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.
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.
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.
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.
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.
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.
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.
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.
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 team | Requested | Received | Share |
|---|---|---|---|
| Queen's Aerospace | $75,000 | $24,600 | 33% |
| QSET | $54,000 | $23,000 | 43% |
| QRET | $53,500 | $23,200 | 43% |
| aQuatonomous | $18,000 | $8,700 | 48% |
| Qlean | $10,000 | $4,300 | 43% |
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.
Every one of them has three things: an artifact, subteams with named leads, and an external deadline. QHPC has the third only in aspiration.
| Organisation | Scale | Structure | Artifact | The 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. |
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.
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.
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.
Every seat below is postable on Breezy as its own listing. Where a seat is new this year, it says so.
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.
| Process | Responsible | Accountable | Consulted | Informed |
|---|---|---|---|---|
| Dean's Donation Fund application | Director, Finance | VP Ops & Finance | President, Sponsorship Director | Whole exec |
| Competition application (ISC/SCC) | VP Technical | President | Faculty advisor, Director of Research | Whole club |
| A new sponsorship ask | Director, Sponsorship | VP Ops & Finance | President (if >$500 or a name-brand logo) | Comms, for asset use |
| A new consulting engagement (§16) | Director, Consulting | VP Ops & Finance | Student Counsel (§33), the client team's captain | Research Director, for topic overlap |
| Credential and access handover | People Ops Coordinator | President | Outgoing exec | VP Technical, for infra access |
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 seat | Backup |
|---|---|
| President | Either VP, by exec vote at the first meeting of the year |
| VP Technical | Director, Applications & Benchmarking |
| VP Ops & Finance | Director, Finance & Treasury |
| Director, Sponsorship | Director, Consulting & Industry Relations |
| Director, Cluster Ops | A named senior Sprint lead from the systems side |
Today every member gets the same Wednesday meeting, which serves neither the beginner nor the person ready to compete.
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.
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.
Hyperloop publishes its full recruitment process. It's fair, accommodating, and battle-tested on 100+ members a year — adopt it rather than improvising:
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.
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.
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.
Trust people's word until they prove untrustworthy. Dishonesty is cause for removal.
No trash talk, no put-downs, no joking about failing to hit team goals — joke about other things.
Push for the highest achievement, but harsh attitudes toward less-experienced members are grounds for removal, same as disdain for team achievements.
When you must work under an assumption to move forward, say so explicitly and keep testing it.
Escalate to a tiebreaker or defer to whoever is closer to the problem, then commit — no relitigating after the fact.
Everything here is "the best way we know right now." Bring a better idea and the team updates.
| Competition | Application window | Format | Cost to enter | Verdict |
|---|---|---|---|---|
| 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 |
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.
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.
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.
| Wk | Meeting topic | Background tasks / real deadlines |
|---|---|---|
| 1 | Returning members welcome back; senior members choose app or sys lead | Exec recruiting new members; sort out comp application deadlines; contact Brandon at CAC re: team server, target week-1 access |
| 2 | Recruitment intro to the team | Senior members prep app/sys presentations; check isc-hpc.com — ISC 2027 window should be open |
| 3 | Intro to Linux and VM setup | Junior members set up VMs |
| 4 | Intro to parallel computation (MPI) | Junior members run the MPI tutorial homework |
| 5 | App/Systems presentations; form Sprint 1 teams | Senior members prepare Sprint 1 materials from §14's topic list |
| 6 | Sprint 1 work session / Q&A | Begin drafting the ISC application — all six sections |
| Reading week — sprint continues, no formal meeting | ||
| 7 | Sprint 1 work session / Q&A | Senior members prepare Sprint 2 materials |
| 8 | Sprint 1 presentations; form Sprint 2 teams | Circulate ISC draft to Ryan Grant / Curtis Shorts for review |
| 9 | Sprint 2 work session / Q&A | Sponsorship outreach round one goes out |
| 10 | Sprint 2 work session / Q&A | Attend the Dean's Donation Fund preparation workshop |
| 11 | Sprint 2 work session / Q&A | Submit the Dean's Donation Fund application (mid-Nov, 8:00 a.m. deadline) and the ISC 2027 application (~14 Nov) |
| 12 | Sprint 2 presentations | Guest speaker; post the term's write-ups; year-in-review |
| Wk | Meeting topic | Background tasks / real deadlines |
|---|---|---|
| 1 | Welcome back; form Sprint 3 teams | Exec recruiting winter joiners; CUCAI registration opens 15 Jan — register as Student Club Partner |
| 2 | Sprint 3 work session / Q&A | Extra ramp-up sessions for new members; CUCAI registration closes 25 Jan, confirmation by 30 Jan |
| 3 | Sprint 3 work session / Q&A | Extra ramp-up sessions for new members |
| 4 | Sprint 3 presentations; form Sprint 4 teams | Select the competition team — six plus alternates |
| 5 | Sprint 4 work session / Q&A | Mock competition planning begins |
| 6 | Sprint 4 work session / Q&A | Mock competition planning; guest speaker |
| Reading week | ||
| 7 | Sprint 4 presentations; form mock-comp teams | SC27 SCC + SCC Connect applications open ~2 March — begin drafting |
| 8 | Mock competition preparation / Q&A | Send delegates to CUCAI, 7–8 March, Toronto |
| 9 | Mock competition preparation / Q&A | Merch drop via Zeffy (pre-order only) |
| 10 | Mock competition — judged, with the interview component | Submit SC27 SCC + SCC Connect applications (~May window opens) |
| 11 | Prep for the 2027–28 season | Open 2027–28 exec hiring on Breezy |
| 12 | Prep for the 2027–28 season | Year-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.
| Event type | Cadence | Owner | Notes |
|---|---|---|---|
| General meeting | Weekly, 2 hours, Wed, Dunning 10 | President | 30/60/30 split per §10 |
| Foundations session | Weekly, 8 weeks/term | VP Education | Material already written |
| Sprint work session | 4 per Sprint, ×4 Sprints/yr | Director, Curriculum | Core mechanism, §10 |
| Guest speaker | 2 per term | President | Highest-reach content historically |
| Mock SCC | Once, Winter Wk 10 | VP Technical | Judged interview added to match the real thing |
| Club fairs | Sept + Winter re-fair | Events Coordinator | Banner ordered in August |
| Social | Termly | Events Coordinator | Keep the terminal Pictionary tradition |
| EngSoc Design Team Showcase | Annual | President | Bring the Pi cluster |
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.
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.
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.
| Dimension | Measured reality | What it means for QHPC |
|---|---|---|
| Format | IEEE 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. |
| Length | 2,899 / 3,651 / 6,334 words across the three sampled — roughly 6–10 pages | One 4-week Sprint plus two weeks of writing covers this comfortably |
| Team size | 1 to 6 authors. One paper was solo-authored. | Maps exactly onto Sprint team size, §10 |
| Institutions | Queen's, U of T, UVic, McMaster (MacAI), UTMIST, WCS, DAIR, AIW | Genuinely national — submitting means competing with and networking against the strongest clubs in Canada |
| Technical bar | The energy paper applies LSTM to building-energy forecasting — well-established method, competently executed, honestly reported | The bar is "real work, properly written up," not novelty. All 35 topics in §14 clear it. |
| Topic distribution | Heavily weighted to ML/AI applications; light on systems and infrastructure | An HPC systems paper would stand out rather than blend in — a real differentiation opportunity |
Both the 2025 (37 papers) and 2026 (35 papers) proceedings were indexed in full. The shift between them matters:
| CUCAI 2025 | CUCAI 2026 | |
|---|---|---|
| Papers | 37 | 35 |
| Systems / simulation content | Sparse | Noticeably more — CFD solvers, TinyML on microcontrollers, microgrid benchmarking |
| Authorship | Mostly teams of 2–6 | Mostly 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."
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 section | Count | Who it's for | Sprint fit | Handbook tier |
|---|---|---|---|---|
| 0 · Entry (E1–E12) | 12 | First- and second-years, any faculty, zero background | First sprint | Vol I · Tier 1 Foundation |
| I–VII · Core (1–35) | 35 | Members who've completed one sprint | Sprints 2–4 | Vol I · Tiers 2–3 Developing, Intermediate |
| VIII · Frontier (36–47) | 12 | Senior members and competition team | Year 2+ | Vol II · Tier 4 Advanced |
| IX · Queen's-specific (48–53) | 6 | Paired with a faculty co-supervisor | Any, with a partner | Vol II · Tier 5 Frontier |
Compare the Pi cluster against a Frontenac partition of similar core count — where does ARM lose or win?
Measure real power draw on the Pi cluster vs an equivalent Frontenac job — a genuine "Green HPC" measurement at student scale.
FIFO vs backfill vs fair-share under synthetic contention. Directly useful to Queen's own School of Computing (see QDES lab, §17).
How allreduce/broadcast latency scales with node count and topology on the Pi cluster.
I/O-bound workload timing across storage backends.
Directly relevant to how modern HPC centres (including the CAC) actually run jobs.
Price a chosen workload on AWS/Azure/Oracle against the club's own cluster — ties straight into the SCC Connect cloud-resource track.
Fault-tolerance mechanisms for long-running jobs.
Does the same simulation give identical results across reruns, compilers, or optimisation flags? A genuinely publishable meta-question.
Pick one: LAMMPS, GROMACS, or OpenFOAM. The exact analysis the Sprint Model's "applications" track already asks for.
Same kernel (matrix multiply or N-body), three parallelisation models, one comparison.
Port a CPU kernel to CUDA or OpenACC and measure the real speedup on Frontenac's GPU nodes.
Monte Carlo simulation as the test case.
MPI vs PGAS (UPC/Chapel) vs task-based (Charm++) on a toy problem — an accessible systems-literature survey plus a small implementation.
Data-parallel vs model-parallel training across multi-GPU nodes.
Latency/throughput vs batch size and quantisation level — genuinely timely, and a joint submission with QMIND writes itself.
A student-scale reproduction of "Green AI"-style measurement.
Uses the Pi cluster as a stand-in for distributed edge devices.
Run an open bioinformatics variant-calling pipeline at scale — a real bridge to Life Sciences and Kingston Health Sciences Centre via the CAC.
Partner candidate: Environmental Studies.
Direct value to Hyperloop (pod aerodynamics), Aerospace, and Relectric — this is a consulting engagement in disguise, see §16.
Partner candidate: Department of Chemistry.
Partner candidate: Department of Physics, Engineering Physics — Queen's has a strong particle-astrophysics community via the Sudbury Neutrino Observatory Institute.
Partner candidate: Civil Engineering, GeoEngineering Centre.
Partner candidates: Beaty Water Research Centre, and aQuatonomous's own "ecological & water research" subteam.
Partner candidate: Smith School of Business, Economics — a genuine Commerce-student research lane.
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.
Attack-surface analysis and mitigations, written as a defensive-hardening guide.
Educational framing — what multi-tenant clusters must defend against.
Directly reusable by the CAC or by your own future dedicated server.
Grafana + Prometheus + custom exporters — also a Project Backlog item, §15.
ParaView or VisIt on simulation output, with an actual usability evaluation.
Worth pitching jointly with Queen's School of Computing's HCI-adjacent groups.
Business-case framing — strong Commerce/Economics collaboration.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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).
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.
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.
Buildable artifacts rather than studies, at the same accessibility level. Each is a resume line and something to demo at a club fair.
| Project | What you build | Skills gained |
|---|---|---|
| Cluster status webpage | A 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" tutorial | A guided walkthrough that takes a total beginner from login to a completed batch job in 20 minutes | Teaching, technical writing, empathy for beginners |
| Benchmark auto-runner | A shell script that runs the standing suite and dumps results to CSV with hardware metadata attached | Bash, reproducibility discipline |
| Cluster temperature/power logger | Poll 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 card | A one-page printable reference for the commands members actually use | Distillation — harder than it looks, and genuinely wanted |
| Onboarding environment script | One script that sets up a new member's SSH config, keys, aliases, and module defaults | Automation, and it removes a real recurring friction |
| Cluster "hello world" in five languages | The same parallel program in C, Fortran, Python, Julia, and Rust — with build instructions for each | Toolchains, build systems, language comparison |
| Club-fair live demo | A 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 |
A concrete on-ramp, in order. Roughly the first month.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Embarrassingly parallel, financially motivated, and genuinely interesting to a Commerce or Economics student. Study convergence rate vs core count and variance-reduction techniques.
Stencil computation on a 3D grid — the canonical memory-bandwidth-bound HPC workload, and directly relevant to geological engineering.
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.
Compare MPI collective algorithms (ring vs tree vs recursive-doubling allreduce) and measure where each wins as message size and node count vary.
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.
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.
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.
Queen's is a founding partner in the Sudbury Neutrino Observatory Institute. Rare-event searches are classic large-scale data-reduction problems.
NanoFabrication Kingston — process modelling and device simulation as a compute workload.
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.
Queen's operates a Rolling Load Simulator. Pair physical experiment with parallel FEA and compare.
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.
Research topics produce write-ups; these produce artifacts members can point to, demo at club fairs, and put on a resume.
| Project | What it is | Why it matters |
|---|---|---|
| Pi Cluster v2 | Scale past 5 nodes; add a Jetson Nano/Orin for a real heterogeneous CPU+GPU cluster | The physical artifact every peer team has and QHPC's is already the best of the bunch |
| Cluster health dashboard | Grafana + Prometheus + custom exporters on both clusters | Makes the club's infrastructure legible to sponsors and new members alike |
| QHPC Job Portal | A lightweight web frontend for members to submit and monitor jobs | A genuine software project for members who'd rather build web tools than run benchmarks |
| "HPC-in-a-box" teaching kit | A portable rack version of the Pi cluster for outreach and demos | Turns club-fair and high-school outreach into a hands-on demo instead of a poster |
| Automated benchmarking CI | Every code change to the club's benchmark suite auto-runs and posts results | Teaches CI/CD, and keeps §14's benchmark numbers always current |
| Slurm scheduling visualiser | An interactive teaching tool showing jobs queue and schedule in real time | Doubles as a Foundations-cohort teaching aid and a CUCAI-eligible ML-scheduling project |
| Volunteer-computing node | Contribute club compute to a real project — Folding@home or Rosetta@home | Zero-effort, visible community contribution and a genuinely good PR story |
| Open-source contribution sprint | A 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-grant | Small compute allocations on the club cluster, awarded competitively to undergrad researchers campus-wide | A friendlier, faster front door than the CAC's own intake for students who just need a little compute — see §16 |
| Layer | Recommendation | Why |
|---|---|---|
| Compute nodes | 8–10× Raspberry Pi 5 (8GB), up from 5 | Large enough to make network-topology and scaling research (§14, topics 04/10/11) actually show a trend, not just two data points |
| Heterogeneous node | 1× NVIDIA Jetson Orin Nano | The first real GPU node — unlocks the CUDA/GPU-offload research lane (§14 no. 12) and the AI/ML systems section entirely (§14 Section III) |
| Provisioning | Warewulf or xCAT for network boot/imaging, building on the existing PXE/TFTP setup | Reproducible rebuilds — directly fixes the "hardware fails or walks" risk in §32 |
| Scheduler | Slurm, matching Frontenac and every real HPC site | Members transfer skills directly to Frontenac and to SC/ISC scoring environments |
| Monitoring | Prometheus + Grafana + node-exporter | The cluster health dashboard project above, and a live demo asset for club fairs and sponsors |
| Container runtime | Apptainer (formerly Singularity) | The HPC-standard container tool — directly feeds research topic 06 |
One suite, run after every hardware or software change, feeding both competition prep and the Research Branch:
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:
| Term | Mentions across all 72 papers |
|---|---|
| Slurm | 0 |
| Compute Canada / Digital Research Alliance | 0 |
| Google Colab | 4 |
| Kaggle | 13 |
| laptop | 5 |
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.
| Team | What they need compute for | QHPC's offer |
|---|---|---|
| Queen's Hyperloop | Pod 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 controller | GPU training runs; benchmarking their model's inference latency |
| Queen's Relectric | Battery thermal simulation; powertrain modelling | Parallel FEA/thermal simulation capacity |
| aQuatonomous | Path-planning/autonomy training; ASV hull hydrodynamics | Training compute; ties directly to Research topic 25 |
| Queen's Rocket Engineering Team (QRET) | Trajectory simulation; propulsion CFD | Batch simulation runs across parameter sweeps |
| Queen's Racing / Formula-style teams | Vehicle dynamics simulation | Parameter-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).
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.
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:
| Club | Their published work that was compute-bound | QHPC's offer |
|---|---|---|
| QMIND | Superconductivity prediction, portfolio RL, diagnostic imaging | Frontenac GPU nodes for training runs; joint CUCAI submission |
| UTMIST | Multi-agent LLM automation; Unity evolutionary-behaviour platform | Batch parameter sweeps — embarrassingly parallel, ideal for Slurm |
| WAT.ai | 40+ projects, 20+ publications, backed by the Waterloo AI Institute | Overflow capacity; the most sophisticated partner and the best co-author |
| Western AI | Projects portfolio explicitly targets CUCAI presentation | Training compute + a joint "how to actually use a cluster" workshop |
| Western Cyber Society | CNN medical imaging with transfer learning | GPU nodes; closest natural systems collaborator |
| UVic AI | Discord-first, reading-group scale | Cluster 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.
Full-text analysis surfaced the specific researchers who described hitting a compute ceiling. These are warm technical leads, not cold outreach.
| Contact | Their paper | What 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 Saragih | Flow 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 Roy | TinyNav: 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."
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.
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.
| Category | Entity | Why it fits |
|---|---|---|
| Compute | Centre 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 infrastructure | Bell Canada | Signed 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 infrastructure | Queen'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 compute | Digital Research Alliance of Canada | The 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/funding | Dunin-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/AI | Ingenuity Labs Research Institute (Smith Engineering) | Robotics and AI compute needs; possible joint hackathon or project pool. |
| Energy | Queen's Centre for Energy and Power Electronics Research (ePOWER) | Energy-efficient computing crossover; research topic 02 pairs naturally. |
| Water/environment | Beaty Water Research Centre | Hydrological modelling compute; overlaps aQuatonomous's own ecological subteam. |
| Structural/geo | GeoEngineering Centre | Geotechnical and structural simulation compute; ties to research topic 24. |
| Nuclear materials | Reactor Materials Testing Laboratory & the Materials at Extremes and Nuclear (MAX-Nuclear) Research Institute | One 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 / geomechanics | Queen's Geomechanics and Geohazards Group & the Robert M. Buchan Department of Mining Engineering | Their 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. |
| Physics | Sudbury Neutrino Observatory Institute (Queen's is a founding partner) | Particle-astrophysics data processing; a strong "citizen HPC" outreach story. |
| Computing research | Queen's Discrete-Event Systems Lab (QDES) | Directly relevant to Research topic 03 (scheduling policy) — a natural co-supervisor. |
| Computing research | Software Evolution & Analytics Lab (SEAL) | Software performance analytics — pairs with the automated-benchmarking CI project. |
| Computing research | Biomotion Lab | Motion-capture data processing — a visualisation/HCI collaboration lane. |
| Business | Smith School of Business (incl. Master of Management Analytics) | Commerce-student research lane for topics 07, 26, 34; a source of Finance/Marketing/Consulting hires. |
| Health | Kingston 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 club | QMIND | Joint AI-infrastructure workshop; a joint CUCAI submission on topics 15–16; cross-recruiting. |
| Peer club | Queen's Women in Design (QWID) | Brand-new (launched this year) — support their technical programming with an HPC 101 session before every other team does. |
| Hackathon | Any Queen's hackathon running that year | Sponsor a "Best Use of HPC/Compute" track; offer cluster access or cloud credits to hackathon teams. Confirm current organiser before reaching out. |
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.
| Club | School | Scale & structure | What 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.
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.
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 instinct is to spend scarce money scaling the Pi cluster from 5 to 10 nodes. Resist that. Split the roles explicitly instead:
| Pi cluster | Frontenac | |
|---|---|---|
| Cost to expand | Real money you don't have | $0 |
| Best use | Teaching — and hardware students are allowed to break | Every 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.
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.
| Tier | Count | Which |
|---|---|---|
| Start immediately, literally $0 | 10 | Topics 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 | ~9 | Topics 19–27 — the partner supplies the domain question and data, QHPC supplies compute and parallelisation |
| Blocked on money | 3 | Topic 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.
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.
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.
| Stream | Status today | Move this year |
|---|---|---|
| Dean's Donation Fund | Sole source | Apply by mid-November; budget at ~40% of ask |
| Merchandise via Zeffy | Planned, unproven | Pre-order only, one drop per term |
| In-kind hardware | None | Easiest first win — Pi units, switches, storage |
| Cloud/compute credits | None | De-risks the SCC Connect entry directly |
| Corporate cash | None | Publish tiers so there's something to say yes to |
| Consulting engagements (§16) | None | New — in-kind or small-cash from other design teams/departments |
| Departmental support | Informal | Formalise via the partnership list in §17 |
| Tier | What a sponsor gets |
|---|---|
| Gold | Logo on cluster, banner, site header; a dedicated tech talk slot; first access to the resume book |
| Silver | Logo on site and banner; named in recaps; one social post |
| Bronze | Logo on site; named in the annual report |
| In-kind | Recognition mapped to the cash tier its value equals |
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.
| Tier | Threshold | Who'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 & equipment | In-kind | Altium, Keysight Technologies, Ansys, SOLIDWORKS, OpenProject, TOPDON, DDQIC, DigiKey, Mouser Electronics |
| Food & hospitality | In-kind | Insomnia 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:
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.
| Target | The real hook | What to ask for |
|---|---|---|
| AMD — the El Capitan angle | El 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 |
| NVIDIA | Already 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 Program | The 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 Canada | See §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, Supermicro | The 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 Cloud | QMIND'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 |
| Protocase | Kingston-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–Canada | One 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 |
| Deloitte | QMIND'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 Center | All 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, Mouser | All 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&W | All 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 |
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.
| Org | Followers | What worked, pulled from their live LinkedIn page |
|---|---|---|
| QMIND | 2,115 | A Globe and Mail feature reshared with one member's story (Design Team → Deloitte internship) as the hook. |
| Queen's Relectric | 401 | A 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 Hyperloop | 964 | Highest-engagement post was a member's personal post, reposted by the team — distribution runs through people. |
| QADT | 327 | Zero organic LinkedIn posts — all their energy goes to Instagram instead. Don't try to be equally active everywhere. |
| aQuatonomous | 286 | Served as the client for APSC 103 — recruitment disguised as first-year curriculum, the model copied in §16. |
| CUCAI | 1,661 | Ticket posts use real urgency and name headline speakers directly rather than making people click through. |
Tiers and target lists are inputs. This is the actual operating procedure — sequence, timing, scripts, and what to say when they push back.
| When | Who | Ask | Why then |
|---|---|---|---|
| Aug | ECE Department, CAC | Written support letter; team server | Needed for the ISC application in November |
| Early Sept | Campus-proven in-kind donors (Ansys, Altium, Keysight, SOLIDWORKS, DigiKey, Mouser) | Software licences and equipment | Academic-year licences reset in September; they already say yes to Queen's teams |
| Mid Sept | Food sponsors (Insomnia, Chatime, Tahini's, Subway, A&W) | Event catering | Trivial to secure; covers the socials line immediately |
| Late Sept | AWS / Azure / Google Cloud | Academic cloud credits | Applications take weeks; needed before the SC27 SCC Connect entry |
| Oct | Corporate tier-B (NVIDIA, AMD, Bell) | Cash or hardware | Package must exist before the DDF application, which asks for it |
| Early Nov | Dean's Donation Fund | Annual application | Mid-November deadline; attach the sponsorship package |
| Nov | Alumni class funds via Queen's alumni relations | Class gift | Long lead time; Sci '62 and Sci '44 precedent at Hyperloop's top tiers |
| Jan–Feb | Speakers, three weeks post-talk | Something small and specific | Never ask at the event itself |
| Mar | CUCAI co-sponsors (Cohere, Accenture, Rootly, SPUR) | Introduction via CUCAI chairs | You'll be in the room as a Student Club Partner |
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.
| What they say | What it means | Response |
|---|---|---|
| "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 yet | Send 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 internally | Recruiting 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. |
| Silence | Wrong person, or wrong time | After touch 3, stop. Try a different contact at the same organisation next cycle, not the same one again. |
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.
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.
Become a CUCAI Student Club Partner. Send a Sprint team to the Project Showcase.
An HPC workshop day co-branded with the CAC and Queen's Women in Design — one room, one day, ~50 people.
Invite HPC/systems clubs from Toronto, Waterloo, Ottawa, McMaster. Two days, published proceedings.
Only if the org underneath it can carry it — 100+ members, a director layer, an advisor bench, returning sponsors.
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 · Foundation | 2027–28 · Consolidation | 2028–29 · Leadership | |
|---|---|---|---|
| Theme | Get structured, get entered, get published | Compete seriously, fund properly | Convene the field |
| Members | 40+ active, 12+ exec seats filled | 60+, all 20 seats filled | 100+, first-year rep pipeline mature |
| Competition | ISC 2027 virtual + SC27 SCC Connect submitted | Compete in at least one; apply to SC28 main track with a vendor partner | Onsite competition; target a placing |
| Research | 8 topics assigned, 2 publications | 12 topics, 4 publications, first CUCAI showcase entry | Proceedings-quality output; co-authored work with 2+ peer clubs |
| Money | DDF + 2 in-kind lines | DDF + 3–5 sponsors incl. one cash tier | Vendor partnership; alumni class gift; multi-year sponsors |
| Consulting | 1 pilot engagement | 3–4 engagements incl. one department | Standing compute service; the CUCAI network uses QHPC |
| Status | Open the design-team conversation | Design-team status secured | Recognised undergraduate body of the CAC |
| Events | Attend CUCAI as Student Club Partner | Host a one-day HPC workshop at Queen's | Host a regional multi-school event |
| Infrastructure | Frontenac + Pi teaching cluster | Dedicated CAC team server; Pi cluster v2 | Named 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.
"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.
| Stage | Target | Mechanism | Realistic conversion |
|---|---|---|---|
| Aware of QHPC | 600+ | Club fair traffic, ECE + Physics/Math/Computing faculty emails, EngSoc newsletter, first-year course client project | — |
| Signed up (newsletter/Discord) | 150 | QR code at fairs pointing to the newsletter, not Instagram | ~25% of aware |
| Attended ≥1 session | 80 | Kickoff meeting; low-friction first session | ~50% of signups |
| Active (≥3 sessions) | 40 | Foundations cohort structure; buddy pairing with a First-Year Rep | ~50% of attendees |
| Placed in a Sprint by December | 30 | The December placement deadline (Hyperloop's mechanic) | ~75% of active |
| Competition team + alternates | 8 | Selected on Sprint performance in January | ~25% of placed |
| Returns next year | 25+ | The real measure of whether the year worked | ~60% of active |
| Leak | Symptom | Fix |
|---|---|---|
| Signup → first session | Big list, empty room | Personal message before the first session, not a broadcast. Name the person. |
| Session 1 → session 3 | The October collapse | Foundations gives a reason to return on a schedule. Anyone missing two consecutive sessions gets a personal check-in, not an automated reminder. |
| Active → placed | People attend but never commit | The December deadline forces a decision. Ambiguity is what kills commitment. |
| Year 1 → year 2 | Annual reset | Give second-years a title and a real responsibility — a Sprint lead role — before they drift. |
| Non-engineering entry | Only ECE students apply | Post 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.
| Measure | Baseline | Target 2026–27 |
|---|---|---|
| Active members (≥3 sessions) | Not tracked | 40+ |
| Sprints completed | 0 formally tracked | 4 |
| Research topics assigned from §14 | 0 | 8 |
| Competition applications submitted | 0 | 3 (ISC, SCC, SCC Connect) |
| Consulting engagements (§16) | 0 | 2 |
| Income lines beyond the Dean's Fund | 0 | 2 |
| Exec roles filled (of ~20 in §04) | 3 | 12+ |
| Risk | Likelihood | Mitigation |
|---|---|---|
| Dean's Fund award far under ask | High | Budget at 40%; build in-kind and cloud-credit lines by December |
| ISC application window missed | High if unwatched | Named weekly owner from 1 August; draft in October |
| Twenty new roles, nobody applies | Medium | Fill the six "new" seats first; let the rest grow over two years, not one |
| Research Branch becomes busywork | Medium | Every topic tagged with a real output format and, where possible, a real partner |
| Design-team clients never materialise | Medium | Start with one warm pitch (Hyperloop or aQuatonomous) rather than five cold ones |
| Advisor unavailable at deadline | Medium | Ask in September; have a second named authorised grad student |
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.
| Document | What it is | Who uses it |
|---|---|---|
| Strategy | ||
| QHPC 2026–27 Operating Plan this document · 55 sections | Structure, program, finance, sponsorship, governance, risk, execution calendar | President; all execs |
| Compute-Rich, Capital-Poor Strategy | How to run the whole programme on a zero-dollar budget; the research catalogue re-scored by cost; seven decision rules | President; 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 references | Director 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 quotes | Director 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 raise | Any team without a GPU allocation; the fallback plan when the GPU partition is unavailable |
| Research Publication Playbook | How a sprint result becomes a submitted paper: the writing pipeline, venue selection, internal review, and the arXiv-regardless rule | Director 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 backwards | Every member writing a paper; sprint leads reviewing one |
| Money and partnerships | ||
| Sponsorship & Partnership Playbook | Real dollar benchmarks from a peer Queen's team, a six-tier target list sorted by warmth, four outreach templates, the national peer network | Director of Sponsorship; Director of Consulting |
| Sponsorship One-Pager designed; sendable as-is | The document you actually send a prospective sponsor | Director of Sponsorship |
| Competition and research intelligence | ||
| Competition Application Draft | All six SCC sections written out substantively, every placeholder marked, plus a pre-submission checklist | VP Technical; President |
| CUCAI Corpus Deep Analysis | Full-text analysis of all 72 papers: the compute-bound researchers with their own quotes, and the no-code papers as recruitment evidence | Director of Consulting; DEI Officer; People Ops |
| CUCAI 2025 Proceedings Index | All 37 papers categorised with direct PDF links, plus format/length/team-size benchmarks | Director of Research |
| Master Resource Index | CUCAI 2026 slide decks and all 35 papers with links; Hyperloop's publications; corrected URLs; the reusable PDF-download technique | Anyone 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.
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 asks | Open 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.
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.
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.
| Element | Specification |
|---|---|
| Question | Where does an ARM cluster win or lose against x86 at equivalent core count, and why? |
| Software | HPL 2.3, HPCG 3.1, OpenMPI, a tuned BLAS (OpenBLAS on ARM, MKL or BLIS on x86), GCC |
| Data | None — benchmarks generate their own |
| Method | Build 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. |
| Deliverable | Efficiency-vs-NB plot per platform; a table of best configurations; 2,500–4,000 words |
| Failure modes | Choosing 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 matters | HPL and HPCG are scored directly at every SCC. This runbook is simultaneously research output and competition training. |
| Element | Specification |
|---|---|
| Question | How does a real application's parallel efficiency degrade with node count, and where is the bottleneck? |
| Software | Pick one: OpenFOAM (CFD), LAMMPS (molecular dynamics), or GROMACS (biomolecular MD). All open source. |
| Data | Each ships tutorial cases — start there, then scale the mesh or particle count |
| Method | Strong 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. |
| Deliverable | Both scaling curves with Amdahl/Gustafson interpretation; a profile breakdown; 3,000–5,000 words |
| Failure modes | Too-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 matters | This is exactly what the Sprint Model's applications track already asks for, and exactly what SCC judges probe in interviews. |
| Element | Specification |
|---|---|
| Question | How do FIFO, backfill, and fair-share differ in throughput, mean wait time, and fairness under contention? |
| Software | Slurm on the Pi cluster (safe to reconfigure — never experiment on Frontenac), plus a synthetic workload generator |
| Data | Generate a synthetic job mix: vary durations (short/medium/long), widths (1–N nodes), and arrival rate. Optionally model on published HPC workload traces. |
| Method | Fix the workload. Reconfigure SchedulerType and priority weights between runs. Measure makespan, mean/95th-percentile wait, node utilisation, and a fairness metric across users. |
| Deliverable | Comparison table + wait-time distributions; 3,000–4,500 words |
| Failure modes | Workload too homogeneous → backfill shows no benefit (its whole advantage is filling gaps around wide jobs). Not draining the queue between runs → contamination. |
| Partner | Queen's Discrete-Event Systems Lab (QDES) is a natural co-supervisor — scheduling is literally their domain. |
| Element | Specification |
|---|---|
| Question | What real speedup does GPU offload deliver on a chosen kernel, and at what problem size does it become worthwhile? |
| Software | CUDA 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 choice | Start 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. |
| Method | Baseline 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. |
| Deliverable | Speedup-vs-problem-size curve with the crossover marked; roofline if achievable; 3,000–5,000 words |
| Failure modes | Comparing 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 matters | The single most competition-relevant technical skill, and the hardest to fake in a judged interview. |
| Element | Specification |
|---|---|
| Question | How do Canadian undergraduates actually access and learn research computing — and where are the gaps? |
| Software | None. A form tool, a spreadsheet, and Overleaf. |
| Data | Structured 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. |
| Method | Replicate 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. |
| Deliverable | A survey paper with a genuine original finding; 4,000–6,000 words |
| Why it matters | The 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. |
The complete materials list for the Research Branch. Note how little of it costs money.
| Category | Specific tool | Cost | Notes |
|---|---|---|---|
| Writing & publication | |||
| Typesetting | Overleaf + IEEE conference template | Free tier | CUCAI's bound proceedings is LaTeX/hyperref — match their toolchain |
| Citations | Zotero (+ Better BibTeX) | Free | Shared group library so citations accumulate across cohorts |
| Plots | matplotlib / seaborn | Free | Agree one house style so figures look consistent across papers |
| Diagrams | draw.io / Inkscape | Free | The repo already contains .drawio org charts |
| Preprints | arXiv | Free | Endorsement may be needed for some categories — ask the faculty advisor |
| Compute & software | |||
| Primary compute | Frontenac via CAC | Free | See the verified node inventory immediately below |
| Teaching cluster | Pi cluster | Owned | Teaching and demos only — see §17c |
| Simulation | OpenFOAM, LAMMPS, GROMACS | Free | All three ship tutorial cases to start from |
| Benchmarks | HPL, HPCG, STREAM, OSU Micro-Benchmarks | Free | The standing suite; re-run after every change |
| Profiling | perf, gprof, Score-P, TAU, nsys/ncu | Free | nsys/ncu for GPU work |
| Environments | Apptainer; Spack or EasyBuild | Free | Reproducibility — essential for topic 09 |
| Commercial exceptions | Ansys, SOLIDWORKS | Ask in-kind | Both already sponsor Queen's Hyperloop — request, never buy |
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.
| Nodes | Count | CPU | Cores | Memory | GPUs |
|---|---|---|---|---|---|
| GPU nodes — the ones that matter for §14 topics 12, 15–16, 36, 41 | |||||
| frnt190–191 | 2 | NVIDIA DGX A100; EPYC 7742 | 128 | 1 TB | 8× A100 40 GB |
| frnt154 | 1 | EPYC 7H12 @ 2.6 GHz | 128 | 1 TB | 8× A100 40 GB |
| frnt156 | 1 | Xeon Gold 5218 | 32 | 768 GB | 8× RTX8000 48 GB — largest GPU memory on the system |
| frnt155 | 1 | Xeon Gold 5218 | 32 | 768 GB | 8× RTX6000 24 GB |
| frnt140–147 | 8 | EPYC 7443 @ 2.8 GHz | 48 | 512 GB | 2× A30 24 GB |
| frnt148–153 | 6 | Xeon Silver 4210 | 20 | 191 GB | 4× RTX6000 24 GB |
| frnt107 / 110 / 108–109 | 4 | Xeon Gold 6130 | 32 | 192–384 GB | 1× A100 / 1× V100 32 GB / 2× RTX6000 |
| frtn201 | 1 | Xeon 6430 | 64 | 256 GB | 2× L4 |
| Large-memory nodes — relevant to topic 41 (quantum simulation) and any memory-bound work | |||||
| frnt029–030, 032–033 | 4 | Xeon E7-8867 v3 | 128 | 2 TB | — |
| frnt031 | 1 | Xeon E7-8867 v4 | 144 | 1 TB | — highest core count on a single node |
| frnt204 / 205 | 2 | EPYC 7543P / 7742 | 32 / 64 | 1 TB | — |
| General CPU capacity | |||||
| frnt116–139 | 24 | Xeon 6338 @ 2.0 GHz | 64 | 512 GB | — |
| frnt046–078 | 33 | Xeon E5-2650 v4 @ 2.7 GHz | 24–32 | 256 GB | — |
| GPU type | Total on system |
|---|---|
| RTX6000 (24 GB) | 36 |
| A100 (40 GB) | 25 |
| A30 (24 GB) | 16 |
| RTX8000 (48 GB) | 8 |
| L4 | 2 |
| V100 (32 GB) | 1 |
| Total | 88 |
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.
| Item | Value | Consequence |
|---|---|---|
| Login | ssh -X user@login.cac.queensu.ca | Single login node; CentOS |
| Scheduler | Slurm | Everything in the Handbook applies directly |
| Modules | Lmod | module load before any build |
| Partitions | standard, reserved, sse3 (decommissioned) | Target standard unless told otherwise |
| Home | /global/home — 500 GB quota | Not for large I/O |
| Scratch | /global/scratch — 5 TB quota | Where benchmark data goes |
| Project | /global/project | Shared team space |
| Filesystem | GPFS, 3.3 PB parallel | Directly the subject of Handbook T3.3 |
| Node-local scratch | 1.5 TB per node via $TMPDISK | Previously unknown. Changes T3.3 and E7 — gives a fast local tier to benchmark against GPFS |
| Default job limits | 1 CPU, 1024 MB, 3 hours if unspecified | Always set -c, --mem, -t explicitly |
| Contributed nodes | 3-hour hard limit | Long jobs must avoid them |
| AMD EPYC NUMA | Presents as 4 NUMA nodes in Slurm | Directly 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.
| Category | Specific tool | Cost | Notes |
|---|---|---|---|
| Data | |||
| Cardiovascular CFD | Vascular Model Repository | Free | Cited by the CUCAI 2026 CFD paper |
| Predictive maintenance | NASA turbofan degradation data | Free | Used by the CUCAI 2025 ProphetJet paper |
| Materials | Materials Project | Free | Pairs with the superconductivity topic |
| Structural biology | Protein Data Bank | Free | For GROMACS/LAMMPS work |
| Climate | ERA5 reanalysis | Free | Registration required |
| Neuroimaging | OpenNeuro | Free | Open fMRI/EEG |
| Equipment gaps — the only real blockers | |||
| Power measurement | Inline power meter / DAQ | Ask Keysight | Unblocks topic 02; they already sponsor a Queen's team |
| Additional Pi nodes | Pi 5 + PoE HATs + switch | Ask in-kind | Unblocks topics 04 and 18 only |
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.
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.
"Train for the competition" is not a plan. These are the specific skills scored, and how to drill each.
| Scored skill | What good looks like | Drill |
|---|---|---|
| HPL tuning | Systematically finding near-optimal N, NB, P×Q for a given machine, and explaining why | Runbook 1, repeatedly, on different node counts. Keep a tuning log so the reasoning is transferable. |
| HPCG | Understanding why HPCG scores are a small fraction of HPL — memory-bandwidth-bound vs compute-bound | Run both on identical hardware; explain the gap using STREAM results. |
| Application builds under time pressure | Building an unfamiliar scientific code from source, with dependencies, quickly | Timed build drills. Pick a code nobody has built before; two-hour limit. This is the most under-practised competition skill. |
| Power management | Staying under a power cap without wrecking performance | Practise CPU frequency scaling and core-count tradeoffs; measure the performance cost of each. |
| Rapid debugging | Diagnosing a failed job from log output alone | Have a senior member deliberately break a configuration; time the fix. |
| The judged interview | Explaining decisions and tradeoffs clearly, admitting what you don't know | Mock interviews with Ryan Grant and Curtis Shorts. 30–40 minutes, panel format, matching the real thing. |
| Team coordination | Six people not blocking each other across a 48-hour window | The 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.
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 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.
Adopt this formally at the first exec meeting of the year — it's the constitution the objective hierarchy in §08 deserves, made procedural:
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.
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.
| Committee | Draws from | Owns |
|---|---|---|
| Competition Strategy | VP Technical, Director of Research, Competition Captains | Which competitions to enter, the training plan, the mock-comp format |
| Sponsorship & Grants | Director of Sponsorship, Director of Finance, Director of Consulting | The ask calendar, sponsor vetting (§32), grant applications (§38) |
| DEI & Accessibility | DEI Officer, People Ops, Events Coordinator | Outreach, event accessibility, the SCC diversity narrative |
| Risk & Safety | VP Ops & Finance, Director of Cluster Ops, President | The safety plan, sanctioning forms, hardware custody (§31, §39) |
| Alumni & Fundraising | Director of Mentorship, Director of Sponsorship | The 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.
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.
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.
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.
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.
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).
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.
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.
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.
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.
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.
A one-page sponsor-vetting checklist for the Sponsorship Director, with any borderline case escalated to an exec vote rather than a unilateral yes.
Differentiate on the compute-utility positioning in §16 — an infrastructure asset is much harder to replicate overnight than a brand.
The partnership list in §17 doubles as a backup-advisor bench — Physics, Computing, and ePOWER contacts are all plausible substitutes with advance notice.
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.
§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.
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."
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:
| Paper | Words | Method | Why it's the argument |
|---|---|---|---|
| AI consciousness and the evolution of labour ethics: Reframing historical materialism 5 Queen's students, 2025 | 6,343 | Marx'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 | 12,934 | Legal + 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 | 8,177 | Stated 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 | 3,004 | Includes a "Threats to Validity" section | Short, 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.
Three different students should be able to look at this and each see themselves in year three.
Sprints, Research Branch topics, open-source contributions, and consulting engagements are all trackable units of work. Make that visible.
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 item | Conservative (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.
| Source | What 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 Research | Real, standard academic cloud-credit programs — directly de-risks the SCC Connect cloud-resource entry, §09. |
| Microsoft Azure for Students | Same category — worth applying for alongside AWS rather than instead of. |
| NVIDIA Academic Hardware Grant Program | Worth a long-shot application given the direct Ian Karlin connection — even a rejection is a reason to talk to NVIDIA again. |
| Google Cloud research credits | Same category as AWS/Azure; apply to all three rather than picking one. |
| Digital Research Alliance of Canada training | Not 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.
| Day | What goes out | Owner |
|---|---|---|
| Monday | Weekend/prior-week recap, one photo, two lines | Content & Publications |
| Wednesday | Meeting-day reminder and what's on the agenda | Marketing & Brand |
| Friday | A resource, a Research Branch highlight, or a member spotlight | Content & 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.
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.
§08's objective hierarchy is the "why." This is the "by when," broken into the academic year's four natural quarters.
| Quarter | Portfolio | Objective | Key results |
|---|---|---|---|
| Q1 · Sept–Nov | VP Technical | Get the ISC application in strong | All six sections drafted by Wk 8; reviewed by Grant/Shorts; submitted by Wk 11 |
| VP Ops & Finance | Diversify income before the DDF result lands | DDF submitted with sponsorship package attached; 1 in-kind hardware commitment secured | |
| Q2 · Dec–Feb | VP Education | Convert fall interest into placed members | 40+ members placed into a Sprint track by the December deadline |
| VP Communications | Build the owned channel | Newsletter live with 100+ subscribers; site content complete | |
| Q3 · Mar–Apr | VP Technical | Submit and rehearse for competition | SC27 SCC + SCC Connect submitted; 2 graded mock competitions run |
| President | Hand over a stronger org than was inherited | 12+ of 20 exec seats filled; transition manual updated continuously, not in April | |
| Q4 · May–Aug | VP Technical / Research | Compete, and bank the results | ISC virtual round completed; 4+ Research Branch write-ups published for the year |
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.
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.
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.
| 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 |
| 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 |
# 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
artifact/README.md (full command sequence), PROJECT_STATUS.md (status + robustness hardening).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.
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.
| 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 |
| 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 |
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
artifact/README.md (full command sequence), PROJECT_STATUS.md (status + robustness hardening).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.