TLDR Tech / Dev
Auto-research with Codex: How I achieved a 232x Faster Kernel over baseline with Codex in GPU Mode's qr_v2 problem
In a recent auto-research contest focusing on GPU optimizations, an impressive 232x speedup over the baseline was achieved in implementing the batched square compact-Householder QR factorization problem, with the author finishing 12th out of 183 participants. The project involved using techniques like the blocked Householder algorithm, continual kernel profiling, and iteration on ideas presented through advanced AI models.
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