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The author provides a detailed introduction to using Claude Opus-5.5 for kernel development and AI work, sharing practical experiences with local model workflows, quantization tasks, and hardware selection.
DwarfStar offers fast fused kernels for key model families, open-sourced under the MIT license to enhance AI implementations.
Tweet by @TheAhmadOsman pointing to a resource for learning how AI kernels work.
A detailed blog post dissecting ThunderKittens, a compact DSL for high-performance AI kernels, including a bottom-up analysis of its abstractions and a benchmark implementing a non-causal attention prefill kernel that outperforms FlashAttention-2 by ~1.55x and matches FlashAttention-3.