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RESOLVE: Language-Agnostic Validation of GPU Kernels Through Testing, Reduction, and Proof

Gargary, Ashkan Vedadi et al.
arXiv (All) · Papers
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and-cluster-computingdistributedmachine-learningparallelprogramming-languages
AI systems can now write and optimize production GPU kernels, but validating them remains an important challenge. Evaluating the kernel on a few random inputs and checking that its outputs match a trusted reference kernel within numeric tolerances is not sufficient: races can cause nondeterministic
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