a cleaner idea than QHPC's scattered event list.
UVic AI
uvicai.ca
Victoria Smaller, Discord-first. Runs an AI Safety reading group and publishes member-made learning resources (lecture slides, Colab notebooks). Proof a small club can matter nationally. A reading group is the cheapest possible recurring program — QHPC could run one on HPC papers with zero budget.
Western Cyber Society
westerncybersociety.ca
Western Submitted to CUCAI 2025 (medical imaging / transfer learning paper). Systems-and-security adjacent — the closest thing to a natural HPC collaborator in this network.
QMIND Queen's Covered throughout this plan. Your on-campus partner for a joint CUCAI submission, §14 topics 15–16.

Why this matters more than it looks: §22's conference ladder assumed QHPC would have to build a national network from scratch over four years. It doesn't. Six clubs across five universities already convene annually, already travel, and already publish proceedings together. Attending CUCAI 2027 as a Student Club Partner puts QHPC inside that network in one step — and Research topic 35 ("survey of undergraduate HPC education across Canada") becomes trivially easy to execute, because the interview subjects are all in one room in Toronto in March.

17c · Constraint strategy

If compute is all you have

The most likely 2026–27 reality: Frontenac access secured and free, Dean's Fund cut to ~40% of ask, zero sponsors. That position is stronger than it looks — and it should drive every decision below.

The asymmetry nobody has noticed. Most Canadian undergraduate tech clubs are money-adequate and compute-poor — the 72-paper CUCAI corpus shows their ceiling is the Colab free tier. QHPC is the inverse: money-poor and compute-rich, with sponsored access to Frontenac (4,500 cores, 88 GPUs, 3.3 PB) at no direct cost to the club. Do not try to become a normal design team with a hardware budget. Play the hand you actually hold.

The core principle: spend compute, not capital

Prefer work whose only expensive inputs are CPU-hours, GPU-hours, and student time — all of which QHPC already has for free. Apply this filter to every proposed project:

The key move: reframe the Pi cluster

The instinct is to spend scarce money scaling the Pi cluster from 5 to 10 nodes. Resist that. Split the roles explicitly instead:

 Pi clusterFrontenac
Cost to expandReal money you don't have$0
Best useTeaching — and hardware students are allowed to breakEvery result that goes in a paper

Under this split the Pi cluster does not need to grow to be valuable. It's the teaching instrument, the club-fair demo, and the photo in the sponsorship deck. If in-kind hardware arrives, grow it; if not, the research programme is unaffected. That decoupling is what makes a zero-budget year survivable.

The entire HPC stack is open source

Rocky Linux, Slurm, OpenMPI, OpenMP, Apptainer, Warewulf, Prometheus/Grafana, OpenFOAM, LAMMPS, GROMACS, HPL, HPCG, STREAM, OSU Micro-Benchmarks, PyTorch, ParaView — all free. Writing runs on Overleaf's free tier with the IEEE template, and CUCAI's own bound proceedings is LaTeX-generated with hyperref, so matching their toolchain costs nothing either. The one real exception is Ansys and SOLIDWORKS, which are commercial — and both already give in-kind licences to Queen's Hyperloop, so ask rather than buy.

How the research catalogue re-scores under a zero budget

TierCountWhich
Start immediately, literally $010Topics 01, 03, 05, 06, 09, 10, 11, 12, 13, 35 — benchmarks, schedulers, containers, scaling studies, GPU offload, and the education survey
Free, but needs a faculty/department partner~9Topics 19–27 — the partner supplies the domain question and data, QHPC supplies compute and parallelisation
Blocked on money3Topic 02 (needs power-measurement gear — one in-kind ask to Keysight unblocks it), topics 04 and 18 (need more Pi nodes)

Ten topics immediately free, nine more free with a partner, three blocked — and one of those three unblocks with a single equipment ask. A zero-budget year costs QHPC almost nothing in research capacity.

What a $0 year actually costs

Foundations curriculum, four sprints, eight research topics, both competition entries, four published write-ups, the mock competition, weekly meetings, guest speakers, Discord and newsletter: all $0. The only unavoidable expense in the entire core programme is a domain name, roughly $15–20 a year.

The sentence that should govern the year: QHPC's core mission — teaching HPC, doing research, entering international competition — is fully executable on a zero-dollar budget. Money buys speed, polish, and reach. It does not buy permission to start. Merch, banners, food, travel, and cluster expansion are growth accelerants, not prerequisites.

And it makes the sponsorship pitch stronger, not weaker

Being capital-light means every dollar is visibly marginal rather than keeping the lights on: "Our research runs on infrastructure we already have and software that's free. We're not asking you to fund our existence — we're asking you to remove three specific constraints we can't engineer around: measurement equipment for the energy study, GPU hardware for the teaching cluster, and cloud credits for the competition that runs on provided cloud resources." Named, bounded asks against named, blocked work convert far better than a general appeal.

18 · Finance

Running the money

Income model

StreamStatus todayMove this year
Dean's Donation FundSole sourceApply by mid-November; budget at ~40% of ask
Merchandise via ZeffyPlanned, unprovenPre-order only, one drop per term
In-kind hardwareNoneEasiest first win — Pi units, switches, storage
Cloud/compute creditsNoneDe-risks the SCC Connect entry directly
Corporate cashNonePublish tiers so there's something to say yes to
Consulting engagements (§16)NoneNew — in-kind or small-cash from other design teams/departments
Departmental supportInformalFormalise via the partnership list in §17
19 · Sponsorship

Build the package before you need it

TierWhat a sponsor gets
GoldLogo on cluster, banner, site header; a dedicated tech talk slot; first access to the resume book
SilverLogo on site and banner; named in recaps; one social post
BronzeLogo on site; named in the annual report
In-kindRecognition mapped to the cash tier its value equals

The ask sequence

  1. Warm campus first — ECE, CAC, Smith Engineering, and now Bell Canada via the sovereign-supercomputer MOU, §16D.
  2. Warm industry second — Ian Karlin (NVIDIA), Brooke Henderson (Sandia), three weeks after their talk, asking for something small and specific.
  3. Kingston/Ontario hardware vendors third — in-kind, specific asks convert better than generic ones.
  4. Cold corporate last, only with a real package behind it.

What a Queen's design team's sponsorship ladder actually looks like — with real numbers

Queen's Hyperloop publishes its full tier structure with dollar thresholds. This is the single most useful sponsorship benchmark available, because it's a peer team on the same campus, under the same EngSoc rules, asking the same donors.

TierThresholdWho's actually in it
MACH IV$8,000+Smith Engineering; Queen's Sci '62
MACH III$5,000+Queen's Sci '44; MG Chemicals
MACH II$3,000+Stantec; Park Lawn Corporation
MACH I$1,000+McElhanney
Software & equipmentIn-kindAltium, Keysight Technologies, Ansys, SOLIDWORKS, OpenProject, TOPDON, DDQIC, DigiKey, Mouser Electronics
Food & hospitalityIn-kindInsomnia Cookies, Chatime, Tahini's, Subway, A&W
Past sponsors—SNC-Lavalin, WSP, Magna International, PwC, L3Harris, Shell, WC Branham, AMS

Three lessons QHPC should copy immediately:

A researched target list — not a generic corporate wishlist

Every name below has a specific, real reason it fits QHPC, pulled from this year's actual research — not a copy-pasted list of big logos.

TargetThe real hookWhat to ask for
AMD — the El Capitan angleEl Capitan, the world's #1 supercomputer and the machine Ian Karlin's own LLNL benchmarking work covered, runs on AMD Instinct MI300A. Unusually direct warm intro via Karlin, on top of the formal University Program route above.A guest technical talk on MI300A architecture; hardware for the Pi Cluster v2 GPU node
NVIDIAAlready warm via Karlin, and a second route via Jonathan Dursi. Critical mechanic: the Academic Grant Program cannot be applied to by students. A full-time faculty member at a PhD-granting institution must be Principal Investigator and submit on the team's behalf. Reviewed quarterly.Ask Ryan Grant to submit as PI. Proposals are stronger if they use NVIDIA pretrained models or software extensively. Portal: NVIDIA Academic Grants.
AMD University ProgramThe most concrete, lowest-friction route on this list — and it was previously mis-scoped. AMD runs a formal university program with a published enrolment path and named contact addresses. Separately, AMD's AI & HPC Cluster gives enrolled academics free remote access to AMD Instinct hardware. AMD also directly sponsored the two fastest Linpack scores at SC22's Student Cluster Competition — this is a vendor with demonstrated SCC intent.Enrol at the University Program using a @queensu.ca address. Contact aup@amd.com for hardware or cluster access; AIER@amd.com for Instinct academic pricing under the AIER 2.0 initiative.
Bell CanadaSee §16D and §17 — the strongest, most timely, most specific pitch on this entire list.Sponsorship framed around student pipeline development for the Kingston facility
Dell, HPE, Lenovo, SupermicroThe classic hardware-vendor sponsors of Student Cluster Competition teams internationally (e.g. Dell/NVIDIA/Intel sponsored Texas A&M's SCC entry). Realistically a multi-year relationship — start the conversation now for eventual use at SC28's main vendor-partnered track, §09.An introductory call now, a hardware-loan commitment for a future onsite SCC entry
AWS, Microsoft Azure, Google CloudQMIND's own inQUbate incubator already partnered with AWS Activate — the door into this ecosystem is already open via a QMIND introduction.Academic cloud credits, §38 — directly de-risks the SCC Connect entry
ProtocaseKingston-based, already a Queen's Relectric sponsor — proven to fund Queen's design teams specifically.In-kind enclosure/rack hardware for Pi Cluster v2
General Dynamics Mission Systems–CanadaOne of Kingston's largest employers, doing C4ISR and defence-relevant computing work; Kingston's own economic development office names AI, cybersecurity, and advanced computing as strategic local sectors.A guest talk on defence-relevant HPC; longer-term co-op pipeline conversation
DeloitteQMIND's own Diamond-tier sponsor and already funding a Queen's student org at scale.A joint QMIND-QHPC sponsorship conversation — warmer than approaching Deloitte cold
Cohere, Accenture, Rootly, SPUR Innovation CenterAll four sponsored CUCAI 2025 — proven willing to fund Canadian undergraduate technical conferences. Rootly's own customer list includes NVIDIA and Figma.Approach as CUCAI co-sponsors once QHPC is a Student Club Partner; warm intro via the CUCAI chairs
Ansys, Altium, Keysight, SOLIDWORKS, DigiKey, MouserAll currently give in-kind software or equipment to Queen's Hyperloop — established, campus-proven in-kind donors who already say yes to Queen's teams.Software licences and components; the lowest-friction asks on this entire list
Queen's graduating class funds (e.g. Sci '62, Sci '44)Alumni class gifts occupy Hyperloop's top two sponsorship tiers — larger than most corporate sponsors, and almost nobody asks.An annual class-gift ask, routed through Queen's alumni relations
Insomnia Cookies, Chatime, Tahini's, Subway, A&WAll five already sponsor a Queen's design team in-kind with food.Event catering — covers the entire socials budget line for the cost of five emails
20 · Brand

Own a channel — with a live peer benchmark

A live cautionary tale, found during this research. aquatonomous.ca — the domain cited earlier in this plan and still linked from EngSoc materials — no longer belongs to the design team. Its subpages now serve unrelated Japanese e-commerce content, indicating the domain lapsed and was re-registered by someone else. The team has moved to aquatonomous.vercel.app. Their own June 2025 LinkedIn post announcing a "major update to aquatonomous.ca" now points at a dead brand asset.

A design team lost its entire public web presence, all its inbound links, and its SEO because a domain renewal fell through a leadership handover. This is the single cheapest catastrophic failure to prevent: register QHPC's domain for multiple years, enable auto-renew, put the billing on an account that survives graduation (the club email, not a personal card), and record the registrar, expiry date, and login in the credentials repo audited every April, §07.

OrgFollowersWhat worked, pulled from their live LinkedIn page
QMIND2,115A Globe and Mail feature reshared with one member's story (Design Team → Deloitte internship) as the hook.
Queen's Relectric401A Design Bay tour for visiting high schoolers, framed as a thank-you to EngSoc. Also just reposted Queen's Women in Design — a live partnership opening.
Smith Hyperloop964Highest-engagement post was a member's personal post, reposted by the team — distribution runs through people.
QADT327Zero organic LinkedIn posts — all their energy goes to Instagram instead. Don't try to be equally active everywhere.
aQuatonomous286Served as the client for APSC 103 — recruitment disguised as first-year curriculum, the model copied in §16.
CUCAI1,661Ticket posts use real urgency and name headline speakers directly rather than making people click through.
20a · Outreach

The sponsorship ask, executed

Tiers and target lists are inputs. This is the actual operating procedure — sequence, timing, scripts, and what to say when they push back.

The ask calendar

WhenWhoAskWhy then
AugECE Department, CACWritten support letter; team serverNeeded for the ISC application in November
Early SeptCampus-proven in-kind donors (Ansys, Altium, Keysight, SOLIDWORKS, DigiKey, Mouser)Software licences and equipmentAcademic-year licences reset in September; they already say yes to Queen's teams
Mid SeptFood sponsors (Insomnia, Chatime, Tahini's, Subway, A&W)Event cateringTrivial to secure; covers the socials line immediately
Late SeptAWS / Azure / Google CloudAcademic cloud creditsApplications take weeks; needed before the SC27 SCC Connect entry
OctCorporate tier-B (NVIDIA, AMD, Bell)Cash or hardwarePackage must exist before the DDF application, which asks for it
Early NovDean's Donation FundAnnual applicationMid-November deadline; attach the sponsorship package
NovAlumni class funds via Queen's alumni relationsClass giftLong lead time; Sci '62 and Sci '44 precedent at Hyperloop's top tiers
Jan–FebSpeakers, three weeks post-talkSomething small and specificNever ask at the event itself
MarCUCAI co-sponsors (Cohere, Accenture, Rootly, SPUR)Introduction via CUCAI chairsYou'll be in the room as a Student Club Partner

The three-touch sequence — never more

  1. Touch 1 — the specific ask. Name the exact item, the exact use, and the Queen's precedent. Offer a tier. Under 200 words.
  2. Touch 2 — day 10. Two sentences. Add one new piece of information (a result, a photo, a competition acceptance), not just "following up."
  3. Touch 3 — day 21. "Closing the loop — is this something you'd revisit next cycle?" This converts a no into a later, and gets you a date.

Then stop, and log it. The single most valuable artifact you leave the 2027–28 exec is a record of who said no and why.

Objection handling

What they sayWhat it meansResponse
"We already sponsor a Queen's team."Budget is allocated, not exhausted"Understood — we're not asking to replace that. We're asking for in-kind [item], which typically comes from a different budget line. And we're the only Queen's team doing HPC, so there's no overlap in what you'd be supporting."
"Send us a package."Polite deferral, or genuine interest — you can't tell yetSend the one-pager same day, with a one-line note naming the specific ask again. Then treat day 10 as touch 2.
"We don't sponsor student groups."Usually true for cash, often false for in-kind"That's fair. Would an equipment loan or software licence sit differently? We'd take a one-year academic licence over a cheque."
"What's the ROI?"They need to justify it internallyRecruiting reach into a scarce skill set, a technical talk slot, and logo placement on a physical cluster. Offer the resume book explicitly — that's the concrete one.
"Come back next year."Real, if you get a date"Happy to. When does your cycle open?" Log the date. Follow up then, referencing the prior conversation.
SilenceWrong person, or wrong timeAfter touch 3, stop. Try a different contact at the same organisation next cycle, not the same one again.

Sponsor fulfilment — the part clubs forget

Securing a sponsor is half the work; keeping them is the half that determines whether next year's exec inherits a relationship or starts cold.

Part VIThe long game
21 · Status

Club, or design team?

The Dean's Donation Fund treats clubs and design teams differently and requires academic advisor approval specifically for design teams. QHPC's actual work — a cluster, an international competition, a faculty advisor — is design-team work. Have this conversation with the Director of Clubs and Conferences this year; the compute-utility positioning in §16 makes the case for you.

22 · Ambition

What it would take to run your own CUCAI

2026–27
Attend and present

Become a CUCAI Student Club Partner. Send a Sprint team to the Project Showcase.

2027–28
Host a single-day event at Queen's

An HPC workshop day co-branded with the CAC and Queen's Women in Design — one room, one day, ~50 people.

2028–29
Regional, multi-school

Invite HPC/systems clubs from Toronto, Waterloo, Ottawa, McMaster. Two days, published proceedings.

2029+
National

Only if the org underneath it can carry it — 100+ members, a director layer, an advisor bench, returning sponsors.

22a · Horizon

The three-year roadmap

This plan covers one year. But several of its highest-value moves — a vendor partnership, design-team status, a hosted event — only pay off across multiple cycles. Here is what each year should be for, so that no single exec team feels obliged to do everything.

 2026–27 · Foundation2027–28 · Consolidation2028–29 · Leadership
ThemeGet structured, get entered, get publishedCompete seriously, fund properlyConvene the field
Members40+ active, 12+ exec seats filled60+, all 20 seats filled100+, first-year rep pipeline mature
CompetitionISC 2027 virtual + SC27 SCC Connect submittedCompete in at least one; apply to SC28 main track with a vendor partnerOnsite competition; target a placing
Research8 topics assigned, 2 publications12 topics, 4 publications, first CUCAI showcase entryProceedings-quality output; co-authored work with 2+ peer clubs
MoneyDDF + 2 in-kind linesDDF + 3–5 sponsors incl. one cash tierVendor partnership; alumni class gift; multi-year sponsors
Consulting1 pilot engagement3–4 engagements incl. one departmentStanding compute service; the CUCAI network uses QHPC
StatusOpen the design-team conversationDesign-team status securedRecognised undergraduate body of the CAC
EventsAttend CUCAI as Student Club PartnerHost a one-day HPC workshop at Queen'sHost a regional multi-school event
InfrastructureFrontenac + Pi teaching clusterDedicated CAC team server; Pi cluster v2Named allocation; possible link to the Kingston sovereign facility

The dependency that matters most: the SC main track requires a vendor partner, and vendor relationships take 18–24 months to build. That means the introductory conversations with Dell, HPE, Lenovo and Supermicro belong in 2026–27, even though they cannot be used until SC28. Starting them late is the single most common way student teams stay stuck in the virtual tracks indefinitely.

22b · Funnel

The recruitment funnel, with real numbers

"Recruit more members" is not a plan either. This models the funnel explicitly so the Education and Comms leads know what to optimise, and what a healthy conversion rate looks like.

StageTargetMechanismRealistic conversion
Aware of QHPC600+Club fair traffic, ECE + Physics/Math/Computing faculty emails, EngSoc newsletter, first-year course client project—
Signed up (newsletter/Discord)150QR code at fairs pointing to the newsletter, not Instagram~25% of aware
Attended ≥1 session80Kickoff meeting; low-friction first session~50% of signups
Active (≥3 sessions)40Foundations cohort structure; buddy pairing with a First-Year Rep~50% of attendees
Placed in a Sprint by December30The December placement deadline (Hyperloop's mechanic)~75% of active
Competition team + alternates8Selected on Sprint performance in January~25% of placed
Returns next year25+The real measure of whether the year worked~60% of active

Where funnels actually leak, and the fix

LeakSymptomFix
Signup → first sessionBig list, empty roomPersonal message before the first session, not a broadcast. Name the person.
Session 1 → session 3The October collapseFoundations gives a reason to return on a schedule. Anyone missing two consecutive sessions gets a personal check-in, not an automated reminder.
Active → placedPeople attend but never commitThe December deadline forces a decision. Ambiguity is what kills commitment.
Year 1 → year 2Annual resetGive second-years a title and a real responsibility — a Sprint lead role — before they drift.
Non-engineering entryOnly ECE students applyPost the §33 roles separately with faculty-specific language, and lead with the award-winning no-code CUCAI papers as proof.

The one metric to instrument from week one: attendance. A sign-in sheet at every session, entered into a single sheet. It is the only number that tells you by November whether the year is working — while there is still time to change it. Hyperloop runs 100+ members; aQuatonomous went 35 → 80 in a year. Neither did it by accident.

23 · Measurement

What to count

MeasureBaselineTarget 2026–27
Active members (≥3 sessions)Not tracked40+
Sprints completed0 formally tracked4
Research topics assigned from §1408
Competition applications submitted03 (ISC, SCC, SCC Connect)
Consulting engagements (§16)02
Income lines beyond the Dean's Fund02
Exec roles filled (of ~20 in §04)312+
24 · Risk

What is most likely to go wrong

RiskLikelihoodMitigation
Dean's Fund award far under askHighBudget at 40%; build in-kind and cloud-credit lines by December
ISC application window missedHigh if unwatchedNamed weekly owner from 1 August; draft in October
Twenty new roles, nobody appliesMediumFill the six "new" seats first; let the rest grow over two years, not one
Research Branch becomes busyworkMediumEvery topic tagged with a real output format and, where possible, a real partner
Design-team clients never materialiseMediumStart with one warm pitch (Hyperloop or aQuatonomous) rather than five cold ones
Advisor unavailable at deadlineMediumAsk in September; have a second named authorised grad student
Part VIIExecution
25 · Now

The first thirty days

☐Check isc-hpc.com for the ISC 2027 SCC window — starting 1 AugustTech
☐Contact Brandon at the CAC about the team's own server — target week-1 access for returning membersTech
☐Post the full ~20-seat org chart on Breezy; fill the six new seats firstPres
☐Remove Winter Classic from LinkedIn About text and recruitment materialsComms
☐Ask Ryan Grant to serve as competition advisor for 2026–27Pres
☐Draft the preliminary budget; register for the October DDF workshopFinance
☐Order the club banner from Printfusion on the EngSoc cardFinance
☐Buy the domain and deploy the existing Next.js siteComms
☐Stand up the newsletter and the club-fair QR codeComms
☐Pull 8 topics from §14 into the Fall Sprint 1/2 rotationResearch
☐Send one warm pitch to a peer design team using the §16 scriptConsulting
☐Email the relevant first-year course coordinator about a QHPC client project, aQuatonomous-styleConsulting
☐Build the sponsor target list and a one-page in-kind hardware askSponsorship
☐Email chair@cucai.ca about Student Club Partner status for 2027Pres
☐Reach out to Queen's Women in Design about an HPC 101 sessionDEI
☐Verify org access and credentials handover for all incoming execsPres
25b · The document set

Everything that accompanies this plan

This plan is the strategy. Twelve companion documents carry the execution detail. Nothing here is intended to be read cover to cover — the point is that when a director needs a specific thing, it exists.

DocumentWhat it isWho uses it
Strategy
QHPC 2026–27 Operating Plan
this document · 55 sections
Structure, program, finance, sponsorship, governance, risk, execution calendarPresident; all execs
Compute-Rich, Capital-Poor StrategyHow to run the whole programme on a zero-dollar budget; the research catalogue re-scored by cost; seven decision rulesPresident; VP Ops & Finance
Research execution
Research & Project Handbook, Vol I
22 runbooks · Tiers 1–3
Week-by-week runbooks from "never used a cluster" to conference-submittable work, plus Slurm, timing, plotting and report-template referencesDirector of Research; Sprint leads
Research & Project Handbook, Vol II
20 runbooks · Tiers 4–6
Advanced HPC research, the six Queen's partnership projects, and eight Tier 6 method-contribution topics; how to approach a research partner; running multi-term work; a readiness triage ranking the Tier 6 flagships; a reviewer pre-mortem; and a Material Passport of independently verified citations with page-anchored quotesDirector of Research; senior members; co-supervisors
Zero-GPU / Single-Node Track
6 runbooks · CPU only
What is genuinely publishable on one CPU-only node with no guaranteed GPU and no guaranteed memory: a memory-ceiling worksheet, a topic-selection guide, six topics each grounded in a verified paper and a real open-weight model, and the objections a reviewer will raiseAny team without a GPU allocation; the fallback plan when the GPU partition is unavailable
Research Publication PlaybookHow a sprint result becomes a submitted paper: the writing pipeline, venue selection, internal review, and the arXiv-regardless ruleDirector of Research; Director of Content & Publications
The Paper Kit
7 parts · no prior publishing experience assumed
The craft between a finished experiment and a submitted paper: how to search the literature and when to stop, how to verify a citation is real, what to do with three noisy runs, why speedups cannot be arithmetically averaged, how each paper section is built, authorship and AI-disclosure rules, artifact packaging, and a deadline plan worked backwardsEvery member writing a paper; sprint leads reviewing one
Money and partnerships
Sponsorship & Partnership PlaybookReal dollar benchmarks from a peer Queen's team, a six-tier target list sorted by warmth, four outreach templates, the national peer networkDirector of Sponsorship; Director of Consulting
Sponsorship One-Pager
designed; sendable as-is
The document you actually send a prospective sponsorDirector of Sponsorship
Competition and research intelligence
Competition Application DraftAll six SCC sections written out substantively, every placeholder marked, plus a pre-submission checklistVP Technical; President
CUCAI Corpus Deep AnalysisFull-text analysis of all 72 papers: the compute-bound researchers with their own quotes, and the no-code papers as recruitment evidenceDirector of Consulting; DEI Officer; People Ops
CUCAI 2025 Proceedings IndexAll 37 papers categorised with direct PDF links, plus format/length/team-size benchmarksDirector of Research
Master Resource IndexCUCAI 2026 slide decks and all 35 papers with links; Hyperloop's publications; corrected URLs; the reusable PDF-download techniqueAnyone doing further research

If you only hand three things to the incoming exec: this plan, the Handbook Volume I, and the Sponsorship Playbook. Those three cover strategy, what members actually do week to week, and where the money comes from. Everything else is reference material that becomes useful when a specific question arises.

Routing table — which document answers which question

The failure mode of a document set this size is that nobody knows which one to open. Route by the question, not by the title.

The question someone actually asksOpen this
"What should this member work on this sprint?"Handbook Vol I, then the progression map at the back of it
"We have no GPU allocation this term. Is the sprint dead?"Zero-GPU / Single-Node Track — start with the memory-ceiling section, then the topic-selection table
"Is this topic actually publishable, or are we fooling ourselves?"Vol II's readiness triage and reviewer pre-mortem
"How do we turn this finished sprint into a submission?"The Paper Kit, start to finish; the Publication Playbook for venue and sign-off; grade the draft against Vol I's sprint rubric
"How do I find the prior work, and how do I know when I have read enough?"Paper Kit Part 1 — the four search passes and the saturation test
"How do I know this citation my AI assistant produced is real?"Paper Kit Part 2. Short answer: a resolving DOI proves nothing; compare the claimed title against the record it resolves to
"I have three timings that disagree. What do I report?"Paper Kit Part 3 — median and spread, never the mean, never the best run
"Who goes on the author list, and in what order?"Paper Kit Part 6. Have this conversation in week 2, not week 11
"How do we approach a faculty member about a collaboration?"Vol II's partner-approach reference
"A company asked what we need. What do we send them?"Sponsorship One-Pager as-is; the Playbook for the follow-up conversation
"Can we afford this?"§37 pro-forma budget here, then the Compute-Rich, Capital-Poor strategy for the zero-dollar version
"Which competition is actually open right now?"§01 and §09 here — and re-verify against the organiser's site before acting
"Is this citation real?"Vol II's Material Passport and the CPU track's passport. Every entry was independently verified; nothing in either was taken on trust from a summary

A standing rule for this document set: the research volumes are the authority on how work is done; this plan is the authority on what work is chosen and who owns it. Where the two disagree, the volumes win on method and this plan wins on priority. Any director noticing a genuine contradiction should fix it in whichever document is wrong rather than working around it — a document set that quietly contradicts itself stops being used within a term.

26 · Sources

What this plan is built on

ISC 2027 and SC27 dates are extrapolated from published 2026 cycles and must be confirmed before anything is planned around them. Where a specific staff contact wasn't already named in QHPC's own materials, this plan deliberately points to a department or office rather than a guessed individual. Instagram accounts could not be read programmatically in this research pass; the peer-channel benchmark in §20 is LinkedIn-only.

Part VII-BTechnical execution playbooks— how to actually run the work, step by step
26a · Runbooks

Five research topics, fully specified

A topic list is not a plan. These five are written as runbooks a second-year member can execute without further guidance — software, data, method, deliverable, and the failure modes that actually bite.

Runbook 1 — HPL/HPCG benchmarking across configurations $0

ElementSpecification
QuestionWhere does an ARM cluster win or lose against x86 at equivalent core count, and why?
SoftwareHPL 2.3, HPCG 3.1, OpenMPI, a tuned BLAS (OpenBLAS on ARM, MKL or BLIS on x86), GCC
DataNone — benchmarks generate their own
MethodBuild both benchmarks from source on each platform. Sweep HPL.dat parameters: problem size N (target ~80% of total memory), block size NB (try 96/128/192/256), and process grid P×Q (keep P≤Q, near-square). Record GFLOP/s and efficiency vs theoretical peak. Repeat ≥3 runs per configuration.
DeliverableEfficiency-vs-NB plot per platform; a table of best configurations; 2,500–4,000 words
Failure modesChoosing N too large → swapping, meaningless numbers. Forgetting to pin processes → run-to-run variance swamps the effect. Comparing an untuned BLAS to a tuned one → measures library quality, not architecture.
Why it mattersHPL and HPCG are scored directly at every SCC. This runbook is simultaneously research output and competition training.

Runbook 2 — Strong vs weak scaling of an open scientific code $0

ElementSpecification
QuestionHow does a real application's parallel efficiency degrade with node count, and where is the bottleneck?
SoftwarePick one: OpenFOAM (CFD), LAMMPS (molecular dynamics), or GROMACS (biomolecular MD). All open source.
DataEach ships tutorial cases — start there, then scale the mesh or particle count
MethodStrong scaling: fix total problem size, double core count (1→2→4→8→16→32…), plot speedup vs ideal. Weak scaling: hold work-per-core constant, grow both together, plot efficiency. Then profile the largest run to find where time actually goes.
DeliverableBoth scaling curves with Amdahl/Gustafson interpretation; a profile breakdown; 3,000–5,000 words
Failure modesToo-small problem → communication dominates immediately and the curve is uninteresting. Not fixing the mesh partitioner → you measure decomposition, not the solver. Ignoring I/O time.
Why it mattersThis is exactly what the Sprint Model's applications track already asks for, and exactly what SCC judges probe in interviews.

Runbook 3 — Slurm scheduling policy comparison $0

ElementSpecification
QuestionHow do FIFO, backfill, and fair-share differ in throughput, mean wait time, and fairness under contention?
SoftwareSlurm on the Pi cluster (safe to reconfigure — never experiment on Frontenac), plus a synthetic workload generator
DataGenerate a synthetic job mix: vary durations (short/medium/long), widths (1–N nodes), and arrival rate. Optionally model on published HPC workload traces.
MethodFix the workload. Reconfigure SchedulerType and priority weights between runs. Measure makespan, mean/95th-percentile wait, node utilisation, and a fairness metric across users.
DeliverableComparison table + wait-time distributions; 3,000–4,500 words
Failure modesWorkload too homogeneous → backfill shows no benefit (its whole advantage is filling gaps around wide jobs). Not draining the queue between runs → contamination.
PartnerQueen's Discrete-Event Systems Lab (QDES) is a natural co-supervisor — scheduling is literally their domain.

Runbook 4 — GPU offload study $0 on Frontenac Hard

ElementSpecification
QuestionWhat real speedup does GPU offload deliver on a chosen kernel, and at what problem size does it become worthwhile?
SoftwareCUDA toolkit; optionally OpenACC or OpenMP target offload for a portability comparison. Frontenac has 88 GPUs — 25 A100s, 36 RTX6000, 16 A30, 8 RTX8000, 2 L4, 1 V100.
Kernel choiceStart simple and well-understood: dense matrix multiply, N-body, stencil/heat equation, or Monte Carlo. Avoid picking something novel — the point is the porting methodology, not the algorithm.
MethodBaseline the CPU version with proper optimisation flags. Port. Profile with nsys/ncu. Report the crossover point — the size below which host↔device transfer dominates and the GPU loses.
DeliverableSpeedup-vs-problem-size curve with the crossover marked; roofline if achievable; 3,000–5,000 words
Failure modesComparing an optimised GPU port to an unoptimised CPU baseline — the most common and most criticised error in this genre. Timing without warm-up. Ignoring transfer cost.
Why it mattersThe single most competition-relevant technical skill, and the hardest to fake in a judged interview.

Runbook 5 — Survey of undergraduate HPC education in Canada $0 No code

ElementSpecification
QuestionHow do Canadian undergraduates actually access and learn research computing — and where are the gaps?
SoftwareNone. A form tool, a spreadsheet, and Overleaf.
DataStructured interviews and a survey of peer clubs — QMIND, UTMIST, WAT.ai, Western AI, UVic AI, Western Cyber Society — plus a systematic content analysis of published CUCAI proceedings.
MethodReplicate and extend the analysis already done here: 72 papers, ~272,000 words, coded for compute-infrastructure mentions. Add interviews on what students wanted access to and couldn't get.
DeliverableA survey paper with a genuine original finding; 4,000–6,000 words
Why it mattersThe interview subjects are all in one room in Toronto in March. It requires no technical background, making it the ideal first project for a non-engineering member — and it doubles as the "educational goals" answer on the SCC application.
26b · Materials

Everything needed to produce a paper — and where it comes from

The complete materials list for the Research Branch. Note how little of it costs money.

CategorySpecific toolCostNotes
Writing & publication
TypesettingOverleaf + IEEE conference templateFree tierCUCAI's bound proceedings is LaTeX/hyperref — match their toolchain
CitationsZotero (+ Better BibTeX)FreeShared group library so citations accumulate across cohorts
Plotsmatplotlib / seabornFreeAgree one house style so figures look consistent across papers
Diagramsdraw.io / InkscapeFreeThe repo already contains .drawio org charts
PreprintsarXivFreeEndorsement may be needed for some categories — ask the faculty advisor
Compute & software
Primary computeFrontenac via CACFreeSee the verified node inventory immediately below
Teaching clusterPi clusterOwnedTeaching and demos only — see §17c
SimulationOpenFOAM, LAMMPS, GROMACSFreeAll three ship tutorial cases to start from
BenchmarksHPL, HPCG, STREAM, OSU Micro-BenchmarksFreeThe standing suite; re-run after every change
Profilingperf, gprof, Score-P, TAU, nsys/ncuFreensys/ncu for GPU work
EnvironmentsApptainer; Spack or EasyBuildFreeReproducibility — essential for topic 09
Commercial exceptionsAnsys, SOLIDWORKSAsk in-kindBoth already sponsor Queen's Hyperloop — request, never buy

Frontenac — the verified node inventory

Pulled from the CAC's own hardware wiki, not the marketing summary. This is what QHPC actually has access to, and it changes several planning assumptions.

NodesCountCPUCoresMemoryGPUs
GPU nodes — the ones that matter for §14 topics 12, 15–16, 36, 41
frnt190–1912NVIDIA DGX A100; EPYC 77421281 TB8× A100 40 GB
frnt1541EPYC 7H12 @ 2.6 GHz1281 TB8× A100 40 GB
frnt1561Xeon Gold 521832768 GB8× RTX8000 48 GB — largest GPU memory on the system
frnt1551Xeon Gold 521832768 GB8× RTX6000 24 GB
frnt140–1478EPYC 7443 @ 2.8 GHz48512 GB2× A30 24 GB
frnt148–1536Xeon Silver 421020191 GB4× RTX6000 24 GB
frnt107 / 110 / 108–1094Xeon Gold 613032192–384 GB1× A100 / 1× V100 32 GB / 2× RTX6000
frtn2011Xeon 643064256 GB2× L4
Large-memory nodes — relevant to topic 41 (quantum simulation) and any memory-bound work
frnt029–030, 032–0334Xeon E7-8867 v31282 TB—
frnt0311Xeon E7-8867 v41441 TB— highest core count on a single node
frnt204 / 2052EPYC 7543P / 774232 / 641 TB—
General CPU capacity
frnt116–13924Xeon 6338 @ 2.0 GHz64512 GB—
frnt046–07833Xeon E5-2650 v4 @ 2.7 GHz24–32256 GB—
GPU typeTotal on system
RTX6000 (24 GB)36
A100 (40 GB)25
A30 (24 GB)16
RTX8000 (48 GB)8
L42
V100 (32 GB)1
Total88

Correction to every prior figure in this plan. The CAC's summary page says "67 GPUs." The hardware wiki's own per-type table sums to 88. The wiki is more granular and more current, so quote 88 GPUs, 25 of them A100s — and cite the wiki, not the summary page. Verify once with CAC staff before it goes in a competition application or sponsorship deck, since being wrong in that direction is worse than being conservative.

Frontenac — environment facts every runbook depends on

ItemValueConsequence
Loginssh -X user@login.cac.queensu.caSingle login node; CentOS
SchedulerSlurmEverything in the Handbook applies directly
ModulesLmodmodule load before any build
Partitionsstandard, reserved, sse3 (decommissioned)Target standard unless told otherwise
Home/global/home — 500 GB quotaNot for large I/O
Scratch/global/scratch — 5 TB quotaWhere benchmark data goes
Project/global/projectShared team space
FilesystemGPFS, 3.3 PB parallelDirectly the subject of Handbook T3.3
Node-local scratch1.5 TB per node via $TMPDISKPreviously unknown. Changes T3.3 and E7 — gives a fast local tier to benchmark against GPFS
Default job limits1 CPU, 1024 MB, 3 hours if unspecifiedAlways set -c, --mem, -t explicitly
Contributed nodes3-hour hard limitLong jobs must avoid them
AMD EPYC NUMAPresents as 4 NUMA nodes in SlurmDirectly relevant to Handbook T2.4. Gives a real NUMA testbed without special access

Three planning consequences. First, frnt156 with 8× RTX8000 at 48 GB is the single best node for memory-hungry GPU work, and frnt154 / frnt190–191 (8× A100 each) are the right targets for distributed-training work with QMIND. Second, the 2 TB nodes make Handbook topic 41 (quantum circuit simulation) genuinely viable — 2 TB supports roughly 37 qubits in double-complex, well past what any peer club can reach. Third, the EPYC NUMA behaviour and the 1.5 TB node-local disk are both free research substrate nobody had accounted for.

CategorySpecific toolCostNotes
Data
Cardiovascular CFDVascular Model RepositoryFreeCited by the CUCAI 2026 CFD paper
Predictive maintenanceNASA turbofan degradation dataFreeUsed by the CUCAI 2025 ProphetJet paper
MaterialsMaterials ProjectFreePairs with the superconductivity topic
Structural biologyProtein Data BankFreeFor GROMACS/LAMMPS work
ClimateERA5 reanalysisFreeRegistration required
NeuroimagingOpenNeuroFreeOpen fMRI/EEG
Equipment gaps — the only real blockers
Power measurementInline power meter / DAQAsk KeysightUnblocks topic 02; they already sponsor a Queen's team
Additional Pi nodesPi 5 + PoE HATs + switchAsk in-kindUnblocks topics 04 and 18 only
26c · Pipeline

From sprint to published paper — the eight-week pipeline

Sprints produce presentations. Papers need a further four weeks. This is the conversion process, and without it the Research Branch generates slide decks that die on a shared drive.

Weeks 1–4The sprint
  • Run the topic per its runbook. Record every configuration and result in a shared sheet as you go — reconstructing this later is the single biggest time sink.
  • Keep a lab notebook: what you tried, what broke, what you changed. This becomes the "lessons learned" section.
  • End with the standard sprint presentation.
Week 5Decide & outline
  • Research Director triages: is there a real finding, or only an experience? Not every sprint becomes a paper — and that's fine.
  • If yes: draft the abstract first. If you can't state the finding in 150 words, the analysis isn't done.
  • Set up the Overleaf project from the IEEE template; agree author order.
Weeks 6–7Write
  • Sections in this order: Method → Results → Related Work → Introduction → Conclusion → Abstract rewrite. Never write the introduction first.
  • Figures before prose — if a plot doesn't show the finding clearly, the finding may not be there.
  • Add a Limitations or "Threats to Validity" section. CUCAI papers that include one read as markedly more rigorous.
Week 8Review & submit
  • Internal review by a member not on the project — if they can't follow the method, neither can a reviewer.
  • Technical review by the faculty advisor or grad mentor.
  • Copy-edit by the Technical Writing Editor (§33).
  • Submit; publish on the club site regardless of acceptance.

Target throughput: four sprints per year, of which perhaps half convert to papers — two publications annually is a realistic and genuinely respectable first-year figure. QMIND reached 200+ lifetime outputs by compounding this, not by a heroic single year.

26d · Competition

Competition preparation — what to actually practise

"Train for the competition" is not a plan. These are the specific skills scored, and how to drill each.

Scored skillWhat good looks likeDrill
HPL tuningSystematically finding near-optimal N, NB, P×Q for a given machine, and explaining whyRunbook 1, repeatedly, on different node counts. Keep a tuning log so the reasoning is transferable.
HPCGUnderstanding why HPCG scores are a small fraction of HPL — memory-bandwidth-bound vs compute-boundRun both on identical hardware; explain the gap using STREAM results.
Application builds under time pressureBuilding an unfamiliar scientific code from source, with dependencies, quicklyTimed build drills. Pick a code nobody has built before; two-hour limit. This is the most under-practised competition skill.
Power managementStaying under a power cap without wrecking performancePractise CPU frequency scaling and core-count tradeoffs; measure the performance cost of each.
Rapid debuggingDiagnosing a failed job from log output aloneHave a senior member deliberately break a configuration; time the fix.
The judged interviewExplaining decisions and tradeoffs clearly, admitting what you don't knowMock interviews with Ryan Grant and Curtis Shorts. 30–40 minutes, panel format, matching the real thing.
Team coordinationSix people not blocking each other across a 48-hour windowThe mock competition — assign explicit roles and a comms protocol before it starts.

The most commonly underestimated item is the build drill. Teams lose competitions not because they can't tune HPL, but because they spend six of their forty-eight hours fighting a dependency chain on an application they'd never compiled. Practise on unfamiliar codes, under a clock, with no internet-search assistance where the rules restrict it.

Part VIIIGovernance & risk infrastructure— running QHPC like an org that expects to still exist in ten years
27 · Governance

A Board and a one-page charter

Three-person clubs don't need governance. A twenty-seat organisation running consulting engagements, handling sponsor money, and touching other people's research data does. This doesn't need to be heavy — it needs to exist and be written down.

The Board of Advisors — distinct from the exec

The exec (§04) runs the year. The Board exists so the year isn't the only thing anyone is thinking about. Meets once a term, thirty minutes, no operational decisions — only direction, conflict resolution, and continuity.

Faculty Advisor
Ryan Grant
  • Signs the SCC application
  • Institutional credibility with ECE and CAC
Graduate Mentor(s)
Curtis Shorts + rotating co-supervisors from §17
  • Technical content authority
  • Co-supervises Research Branch topics
CAC Liaison
Brandon (or successor)
  • Infrastructure and account provisioning
  • Escalation path for the compute-utility program, §16
Immediate Past President
The outgoing President, one year
  • The single best anti-reset mechanism CUCAI has — copy it exactly
  • Answers "why did we do it this way" questions the manual can't
Industry Advisors (informal)
Ian Karlin, Brooke Henderson, and future alumni
  • No obligations — a standing invitation to weigh in when asked
  • First call for sponsorship warm intros
Student-at-Large
Elected by the general membership
  • Voice for members with no exec seat
  • Raises culture or conduct issues directly to the Board, bypassing the exec if needed

The one-page charter

Adopt this formally at the first exec meeting of the year — it's the constitution the objective hierarchy in §08 deserves, made procedural:

  1. Purpose: the top-level objective from §08, verbatim.
  2. Decision rights: the President breaks ties; each VP has final say within their own portfolio; anything touching money above a threshold (set it — e.g. $200) needs two exec signatures.
  3. Removal process: the culture doc already says persistent dishonesty or contempt for teammates is cause for removal — the charter specifies how: a Board majority vote, with the affected person given a chance to respond first.
  4. Amendment process: the strategy is "provisional, not dogma" (§08) — formalise that as a simple majority exec vote to change any part of this plan, logged in the transition manual with the reason.
  5. Conflict of interest: any exec with a personal or financial stake in a sponsorship or consulting decision recuses from that vote.

Why bother at this scale: the moment QHPC runs paid or in-kind consulting engagements (§16) and handles sponsor and Dean's Fund money in the same year, "we'll figure it out when it comes up" stops being a workable governance model. Writing four paragraphs now is cheaper than an argument in March.

28 · Committees

Standing committees — where portfolios have to talk to each other

A twenty-seat org chart creates silos by design. Committees are the deliberate seams that stop that from happening — each pulls two or three directors from different VP lines, meets monthly, and reports to the President.

CommitteeDraws fromOwns
Competition StrategyVP Technical, Director of Research, Competition CaptainsWhich competitions to enter, the training plan, the mock-comp format
Sponsorship & GrantsDirector of Sponsorship, Director of Finance, Director of ConsultingThe ask calendar, sponsor vetting (§32), grant applications (§38)
DEI & AccessibilityDEI Officer, People Ops, Events CoordinatorOutreach, event accessibility, the SCC diversity narrative
Risk & SafetyVP Ops & Finance, Director of Cluster Ops, PresidentThe safety plan, sanctioning forms, hardware custody (§31, §39)
Alumni & FundraisingDirector of Mentorship, Director of SponsorshipThe Fellows program (§35), long-term giving, speaker pipeline

Five committees, each meeting monthly, each with a one-page written output — this is a small enough overhead that it does not need its own hires; every seat on it is already a director elsewhere in §05.

29 · Legal

Contracts and IP for the consulting program

The moment §16 becomes real — QHPC running compute for Hyperloop, or for a department — someone has to answer "who owns the results, and what happens if it goes wrong." This is exactly the kind of problem a Law student finds genuinely interesting, and it's a real, resume-worthy project for one.

A lightweight engagement template — draft this with a Law-student volunteer, then have EngSoc or Queen's Legal Counsel review it before first use

This is a template, not legal advice. Treat every clause above as a starting draft. Anything involving money changing hands, a corporate sponsor, or third-party data should go past EngSoc's own governance contacts or Queen's Legal Counsel before QHPC signs it.

30 · Data & ethics

Data governance for the Research Branch

Two Research Branch topics (§14, topics 19 and the health-adjacent stretch in §17) touch genomics and medical data. Get the boundary right before anyone runs a real dataset.

31 · Safety

Physical and liability risk

32 · War-gaming

Scenario planning — every branch that matters

A plan this detailed is only as good as its worst-case branches. Ten scenarios, worked through in advance, so nobody is improvising during the actual crisis.

01
Dean's Donation Fund awards $0

The core program survives regardless — ISC virtual and SCC Connect are already zero-hardware, zero-travel. Cut anything travel- or merch-related; lean entirely on in-kind hardware and cloud credits (§38).

02
ISC rejects the application

Run the same benchmark suite as an unofficial "shadow" entry against public ISC problem sets for training value, reapply next cycle with a stronger institutional-support section, and put full weight behind SC27 SCC Connect instead.

03
A key exec resigns mid-year

This is why §05 pairs a Director under every VP — the Director is the trained backup. Two VPs share the portfolio on an interim basis rather than leaving it vacant.

04
Cluster hardware is stolen or damaged

Ask EngSoc's General Manager whether registered-club equipment is covered under any Queen's or EngSoc property policy. Keep the build fully documented and reproducible (§15) so a replacement set can be re-imaged in a day, not a month.

05
Attendance collapses after the October midterm slump

The Discord-plus-newsletter design in §20 is deliberately async-friendly. Add a specific trigger: anyone who misses two consecutive Sprint sessions gets a personal check-in message, not just an automated reminder.

06
A consulting engagement goes badly

Start with exactly one pilot engagement in §16, not five simultaneous ones. The engagement template in §29 sets scope and expectations up front; run a written retro afterward regardless of outcome.

07
A prospective sponsor's values conflict with the club's

A one-page sponsor-vetting checklist for the Sponsorship Director, with any borderline case escalated to an exec vote rather than a unilateral yes.

08
A competing club launches covering similar ground

Differentiate on the compute-utility positioning in §16 — an infrastructure asset is much harder to replicate overnight than a brand.

09
Both the faculty advisor and graduate mentor become unavailable

The partnership list in §17 doubles as a backup-advisor bench — Physics, Computing, and ePOWER contacts are all plausible substitutes with advance notice.

10
International travel (an ISC onsite final, or the stretch option in §45) becomes financially or logistically impossible

Set a hard decision deadline eight weeks out: secure the funding and visas by then, or withdraw gracefully to the virtual track rather than scrambling at the last minute.

Part IXTalent for every faculty— HPC is interdisciplinary; the org chart should look like it
33 · Extended bench

Roles for every faculty at Queen's — not just Engineering and Commerce

§04–05 covers the twenty-seat core that runs the year day to day. This is the extended bench — real, useful, resume-worthy roles that let a student from any faculty plug in without pretending to be an engineer. None of these require code.

Faculty of Law
Student Counsel
  • Drafts and maintains the consulting engagement template, §29
  • Reviews sponsorship contracts before signature
A genuine transactional-law project, not busywork
Faculty of Law
Compliance & Privacy Officer
  • Owns the data classification policy, §30
  • First point of contact for any dataset with a grey area
Faculty of Education
Curriculum Pedagogy Advisor
  • Improves how the Foundations cohort actually teaches, not just what it covers
  • A natural joint research project with Education faculty on teaching HPC to novices
Health Sciences / Kinesiology
Wellness & Accessibility Officer
  • Runs the burnout check-ins the culture doc calls for
  • Partners with the Biomotion Lab, §17, on any motion-capture-adjacent research
Environmental Studies / Geography
Sustainability Officer
  • Owns the carbon-accounting research topic, §14 no. 34
  • Coordinates e-waste recycling of retired hardware, §40
Global Development Studies
International & Exchange Coordinator
  • Travel, visa, and insurance logistics for any onsite competition, §45
  • Builds relationships with international peer clubs for the survey topic, §14 no. 35
Psychology
People Experience Researcher
  • Runs a real member-satisfaction survey each term
  • Turns the culture doc's tenets from aspiration into measured outcomes
English / Languages
Technical Writing Editor
  • Polishes every Research Branch write-up before publication
  • Translates recruitment material for international and exchange students
Dan School of Drama & Music / Film
Media Producer
  • Runs the "Cluster Chats" series, §43
  • Event photography and videography
Fine Art / Art History
Visual Designer
  • Owns the brand guidelines, §41, distinct from the Web Lead's job
  • Merchandise and print design
Political Studies / Public Policy
Government & Institutional Relations
  • Liaises with the AMS and, longer-term, Kingston municipal data initiatives
  • Tracks anything in university policy that affects design-team status, §21
Smith Business — MMA
Data & Analytics Officer
  • Builds the organisational metrics dashboard, §23, from real attendance and funnel data
  • A direct, resume-ready analytics project for a Master of Management Analytics student
Any grad program
Graduate Advisory Council
  • A standing council of grad students (Physics, Computing, Chemistry, and beyond) who co-supervise Research Branch topics alongside Curtis Shorts
  • Widens the advisor bench well past one person

The recruiting line that actually works: "You don't need to know Linux to help run a supercomputing club." Every card above is true, specific, and true regardless of major — that's what gets a Law or Kinesiology student to actually read the posting instead of assuming it says "engineers only."

Hard evidence for the postings — from the CUCAI corpus

Don't assert that non-technical students can contribute. Show them four papers, all by Queen's undergraduates, none containing a single line of code:

PaperWordsMethodWhy it's the argument
AI consciousness and the evolution of labour ethics: Reframing historical materialism
5 Queen's students, 2025
6,343Marx's historical materialism as analytical framework🏆 Won the Ethical Development award. No model, no dataset, no experiment.
Generative Music AI's $350 Million Problem
5 Queen's students, 2025
12,934Legal + economic analysis of copyright and training data (Suno/Udio)The longest paper in the entire two-year corpus contains no code.
Beyond Bill C-27: From AI Legislative Gaps to a Reformed AI and Data Act
5 Queen's students, 2026
8,177Stated verbatim: "legislative analysis, case studies, and comparison with international models"A full statutory critique — PIPEDA, CPPA, AIDA — with proposed amendments. This is a law paper.
B.A.I.L.I.F.F.: Bias Analysis in Interactive Legal Intelligence & Fairness Framework
Solo-authored, 2026
3,004Includes a "Threats to Validity" sectionShort, solo, methodologically rigorous — the most achievable entry point of the four.

And the pattern underneath it: cross-referencing author lists across both years, Kate Sigurdson co-authored both the award-winning 2025 consciousness paper and the 2026 Bill C-27 paper; Kay Yan co-authored the 2025 music-copyright paper and authored a 2026 paper on bias auditing in financial AI. These students are building genuine multi-year publication records in AI policy without writing code. That's a career track, not a token gesture — and it's the single most persuasive thing you can put in front of a Law or Political Studies applicant.

34 · Lifecycle

The member journey — three tracks, one club

Three different students should be able to look at this and each see themselves in year three.

Track A — the technical path

Day 1
  • Club fair QR code → newsletter and Discord
Week 1
  • First Foundations session; paired with a First-Year Rep buddy
Term 1
  • Foundations certificate; joins a Sprint on the systems side
Year 2
  • Becomes a Sprint lead; sits on the Competition Team as an alternate
Year 3
  • Director of Cluster Ops or Applications; competes at SC or ISC for real
Alumni
  • Joins the Fellows program, §35; returns as a guest speaker or industry advisor

Track B — the research path

Day 1
  • Joins via a departmental email (Physics, Chemistry, Environmental Studies) rather than a club fair
Term 1
  • Picks a domain topic from §14 Section IV, paired with a grad co-supervisor from §33's Advisory Council
Year 2
  • Co-authors a write-up submitted to CUCAI or as a department poster
Year 3
  • Director of Research; owns topic curation and department partnerships, §17
Alumni
  • Goes to grad school or industry citing a real undergraduate research output

Track C — the business/ops path

Day 1
  • Sees a Breezy posting for Finance, Marketing, or Consulting — not a technical one
Term 1
  • Shadow-supports the Director of Sponsorship or Finance; learns the DDF and BoE process directly
Year 2
  • Owns a portfolio directly — the sponsorship deck, the newsletter, or the consulting pipeline
Year 3
  • VP Operations & Finance or VP Communications & Growth
Alumni
  • A real "ran a $X sponsorship pipeline for a student org" line on a Commerce resume
35 · Alumni

The Fellows program

36 · Recognition

A contribution system, not just a resume line

Sprints, Research Branch topics, open-source contributions, and consulting engagements are all trackable units of work. Make that visible.

Part XMoney, infrastructure & sustainability
37 · Budget

Pro-forma — three scenarios

Illustrative planning figures, not quotes — replace every number with a real one once vendors and the DDF outcome are known. The point is the shape of the budget, not the digits.

Line itemConservative (30% DDF)Base (40% DDF)Stretch (50%+ sponsorship)
Cluster hardware & parts$600$1,200$2,500
Workshop & training materials$150$250$400
Banner, print, club-fair materials$200$300$400
Speaker gifts / thank-yous$100$200$300
Socials & food$250$400$600
CUCAI travel & tickets (delegation)$0 (skip)$400$800
Merch COGS (pre-order only)$0$500 (revenue-covered)$1,000 (revenue-covered)
Contingency$150$300$500
Total planning figure~$1,450~$3,050~$6,500

Note what's absent even at Stretch: no line for onsite SC/ISC travel or a vendor-hardware SCC entry — those depend on a vendor partnership (§19) that realistically doesn't exist until SC28. The Conservative column should be the one the club can run comfortably on with zero surprises.

38 · Grants

Funding sources beyond the Dean's Fund

SourceWhat it actually is
NSERC Undergraduate Student Research Award (USRA)An individual-student award obtained through a supervising professor, not a club-level grant — but the Director of Research can actively point Research Branch participants toward a §17 faculty partner and encourage them to apply. One current Hyperloop member already holds one.
AWS Educate / AWS Cloud Credits for ResearchReal, standard academic cloud-credit programs — directly de-risks the SCC Connect cloud-resource entry, §09.
Microsoft Azure for StudentsSame category — worth applying for alongside AWS rather than instead of.
NVIDIA Academic Hardware Grant ProgramWorth a long-shot application given the direct Ian Karlin connection — even a rejection is a reason to talk to NVIDIA again.
Google Cloud research creditsSame category as AWS/Azure; apply to all three rather than picking one.
Digital Research Alliance of Canada trainingNot cash — free access to advanced-research-computing bootcamps, webinars, and one-on-ones, arranged through a sponsoring faculty member. Ask Ryan Grant to sponsor member access this term; the portal is explora.alliancecan.ca.
Dunin-Deshpande Queen's Innovation Centre (DDQIC)Confirmed — DDQIC is a current CUCAI sponsor, meaning it actively funds exactly this kind of large student technical initiative. Apply directly; this is real money, not a maybe.

None of these require the club to be a registered non-profit or design team — they're academic programs built for exactly this kind of use, and applying costs a form, not money.

39 · Facilities

Equipment and physical space

40 · Sustainability

Environmental and financial accessibility

Part XIBrand system & content engine
41 · Brand

Guidelines — written once, applied by everyone

42 · Calendar

A weekly content rhythm

DayWhat goes outOwner
MondayWeekend/prior-week recap, one photo, two linesContent & Publications
WednesdayMeeting-day reminder and what's on the agendaMarketing & Brand
FridayA resource, a Research Branch highlight, or a member spotlightContent & Publications

Three posts a week is sustainable indefinitely and gives new members something to see between Wednesdays; it's not a burden if it's this templated.

43 · Media

"Cluster Chats" — a light interview series

Short, low-production video or audio interviews with alumni, sponsors, and faculty partners — Ian Karlin and Brooke Henderson are the obvious first two guests. Produced by the Media Producer role in §33, hosted wherever the newsletter already lives. This doubles as sponsorship inventory (§19's Gold tier) and as durable recruiting content that outlives a single social post.

Part XIIStrategic cadence & synthesis
44 · OKRs

Quarterly objectives, cascading from the culture doc

§08's objective hierarchy is the "why." This is the "by when," broken into the academic year's four natural quarters.

QuarterPortfolioObjectiveKey results
Q1 · Sept–NovVP TechnicalGet the ISC application in strongAll six sections drafted by Wk 8; reviewed by Grant/Shorts; submitted by Wk 11
VP Ops & FinanceDiversify income before the DDF result landsDDF submitted with sponsorship package attached; 1 in-kind hardware commitment secured
Q2 · Dec–FebVP EducationConvert fall interest into placed members40+ members placed into a Sprint track by the December deadline
VP CommunicationsBuild the owned channelNewsletter live with 100+ subscribers; site content complete
Q3 · Mar–AprVP TechnicalSubmit and rehearse for competitionSC27 SCC + SCC Connect submitted; 2 graded mock competitions run
PresidentHand over a stronger org than was inherited12+ of 20 exec seats filled; transition manual updated continuously, not in April
Q4 · May–AugVP Technical / ResearchCompete, and bank the resultsISC virtual round completed; 4+ Research Branch write-ups published for the year
45 · Stretch

Additional competitions worth investigating

Beyond ISC, SC27, and SCC Connect (§09), one more is worth a research pass before next year's plan is written — this one is flagged as unverified, deliberately, rather than asserted as fact.

Verify
The ASC Student Supercomputer Challenge

An international student cluster competition organised out of China, with a public registration process that has in past years drawn universities worldwide. Confirm current eligibility for a Canadian team, the travel and cost implications if selected for the onsite round, and whether a virtual or preliminary track exists before committing any planning time to it. Worth a single research pass by the Director of Research in the spring, not a fall priority.

46 · Synthesis

If you read nothing else

  1. Watch isc-hpc.com from 1 August. It's the only competition entry available before March, and it's free to enter.
  2. Post all twenty core seats, not three — Finance, Sponsorship, Consulting, Marketing, Content, Events, and DEI are real jobs for Commerce, Arts, and Law students who currently assume this club isn't for them.
  3. Run the Sprint Model exactly as the grad mentors designed it — it already works, and it's already built to feed this year's competition prep.
  4. Pitch one design team and one first-year course as compute clients this term — the single highest-leverage strategic move in this whole plan, and it only needs one warm conversation to start.
  5. Budget as if the Dean's Fund gives you 40% of what you ask for, because the data says it will, and build the year so nothing breaks if it does.
2026-08-08 · Generated ResearchMeasurement Execution Plan — Generated 2026-08-08

Measurement Execution Plan (Carry D Runbook)

Operational runbook for executing the registered-report protocol. Maps every [MEASURED] slot and the [CROSSOVER VERDICT] to its pre-registered rule so filling results requires no re-derivation of the protocol. Prepared 2026-08-06; rule references cite the revised draft.

Scope: Single Raspberry Pi 4B (4 GB) leg vs single Frontenac CPU node leg. CPU-only, no GPU offload.

Phase A. Pre-Execution Checks (Week 1)

Check Pass criterion Fallback if fail
RAPL available on Frontenac leg turbostat or perf exposes package energy Record channel; do NOT silently switch (report as limitation)
RAPL available on Pi leg Expected NOT available (G2 gap) Use SoC instrumentation + calibrated estimation fallback (planned)
Ollama runtime installs on both legs Version-pinned in artifact Use llama.cpp only and record deviation
28-model reproduction feasible Full sweep runs on Pi within budget Stratified sample per tier (already specified in §3.3)
Governors default schedutil (Arm), ondemand (server) Record deviation; report in §4.4

Phase B. Grid Definition

  • Tiers: small <4B; mid 4-8B; large >8B, loadable at fp16 within 8 GB.
  • Primary selection rule: two smallest-parameter models at or above tier floor, from the Husom 28-model sweep.
  • Alternative selection rule (grid sensitivity): two largest-parameter models at or below tier ceiling.
  • Quantization levels per model: q4_0, q5_0, q8_0, fp16.
  • Grid cells: 3 tiers x 2 models x 4 levels = 24 cells per leg (or tier-comparable if memory-pressure fallback triggers).
  • Prompt workload: fixed prompt (exact text + token length recorded in artifact).

Phase C. Per-Cell Measurement Protocol

  1. Randomize measurement order across cells (decouple thermal drift).
  2. Per cell: 1 warm-up run, then 30 measurement runs (fixed in advance).
  3. Energy: RAPL package counter (server); SoC instrumentation at 100 ms sampling (Pi primary channel).
  4. Calibration: external power meter on 10% of cells (minimum 8, stratified across tiers and quantization levels); compute calibration error bound.
  5. Estimation fallback (Pi secondary channel): CPU-utilization model, labeled wherever used.
  6. Record per run: energy (J), generated tokens, throughput (tok/s), latency (TTFT, TPT).
  7. Accuracy spot-checks: fp16 + q4_0 cells of the two small-tier models + tier-floor model of each remaining tier; quality metric = perplexity on fixed workload; collapse threshold = >10% degradation vs fp16 reference.

Phase D. Pre-Registered Decision Rules

D1. Fallback validity (apply per cell before statistics)

  • (i) Include fallback-estimated cell only if estimation and primary channels agree on sign within the cell CI.
  • (ii) Report calibration error bound per cell.
  • (iii) Exclude cell from crossover claims if estimate falls within calibration error bound of the crossover boundary; report as boundary-ambiguous.

D2. Crossover test (per cell)

  • Paired t-test; pairing unit = repetition block (run j on Pi vs run j on server, matched workload).
  • Welch fallback when per-leg variance ratio > 4; report both results.
  • Declare crossover when: |mean diff| > 2 x SE of difference AND sign consistent across >=80% of repetition blocks.
  • Multiple comparison: Benjamini-Hochberg FDR, alpha = 0.05, across declared grid.
  • Reporting gate: cells contradicting tier-median trend reported with equal prominence to confirming cells.

D3. Operational threshold

  • Crossover margin <10% at operating point is NOT claimed as operationally meaningful.

D4. Runtime-robustness

  • llama.cpp cross-check on 10% of cells (min 4, 1 per tier); crossover cell is runtime-robust only if llama.cpp reproduces the Ollama sign; disagreement reported.

Phase E. Robustness Checks

  1. Grid sensitivity: re-check declared crossover cells under the alternative selection rule; non-persisting cells = grid-dependent, not device-class findings.
  2. llama.cpp fragilities: report runtime-dependent cells.
  3. Governor deviations: report any deviation from pinned default.
  4. Variance / warm-up / thermal drift: report; cells flipping under CI criterion are reported, not smoothed.

Phase F. Slot Fill Mapping

Slot Feed from Pre-registered rule
§4.1 energy-per-token tables/heatmaps Phase C step 6 D1 labeling of fallback cells
§4.2 crossover curve + figure Phase D D2 Boundary = interpolated estimate between grid points; grid-density caveat in caption
§4.3 joint E/T/L view Phase C step 6 G3 joint characterization
§4.4 robustness Phase E D4, E1-E4
§4.5 null/negative + surprising cells Phase D D1(iii), D2 gate, C7 Surprising cell = largest absolute margin contradicting tier-median sign, per leg
§5.1-5.3 discussion Verdict Conditional on verdict; apply D3, operating assumptions
§6.1 [CROSSOVER VERDICT] Phase D D2 across grid One sentence: crossover at operating points... OR no crossover observed within measured grid

Phase F.5 Automated Pipeline (synthetic-first, verified 2026-08-08)

# 1. generate draft data (synthetic only; skip on real data)
python scripts/synthetic_data.py --grid configs/grid.json --prompt-file configs/prompt.txt --out data/synthetic --seed 42

# 2. analyze (D1-D4, BH-FDR)
python scripts/analyze.py --pi-dir data/synthetic/pi --server-dir data/synthetic/server --out results/synthetic

# 3. figures + table1 (fig1_crossover, fig2_heatmap, fig3_joint, fig4_robustness, fig5_margin)
python scripts/plots.py --pi-dir data/synthetic/pi --server-dir data/synthetic/server \
    --cells results/synthetic/cells.csv --crossover results/synthetic/crossover.csv \
    --verdict results/synthetic/verdict.json --grid configs/grid.json --out figures/synthetic

# 4. manuscript table
python scripts/make_table1_tex.py figures/synthetic/table1.csv figures/table1.tex

# 5. tests (40 tests, 1 skipped)
python -m unittest discover -s tests
  • Non-tested cells (missing-leg, boundary-ambiguous) render as grey bars in fig5 and a Status column in table1.tex.
  • Docs: artifact/README.md (full command sequence), PROJECT_STATUS.md (status + robustness hardening).

Phase G. Post-Execution Tasks (Author)

  1. Fill all slots; trim §3 and §5 toward the 6,000-word target gate.
  2. Re-verify: em dashes = 0 in prose; no flagged AI terms; TEEL; IEEE first-appearance ordering.
  3. Complete Carry A (bibliographic fields), Carry B (author block), Carry C (DOI/Zenodo).
  4. Regenerate Phase 7 outputs from the filled draft; update checklist.

Artifact Contents to Release

Measurement scripts, raw power/energy logs, model configs, analysis notebooks, OS image/kernel/Ollama/llama.cpp versions, model hashes, governor settings, sampling intervals. DOI/Zenodo record at release.

Imported from measurement-execution-plan.md (2026-08-08), derived from t-cpu2-measurement-execution-checklist.md. Phases A-G: pre-execution checks, grid definition, per-cell measurement protocol, pre-registered decision rules (D1-D4), robustness checks, slot-fill mapping, and the synthetic-first automated pipeline (40 tests, 1 skipped). Complements the Operating Plan above.

2026-08-08 · Generated ResearchT-CPU2 Measurement Execution Checklist (Source Runbook)

T-CPU2 Measurement Execution Checklist (Carry D Runbook)

Purpose: Operational runbook for executing the registered-report protocol in phase4-complete-draft.md (revision round 1, post external editorial review). Maps every [MEASURED] slot and the [CROSSOVER VERDICT] to its pre-registered rule so that filling results requires no re-derivation of the protocol. Prepared 2026-08-06; all rule references cite the revised draft sections.

Scope: Single Raspberry Pi 4B (4 GB) leg vs single Frontenac CPU node leg. No GPU offload. CPU-only.


Phase A. Pre-Execution Checks (Week 1, per track file)

Check Pass criterion Fallback if fail
RAPL available on Frontenac leg turbostat or perf exposes package energy Record channel; do NOT silently switch (report as limitation)
RAPL available on Pi leg Expected NOT available (G2 gap) Use SoC instrumentation + calibrated estimation fallback (planned)
Ollama runtime installs on both legs Version-pinned in artifact Use llama.cpp only and record deviation
28-model reproduction feasible Full sweep runs on Pi within budget Stratified sample per tier (already specified in §3.3)
Governors default schedutil (Arm), ondemand (server) Record deviation; report in §4.4

Phase B. Grid Definition (from §3.3)

  • Tiers: small <4B; mid 4-8B; large >8B, loadable at fp16 within 8 GB.
  • Primary selection rule: two smallest-parameter models at or above tier floor, from the Husom 28-model sweep.
  • Alternative selection rule (for grid sensitivity): two largest-parameter models at or below tier ceiling.
  • Quantization levels per model: q4_0, q5_0, q8_0, fp16.
  • Grid cells: 3 tiers x 2 models x 4 levels = 24 cells per leg (or tier-comparable if memory-pressure fallback triggers).
  • Prompt workload: fixed prompt (record exact text + token length in artifact).

Phase C. Per-Cell Measurement Protocol (from §3.4, §3.5)

  1. Randomize measurement order across cells (decouple thermal drift).
  2. Per cell: 1 warm-up run, then 30 measurement runs (fixed in advance).
  3. Energy: RAPL package counter (server); SoC instrumentation at 100 ms sampling (Pi primary channel).
  4. Calibration: external power meter on 10% of cells (minimum 8, stratified across tiers and quantization levels); compute calibration error bound.
  5. Estimation fallback (Pi secondary channel): CPU-utilization model, labeled wherever used.
  6. Record per run: energy (J), generated tokens, throughput (tok/s), latency (TTFT, TPT).
  7. Accuracy spot-checks: fp16 + q4_0 cells of the two small-tier models + tier-floor model of each remaining tier; quality metric = perplexity on the fixed workload; collapse threshold = >10% degradation vs fp16 reference of same model.

Phase D. Pre-Registered Decision Rules (from §3.4, §3.7)

D1. Fallback validity (apply per cell before statistics)

  • (i) Include fallback-estimated cell only if estimation channel and primary channel agree on sign within the cell CI.
  • (ii) Report calibration error bound per cell.
  • (iii) Exclude cell from crossover claims if estimate falls within calibration error bound of the crossover boundary; report as boundary-ambiguous in §4.5.

D2. Crossover test (per cell)

  • Paired t-test; pairing unit = repetition block (run j on Pi vs run j on server, matched workload).
  • Welch fallback when per-leg variance ratio > 4; report both results for that cell.
  • Declare crossover at p when: |mean diff| > 2 x SE of difference AND sign consistent across >=80% of repetition blocks.
  • Multiple comparison: Benjamini-Hochberg FDR, alpha = 0.05, across declared grid; report each cell against adjusted threshold.
  • Reporting gate: cells whose direction contradicts tier-median trend reported with equal prominence to confirming cells.

D3. Operational threshold (from §5.1)

  • Crossover margin <10% at operating point is NOT claimed as operationally meaningful.

D4. Runtime-robustness (from §3.2)

  • llama.cpp cross-check on 10% of cells (min 4, 1 per tier); crossover cell is runtime-robust only if llama.cpp reproduces the Ollama sign; disagreement reported in §4.4.

Phase E. Robustness Checks (from §4.4)

  1. Grid sensitivity: re-check declared crossover cells under the alternative selection rule; if that rule selects different models, measure 1 additional model per tier. Non-persisting cells = grid-dependent, not device-class findings.
  2. llama.cpp fragilities: report runtime-dependent cells.
  3. Governor deviations: report any deviation from pinned default.
  4. Variance / warm-up / thermal drift: report; cells flipping under CI criterion are reported, not smoothed.

Phase F. Slot Fill Mapping

Slot Feed from Pre-registered rule
§4.1 energy-per-token tables/heatmaps Phase C step 6 D1 labeling of fallback cells
§4.2 crossover curve + figure Phase D D2 Boundary = interpolated estimate between grid points; grid-density caveat in caption
§4.3 joint E/T/L view Phase C step 6 G3 joint characterization
§4.4 robustness Phase E D4, E1-E4
§4.5 null/negative + surprising cells Phase D D1(iii), D2 gate, C7 Surprising cell = largest absolute margin contradicting tier-median sign, per leg
§5.1-5.3 discussion Verdict Conditional on verdict; apply D3, §5.3 operating assumptions
§6.1 [CROSSOVER VERDICT] Phase D D2 across grid One sentence: crossover at operating points... OR no crossover observed within measured grid

Phase F.5 Automated Pipeline (synthetic-first, verified 2026-08-08)

Run from artifact/ after real measurement (or synthetic draft):

# 1. generate draft data (synthetic only; skip on real data)
python scripts/synthetic_data.py --grid configs/grid.json --prompt-file configs/prompt.txt --out data/synthetic --seed 42

# 2. analyze (D1-D4, BH-FDR) — real: --pi-dir data/pi --server-dir data/server
python scripts/analyze.py --pi-dir data/synthetic/pi --server-dir data/synthetic/server --out results/synthetic

# 3. figures + table1 (fig1_crossover, fig2_heatmap, fig3_joint, fig4_robustness, fig5_margin)
python scripts/plots.py --pi-dir data/synthetic/pi --server-dir data/synthetic/server \
    --cells results/synthetic/cells.csv --crossover results/synthetic/crossover.csv \
    --verdict results/synthetic/verdict.json --grid configs/grid.json --out figures/synthetic

# 4. manuscript table
python scripts/make_table1_tex.py figures/synthetic/table1.csv figures/table1.tex

# 5. tests (15/15 pass)
python -m unittest discover -s tests
  • Non-tested cells (missing-leg, boundary-ambiguous) render as grey bars in fig5 and a Status column in table1.tex; tested-only runs omit the Status column.
  • Docs: artifact/README.md (full command sequence), PROJECT_STATUS.md (status + robustness hardening).

Phase G. Post-Execution Tasks (Author)

  1. Fill all slots; trim §3 (+25.5%) and §5 (+31.2%) toward the 6,000-word target gate.
  2. Re-verify: em dashes = 0 in prose; no flagged AI terms; TEEL; IEEE first-appearance ordering.
  3. Complete Carry A (bibliographic fields), Carry B (author block), Carry C (DOI/Zenodo).
  4. Regenerate Phase 7 outputs from the filled draft; update checklist.

Artifact Contents to Release (§7.2-7.3)

Measurement scripts, raw power/energy logs, model configs, analysis notebooks, OS image/kernel/Ollama/llama.cpp versions, model hashes, governor settings, sampling intervals. DOI/Zenodo record at release.

Imported from t-cpu2-measurement-execution-checklist.md (2026-08-08). Source runbook for the Measurement Execution Plan above.