4 tagged aiinfra, measured the same way as everything else here.
Skill Claude CodeCodex
Corpus-backed GPU kernel knowledge base for CUDA, Triton, CuTe, CUTLASS, and Ampere/Hopper/Blackwell kernel research. Use when the user needs to search merged kernel PR pages, inspect PR diff/provenance artifacts, find KernelWiki synthesis pages, query blog/doc/contest notes, or retrieve evidence-backed implementation…
Skill Claude CodeCodex
Standalone kernel benchmarking skill for cuda-cpp, cutlass, cute-dsl, and triton implementations. Use when the user wants to compare a custom CUDA/CUTLASS .cu kernel or CuTe DSL/Triton .py kernel against selectable PyTorch eager, torch.compile, or FlashInfer baselines, validate correctness, measure execution time with…
Skill Claude CodeCodex
Iterative GPU kernel optimization orchestrator for CUDA/CUTLASS/CuTe DSL/Triton kernels. Use for measured, one-change-at-a-time optimization loops with correctness, NCU profiling, KBS evidence, hypothesis discipline, hard iteration gates, final benchmarking, and a traceable report.