KernelArc: A Multi-Agent Framework for GPU Kernel Optimization
How a collaborative multi-agent system is setting new performance records for GPU kernel acceleration.
We present KernelArc, a multi-agent framework for autonomous GPU kernel optimization across heterogeneous workloads. Strategy-specialized agents run in parallel and coordinate through conclusions-only shared memory, a deterministic benchmark guard, and read-only cross-agent state...
ArXiv CS.AI
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KernelArc demonstrates that multi-agent systems can significantly outperform traditional manual or single-agent approaches in the complex domain of GPU hardware optimization. By parallelizing specialized search strategies, this framework achieves record-breaking performance on cutting-edge hardware architectures like the NVIDIA H100 and B200.
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