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B200 Attention Kernel from Scratch to Near-SOTA in 60 Diagrams

iaroslavelistratov.github.io · published 28 August 2026

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https://github.com/IaroslavElistratov/b200-attention
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https://github.com/IaroslavElistratov/b200-attention/blob/master/kernels/1_basic/1_baseline.cu
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https://github.com/IaroslavElistratov/b200-attention/blob/master/kernels/5_minor/18_tma_l2_promotion.cu
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https://github.com/IaroslavElistratov/b200-attention/tree/master/capstone-project
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https://github.com/IaroslavElistratov/b200-attention/blob/master/capstone-project/GETTING_STARTED.md
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https://github.com/IaroslavElistratov
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https://github.com/IaroslavElistratov/b200-attention/tree/master/benchmarks
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https://github.com/Dao-AILab/flash-attention/issues/2729
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https://arxiv.org/abs/2603.05451
arxiv.org
https://github.com/Dao-AILab/flash-attention/blob/fa4-v4.0.0.beta4/flash_attn/cute/flash_fwd_sm100.py
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https://github.com/NVIDIA/cutlass/tree/v4.4.1/examples/77_blackwell_fmha
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https://github.com/NVIDIA/cutlass/blob/v4.4.1/examples/python/CuTeDSL/blackwell/fmha.py
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tcgen05 for dummies Read at the source ↗
gau-nernst.github.io
https://www.modular.com/matrix-multiplication-on-blackwell
modular.com
Inside NVIDIA GPUs: Anatomy of high performance matmul kernels Read at the source ↗
aleksagordic.com
https://research.colfax-intl.com/cutlass-tutorial-writing-gemm-kernels-using-tensor-memory-for-nvidia-blackwell
research.colfax-intl.com
https://github.com/IaroslavElistratov/triton-autodiff
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PyTorch internals Read at the source ↗
blog.ezyang.com
https://pytorch-dev-podcast.simplecast.com/episodes
pytorch-dev-podcast.simplecast.com
https://www.thonking.ai/
thonking.ai
https://youtu.be/139UPjoq7Kw
youtu.be
https://introtodeeplearning.com/
introtodeeplearning.com
Elsewhere on iaroslavelistratov.github.io (1)