KernelBench operators

Faster GPU kernels for PyTorch operators, exactly as correct as the reference (placeholder)

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State the benchmark (placeholder)

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	1	+# KernelBench operators
	2	+
	3	+> Placeholder. This benchmark is here so the benchmark panel can be tried out. Its baseline is from the blueprint or the literature as of 2026-10-19 and must be checked again; every route and score after it is made up.
	4	+
	5	+## Task
	6	+
	7	+Write GPU kernels that compute what twelve PyTorch operators and modules from Stanford’s KernelBench compute, faster. A kernel counts only if it matches the PyTorch reference on random inputs. The score is the geometric mean speed-up over PyTorch eager on the pinned runner, so the baseline is exactly 1. Triton, CUDA and anything else that compiles on the runner is fine.
	8	+
	9	+## How to take part
	10	+
	11	+Start a route from `main` (the baseline) or from any route on the leaderboard, keep your files in the route's folder, and push: the verifier scores every commit. Say what your route changes with tags, and keep the misses: a route that scores worse is a result too.