| --- |
| license: mit |
| tags: |
| - synthetic |
| - rl |
| - multi-agent |
| - cuda |
| - triton |
| - inference |
| - kernel-optimization |
| --- |
| |
| # kernelswarm — multi-agent kernel-optimization episodes (RL) |
|
|
| Synthetic dataset of **multi-agent long-horizon optimization campaigns** on |
| AI-inference kernels. Each row is one whole episode: a lead orchestrator plus |
| 2–20 specialist agents split the work, exchange dispatches/statuses/handoffs, |
| submit full kernel candidates, and receive simulated compile/verify/bench |
| feedback — with a reward attached to every environment result. |
|
|
| **Inference-focused only.** All ops are inference primitives (decode/prefill |
| attention, quantized GEMM/GEMV, sampling, norms, KV-cache, MoE, Mamba). |
|
|
| > ⚠️ All benchmarks, compiles and correctness checks are **simulated |
| > analytically** — no kernel was ever compiled or executed on a real GPU. |
|
|
| ## Row format (one row = one episode) |
|
|
| ```json |
| { |
| "episode_id": "flash_decode_h100_B=8,..._dispatch_74", |
| "scenario": "dispatch", // dispatch | parallel_sweep | pipeline | campaign |
| "n_agents": 6, |
| "op": "flash_decode", "impl": "cuda", |
| "gpu": "h100", "arch": "sm_90a", "dtype": "fp16", |
| "shape": {...}, "baseline_ms": 0.42, "best_ms": 0.006, |
| "speedup": 66.4, "elapsed_s": 17335, |
| "agents": [{"id": "a01", "role": "worker", "skill": 0.9, |
| "tries": 8, "kept": 5, "best_ms": 0.008}, ...], |
| "num_messages": 74, |
| "messages": [ ... ] |
| } |
| ``` |
|
|
| ## Message kinds |
|
|
| | kind | role | meaning | |
| |-------------|-----------------|------------------------------------------------| |
| | `plan` | lead | campaign split strategy | |
| | `dispatch` | lead | subtask assignment (`to`, `subtask`) | |
| | `candidate` | agent | **full kernel source** + `params` | |
| | `result` | env | compile/verify/bench outcome + `reward` | |
| | `status` | agent | terse progress report | |
| | `review` | reviewer | pass/fail verdict | |
| | `verify` | verifier | correctness check report | |
| | `leaderboard` | env | ranked agent best-times | |
| | `merge` | lead | pick winner, update shared best | |
| | `redirect` | lead | re-assign agent to winner's variant/region | |
| | `handoff` | agent | pass artifact to another agent | |
| | `verdict` | lead | final outcome + terminal reward | |
|
|
| ## Rewards |
|
|
| - `result` msgs: `min(1, log2(prev_best / new))` on kept improvement; |
| `-0.05` no-improvement, `-0.1` compile error, `-0.3` wrong result, |
| `-0.05` unsupported arch. |
| - `verdict` msg: `log2(speedup) / 4` terminal bonus. |
|
|
| ## Scenarios |
|
|
| - **dispatch** — lead splits variants across workers, merges, redirects losers (2–8 agents) |
| - **parallel_sweep** — N workers each own a cfg slice of one variant; leaderboard + top-2 refine (4–20) |
| - **pipeline** — proposer → reviewer → verifier → tuner chain over variants (3–6) |
| - **campaign** — fleet dispatch over variant×cfg space + verifier rebench (5–20) |
| |
| ## Coverage |
| |
| - 17 ops (14 CUDA + 3 Triton impls): flash_decode, swa_decode, gemm_fp16, |
| int8_gemm, fp8_gemm, int4_gemv, rmsnorm, rope, swiglu_act, topk_sample, |
| nucleus_sample, mamba_scan, moe_scatter, kv_append, fused_qkv_rope, |
| triton_flash_decode, triton_rmsnorm |
| - GPUs: h100, h200, a100, a10, rtx_a6000, rtx_5090 (arch features gated: |
| wgmma/tma/fp8/fp4/cp.async) |
| - 2400 episodes · ~170k messages · avg 71 msgs/episode · avg 8.6 agents |
| - Simulated horizon: 1–5 h per episode |
| |
| ## Files |
| |
| - `batches/batch_*.jsonl` — 24 shards × 100 episodes |
| - `episodes.jsonl` — all episodes concatenated |
| - `tasks_holdout.jsonl` — (op, gpu, shape) task specs for eval |
| - `stats.json` — aggregate stats |
| |
