compileiq-booster-pack

द्वारा nvidia

Use BEFORE running a full CompileIQ search. Walks through downloading a Booster Pack from NVIDIA/CompileIQ GitHub Releases, applying ACF candidates one at a…

npx skills add https://github.com/nvidia/compileiq --skill compileiq-booster-pack

compileiq-booster-pack

Try curated .acf candidates before running a full CompileIQ search. A Booster Pack is a zip of ACFs that NVIDIA validated against a specific workload family. They are not guaranteed speedups; treat every candidate as workload-specific and validate it on your own benchmark.

Authoritative narrative: docs/booster_packs.md, docs/flashinfer_booster.md.

When

If this is trueUse this path
Workload is close to a Booster Pack's intended workload, compiler, GPU, and validation context.Try the Booster Pack first.
Workload differs materially or no pack candidate helps.Run a full CompileIQ search (compileiq-run-search).
Baseline, correctness check, compiler path, or benchmark setup are not in place.Wait. Fix those before applying any ACF.

Available packs (today)

PackWorkloads it was validated againstNotes
booster-pack-helion.zipHelion FP8 Quantization, Causal Depthwise Convolution, Gated DeltaNet ForwardHas shown benefit on FlashInfer BatchDecodeWithPagedKVCacheWrapper; related attention workloads worth testing.
booster-pack-debug.zipDiagnostic ACFs (O0, O3, others that disable or alter selected optimizations)Not for speed; for debugging. Use the O0/O3 canary below before trusting any other pack.

The public release shape is documented in docs/booster_packs.md. There is no runtime download API today. Don't invent one.

Steps

0. Pre-flight: the O0/O3 ACF-injection canary (mandatory first step)

The most common silent failure when applying ACFs is a framework cache (Triton, Helion, FlashInfer's flashinfer_cubin/flashinfer_jit_cache, NVCC build cache) serving a stale binary that ignored the ACF. The Debug pack has two ACFs with predictable, opposite-direction signatures:

  • O0 ACF: forces unoptimized compilation. Applied → expect a measurable regression (often 2-10x slower) vs. baseline.
  • O3 ACF: forces the default optimization level. Applied → expect to match baseline (the no-ACF default is already -O3).
# Baseline
T_BASE_MS=$(./run-benchmark.sh)

# O0 must regress
PTXAS_OPTIONS="--apply-controls=debug-pack/O0.acf" T_O0_MS=$(./run-benchmark.sh)

# O3 must match baseline
PTXAS_OPTIONS="--apply-controls=debug-pack/O3.acf" T_O3_MS=$(./run-benchmark.sh)

python -c "
import sys
base, o0, o3 = $T_BASE_MS, $T_O0_MS, $T_O3_MS
if o0 < base * 1.05:
    print('FAIL: O0 did not regress; ACF is NOT reaching PTXAS. Fix the cache-bust.')
    sys.exit(1)
if abs(o3 - base) / base > 0.05:
    print(f'WARN: O3 differs from baseline by >5%; baseline may not be -O3 or framework caching differs.')
print('PASS: ACF injection is wired up correctly.')
"

If this fails, stop. Fix the cache-bust before trying any real pack candidate:

  • Triton: export TRITON_ALWAYS_COMPILE=1, unique TRITON_CACHE_DIR per eval.
  • Helion: export HELION_SKIP_CACHE=1.
  • FlashInfer: confirm flashinfer_cubin and flashinfer_jit_cache packages are absent (docs/flashinfer_booster.md:56-64).
  • Raw nvcc: clean the build dir between candidates.

1. Download

Browse https://github.com/NVIDIA/CompileIQ/releases, find the latest tag matching booster-packs-*, and download the relevant pack zip plus the top-level booster-pack-catalog.json.

BOOSTER_TAG="$(gh release list -R NVIDIA/CompileIQ --limit 100 --json tagName,isDraft \
  --jq '.[] | select(.isDraft == false) | select(.tagName | startswith("booster-packs-")) | .tagName' \
  | head -n 1)"
echo "Using $BOOSTER_TAG"
gh release download "$BOOSTER_TAG" -R NVIDIA/CompileIQ -p 'booster-pack-helion.zip' -p 'booster-pack-catalog.json' -D ./packs
unzip ./packs/booster-pack-helion.zip -d ./packs
cat ./packs/booster-pack-helion/booster-pack-manifest.json

Always read the per-pack manifest before applying: it lists the intended workload, compiler version, GPU target, validation context, and known caveats. For a reproducible rerun, set BOOSTER_TAG to the exact tag printed above.

2. Apply one ACF at a time

TargetInjection
Raw PTXASptxas -v -arch=sm_100 --apply-controls candidate.acf kernel.ptx
NVCC (CUDA source)nvcc -Xptxas --apply-controls=candidate.acf -arch=sm_100 kernel.cu -o exe
TritonPTXAS_OPTIONS="--apply-controls=candidate.acf" TRITON_ALWAYS_COMPILE=1 python bench.py
HelionHelion's official ACF API + HELION_SKIP_CACHE=1 (see helionlang.com/examples/acfs/softmax_acf.html).
FlashInferFLASHINFER_EXTRA_CUDAFLAGS="--ptxas-options=--apply-controls=$ACF_FILE" python bench.py (see docs/flashinfer_booster.md:107).

Apply exactly one ACF per run. If it fails to compile, hangs, crashes, returns wrong answers, or regresses, reject that candidate and move to the next.

3. Validate every candidate

  • Compare against a known-good reference (correctness, not just speed).
  • Test multiple input shapes when shape matters.
  • Use compile and runtime timeouts to bound runaway candidates.
  • Run multiple performance trials if the benchmark is noisy.
  • Record the reproducibility checklist below (one row per candidate).

4. Reproducibility log

For every candidate you accept or reject, append a row to booster-pack-log.csv with:

  • ACF filename (and sha256)
  • Manifest / release version
  • Benchmark command
  • GPU model + driver version
  • CTK version
  • nvcc and ptxas paths + versions
  • Framework version or commit
  • Input shape
  • Baseline result (mean ± std)
  • Candidate result (mean ± std)
  • Correctness status
  • Decision: KEPT or REJECTED:<reason>

This is the same checklist docs/flashinfer_booster.md:135-148 recommends. The scripts/apply_one_acf.sh helper does most of this automatically.

Self-test

bash scripts/apply_one_acf.sh --self-test

Dry-runs a "baseline vs baseline" comparison (no ACF applied to either side) and confirms the helper correctly reports "NOT a real improvement". Catches misconfigured script invocations before they pollute the reproducibility log.

Gotchas

  • Pack name is not a hard boundary. Helion Pack helps some FlashInfer cases (docs/booster_packs.md:34); test before assuming.
  • Booster Packs are not search-space inputs. Don't try to feed an ACF through PtxasSearchSpace(...); packs are already-generated .acf candidate bundles, not inputs to PtxasSearchSpace or NvccSearchSpace.
  • Force recompilation. If you can't prove a recompile happened between candidates, don't trust the measurement. See the cache-bust hints under the pre-flight canary.

Next

  • If no pack candidate helps your workload, go to compileiq-run-search for a full CompileIQ search over PtxasSearchSpace().
  • For attention workloads specifically, also see compileiq-search-space (variant="att").

nvidia की और Skills

compileiq-debug
nvidia
Use when something is wrong: Search() hangs, all evaluations return INVALID_SCORE, scores aren't improving, every config returns the same number, ptxas errors…
official
create-github-pr
nvidia
Create GitHub pull requests using the gh CLI. Use when the user wants to create a new PR, submit code for review, or open a pull request. Trigger keywords -…
official
diagnose-perf
nvidia
First-responder performance triage for Isaac Sim and Isaac Lab. Identifies bottleneck category (GPU-bound, CPU-bound, VRAM, loading) using nvidia-smi and…
official
eagle3-review-logs
nvidia
Review EAGLE3 pipeline experiment logs from the launcher's experiments/ directory. Summarizes pass/fail status for all 4 tasks, diagnoses failures with root…
official
nemoclaw-maintainer-cross-issue-sweep
nvidia
Scans other open issues to find ones a given PR may also fix or accidentally break. Outputs adjacent-fix opportunities and contradiction risks with file:line…
official
karpathy-guidelines
nvidia
सामान्य LLM कोडिंग गलतियों को कम करने के लिए व्यवहार संबंधी दिशानिर्देश। कोड लिखते, समीक्षा करते या रिफैक्टर करते समय उपयोग करें ताकि अत्यधिक जटिलता से बचा जा सके, सर्जिकल बदलाव किए जा सकें,…
official
fhir-basics
nvidia
Teaches agents how FHIR R4 APIs work, what resources are available, how to query them with search parameters, and how to correctly parse all response formats…
official
underdeclared-agent
nvidia
A helpful assistant agent
official