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KernelBench

Frontier coding agents write GPU kernels. Each session is one autonomous agent, graded against a roofline (or ms/speedup) ceiling, then reward-hack audited before anything is published. Live: kernelbench.com.

This monorepo is the website and the evals. GPU sessions launch to Lambda / Brev (or another remote worker). Operator workflow: AGENTS.md. Methodology and history: each bench's SPEC.md and DEVLOG.md.

Benches

bench path what site
hard benchmarks/hard/ per-op kernels (CUDA or Triton), roofline-graded /hard
mega benchmarks/mega/ full fused megakernels /mega
cuda benchmarks/cuda/ CUDA-only writing deck (Triton/DSL fail) /cuda
mini benchmarks/mini/ small-model (<200B) deck, capped + 5-repeat (WIP) unpublished
multi benchmarks/multi/ 4×H100 NVLink multi-GPU (WIP, frontier roster) unpublished
v3 benchmarks/v3/ offline archive (separate harness) not on site

Hard / mega / cuda share harness machinery and run unlimited wall-clock (BUDGET_SECONDS=0). Mini is capped; multi is sequential on a 4-GPU node.

Website (local)

Next.js 16 + Tailwind. Package manager is bun (bun.lock):

bun install
bun dev          # http://localhost:3000
bun run build

Site data is baked at build time from benchmarks/*/results/ (app/_lib/data.ts). Publish/deploy: kb publish then kb deploy — see AGENTS.md.

Docs map

  • AGENTS.md — sweeps, harnesses, Lambda/Brev, publish, audits
  • benchmarks/<bench>/SPEC.md — methodology
  • benchmarks/<bench>/DEVLOG.md — design history
  • benchmarks/<bench>/README.md — short human entry for that deck

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kernelbench.com — GPU kernel engineering benchmarks for autonomous LLM coding agents. v3 archive + v-hard latest.

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