jhinpan/flydsl-rocprof-cli/flyprof-usage

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Start here to profile a FlyDSL kernel on AMD CDNA (gfx950/MI350X). Router for the flyprof CLI: how to run the fixed capture->analyze->report workflow, read its JSON envelopes, and pick the right sub-skill. Use whenever asked to profile/analyze a kernel, find why a kernel is slow, build an optimization report, or capture an ATT trace for a FlyDSL kernel.

Install

npx vskill@latest install jhinpan/flydsl-rocprof-cli/flyprof-usage

SKILL.md

flyprof — profile any FlyDSL kernel, get an instruction-level optimization report

flyprof is the front half of FlyDSL kernel optimization: given a kernel name it produces a complete, agent-readable diagnosis — every stall bubble, where it lives in the .py, and which FlyDSL thread-level knob addresses it. It does not optimize the kernel; it gives you the evidence to. Drive it the same way every time.

The contract (read this once)

  • Every command prints ONE JSON envelope. Pass -f json (it's the default when

piped). Shape: {"ok": true, "command": ..., "bundle": ..., "data": {...}, "warnings": [...]} or {"ok": false, "command": ..., "error": {"code", "exitCode", "message", "help", ...}}. Read `data`/`error` — never scrape prose.

  • State flows through a bundle directory. The first command makes one (under

runs/<kernel>-<ts> by default, or pass --bundle DIR); every later command takes --bundle DIR and reads the prior artifacts (capture.json, bubbles.json, …).

  • Exit codes are the truth, not the message (sysexits): 0 ok · 66 empty/

no-match (a result, not a bug) · 69 rocprofv3/GPU missing (STOP) · 75 timeout (retry) · 78 bad config/missing build tree · 70 internal. See flyprof-triage.

  • Don't memorize kernel names — query them. flyprof list -f json is the source

of truth and changes as the worktree moves.

The fixed workflow

flyprof list # what can I profile?
flyprof doctor # can this box capture? (verdict: ready)
flyprof run <kernel> --gpu 0 # the whole pipeline, or step through it:
flyprof tile <k> --shape … --dtype … (GPU-free: tile/occupancy/roofline advice)
flyprof capture <k> --tag both --with-pmc (rocprofv3 ATT + PMC -> bundle)
flyprof counters <k> (roofline / occupancy / L2 / bound)
flyprof bubbles --bundle <dir> (stall taxonomy)
flyprof map --bundle <dir> (ISA <-> .py:line)
flyprof report --bundle <dir> (ranked bubble->knob recommendations)
flyprof bundle --bundle <dir> (canonical examples/<k>/ for the hub)

flyprof run is the convenience path; the per-command path is for when you want to inspect or re-run one stage.

Where to go next (intent -> sub-skill)

You want to…Sub-skill
capture an ATT trace / it returned empty or out-of-rangeflyprof-capture
read counters / tile / bubbles / map on a captured bundleflyprof-analyze
produce the optimization report and act on a recommendationflyprof-report
a command failed — what does the error code meanflyprof-triage

Don't guess. Lean on the envelopes. If a number looks wrong, re-run the command that produced it and read its confidence field before making a claim.

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Source

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