HPC-230 · HPC & Large Systems · Advanced
HPC Performance Analysis — full syllabus
Profiling applications that span many nodes, where the bottleneck is rarely where you expect.
Who this course is for
Performance engineers and HPC support staff who must find out why a multi-node application is slow — and prove it — when the bottleneck is rarely where anyone expected.
Prerequisites
- Experience running MPI or hybrid applications
- Basic statistics (means, distributions, variance)
- HPC-101 strongly recommended
Course outline
Day 1 — Scaling methodology and measurement integrity
- Strong vs weak scaling; efficiency metrics
- Amdahl and Gustafson as diagnostic tools
- Experimental integrity: warm-up, repetitions, frequency pinning
- Coordinated omission and other benchmark lies
- Designing a scaling experiment you would stake a decision on
Day 2 — Profiling multi-node codes
- Profiling vs tracing; instrumentation overhead
- mpiP, Score-P and TAU on real codes
- Timelines: reading communication/computation overlap
- Load imbalance quantification across ranks
- I/O profiling with Darshan; the storage bottleneck
Day 3 — Diagnosis and the performance report
- Bottleneck taxonomy: compute, memory, network, I/O, imbalance
- Hypothesis-driven investigation: one change, one measurement
- Roofline context for the compute ceiling
- Separating correlation from causation in profiles
- Building a performance report that drives a buy/optimise decision
Hands-on labs
- Lab: run strong and weak scaling sweeps; compute efficiency and locate the knee where scaling breaks
- Lab: expose measurement noise (frequency scaling, warm-up, cache state) and redo the experiment properly
- Lab: profile an MPI code with mpiP or Score-P and produce a communication/computation breakdown
- Lab: quantify load imbalance across ranks and trace it back to the decomposition
- Lab: profile application I/O with Darshan and determine whether storage or compute actually limits the job
Capstone project
Conduct a complete performance investigation of a supplied multi-node application: preregistered experiment plan, scaling curves with error bars, profiling and I/O evidence, a ranked bottleneck list with a fix-and-verify loop, and a two-page report answering the only question management asks — buy more nodes, rewrite the decomposition, or fix the I/O?
What you leave with
- A repeatable strong/weak scaling methodology with honest measurement
- Profiling fluency across mpiP, Score-P and Darshan
- Communication/computation/imbalance breakdowns you can produce on demand
- Experimental-integrity habits that survive peer review
- A performance-report template that turns evidence into decisions
Upcoming dates
| Dates | Where | Seats | Early bird | Regular | |
|---|---|---|---|---|---|
| 25 Oct – 27 Oct 20263 full days | RiyadhIn person · KAFD Conference Centre | 6 of 14 | — | SAR 9,000 | |
| 1 Nov – 3 Nov 20263 full days | Kuwait CityIn person · Al Hamra Tower | 11 of 14 | — | KWD 740 | |
| 8 Nov – 10 Nov 20263 full days | MuscatIn person · Knowledge Oasis Muscat | 6 of 14 | OMR 830until 9 Oct | ||
| 8 Nov – 15 Nov 20266 half-days | Gulf bandLive online · 09:00–13:00 GMT+3 | 16 of 20 | US$1,580until 9 Oct | ||
| 9 Nov – 11 Nov 20263 full days | OttawaIn person · Kanata North Tech Park | 11 of 14 | CAD 2,930until 10 Oct | ||
| 16 Nov – 18 Nov 20263 full days | TorontoIn person · MaRS Discovery District | 6 of 14 | CAD 2,930until 17 Oct | ||
| 16 Nov – 23 Nov 20266 half-days | Europe bandLive online · 09:00–13:00 CET | 5 of 20 | US$1,580until 17 Oct | ||
| 23 Nov – 25 Nov 20263 full days | LondonIn person · Shoreditch Works | 11 of 14 | GBP 1,680until 24 Oct | ||
| 23 Nov – 25 Nov 20263 full days | BerlinIn person · Factory Görlitzer Park | 6 of 14 | EUR 1,990until 24 Oct | ||
| 23 Nov – 30 Nov 20266 half-days | Americas bandLive online · 13:00–17:00 ET | 10 of 20 | US$1,580until 24 Oct |
Book a seat, or bring this course to your team
Seats can be reserved online; private delivery runs on-site or live online, adapted to your stack.
Questions about fit or prerequisites? Email hello@kernelsystems.academy. To save this syllabus, print this page to PDF from your browser.