KernelArc: A Multi-Agent Framework for GPU Kernel Optimization
3.60T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2608.17071.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryKernelArc is a multi-agent framework for autonomous GPU kernel optimization on H100 and B200 GPUs, with strategy-specialized agents coordinating via conclusions-only shared memory, deterministic benchmark guards, and plateau-triggered drafting. On SOL-ExecBench, submissions ranked first on L1, L2, Quantization, and FlashInfer tasks as of July 30, 2026.
Why it mattersConcrete multi-agent coordination design (conclusions-only memory, plateau-triggered drafting) measured against a real leaderboard on a hard optimization task, not just a conceptual proposal.
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