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arXiv AI By Joyjit Kundu, Ben Stoffelen, Kaili Wang, Peter Vrancx, Ludovic Denoyer

KernelArc: A Multi-Agent Framework for GPU Kernel Optimization

Read the original on arXiv AI →

KernelArc is a multi-agent framework designed to autonomously optimize GPU kernels across diverse workloads. It employs strategy-specialized agents that run concurrently, coordinating via conclusions-only shared memory, a deterministic benchmark guard, and read-only cross-agent state with plateau-triggered drafting. Evaluated on NVIDIA H100 and B200 GPUs with SOL-ExecBench workloads, KernelArc produced top-ranked implementations for tasks such as BF16 GEMM, cuBLASLt configuration tables, and various attention mechanisms, achieving first place on several leaderboard categories.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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