# Facebookexperimental Triton Kernel Perf Testing

> Kernel Performance Testing

- Skill: `tomevault-io/facebookexperimental-triton-kernel-perf-testing` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/facebookexperimental-triton-kernel-perf-testing`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/facebookexperimental-triton-kernel-perf-testing/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/facebookexperimental-triton-kernel-perf-testing

---


# Kernel Performance Testing

**Never run performance tests unless the user explicitly asks.**

## GPU selection protocol

1. Run `nvidia-smi` to check GPU occupancy.
2. Pick the GPU with the lowest memory usage.
3. Set `CUDA_VISIBLE_DEVICES` to that GPU.

## Benchmark commands

All benchmarks must be wrapped with `denoise.sh` for stable results.

### Hopper GPU

```bash
CUDA_VISIBLE_DEVICES=<gpu_id> third_party/tlx/denoise.sh python third_party/tlx/tutorials/testing/test_hopper_gemm_perf.py [--version {ws|pipelined}]
CUDA_VISIBLE_DEVICES=<gpu_id> third_party/tlx/denoise.sh python third_party/tlx/tutorials/testing/test_hopper_fa_perf.py [--version {ws|ws_pipelined|ws_pipelined_pingpong|ws_pipelined_pingpong_persistent}]
```

### Blackwell GPU

```bash
CUDA_VISIBLE_DEVICES=<gpu_id> third_party/tlx/denoise.sh python third_party/tlx/tutorials/testing/test_blackwell_gemm_perf.py [--version {ws|pipelined|clc|2cta}]
CUDA_VISIBLE_DEVICES=<gpu_id> third_party/tlx/denoise.sh python third_party/tlx/tutorials/testing/test_blackwell_fa_perf.py [--version {ws|ws_pipelined|ws_pipelined_pingpong|ws_pipelined_pingpong_persistent}]
```

### Other kernels

```bash
CUDA_VISIBLE_DEVICES=<gpu_id> third_party/tlx/denoise.sh python third_party/tlx/tutorials/<KERNEL.py>
```

## If tests hang

Run `third_party/tlx/killgpu.sh` to kill GPU processes that have been running too long.

## Interpreting results

- Output reports **TFLOPS** for each problem size and configuration.
- Compare against cuBLAS baselines when available (printed alongside Triton results).
- Higher TFLOPS = better. Look for regressions relative to previous runs.
- Check for consistency across runs — high variance suggests noisy measurements (ensure `denoise.sh` is being used).

---
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<!-- tomevault:4.0:skill_md:2026-04-11 -->