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tcgen05 for dummies

gau-nernst.github.io · published 21 December 2025

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6blogs citing
First cited
2 Feb 2026
Most recent
11 Sept 2026
Rank this month
not ranked
Links from this post
27
Words captured
17,699

Cited by

Blog
In the post
Date
osmarks.net
Fixing Graphcore Read at the source ↗
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B200 Attention Kernel from Scratch to Near-SOTA in 60 Diagrams Read at the source ↗
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cudaforfun.substack.com
Outperforming cuBLAS on NVFP4 Read at the source ↗
15 Aug 2026
hamzaelshafie.bearblog.dev
Dissecting ThunderKittens: Anatomy of a Compact DSL for High-Performance AI Kernels Read at the source ↗
21 May 2026
simons blog
SBO and LBO explained visually Read at the source ↗
18 Apr 2026
danielvegamyhre.github.io
MXFP8 GEMM: Up to 99% of cuBLAS performance using CUDA + PTX Read at the source ↗
29 Mar 2026
danielvegamyhre.github.io
Debugging deadlocks in warp-specialized GEMM kernels with CUDA-GDB Read at the source ↗
2 Feb 2026

Links from this post

Link
Host
Outperforming cuBLAS on H100: a Worklog Read at the source ↗
cudaforfun.substack.com
https://modal.com/
modal.com
https://github.com/gau-nernst/learn-cuda/tree/3b90ac9b/02e_matmul_sm100/
github.com
https://docs.nvidia.com/cuda/cuda-driver-api/group__CUDA__TENSOR__MEMORY.html
docs.nvidia.com
My first Multi-GPU kernel: Writing All-to-all for AMD MI300X Read at the source ↗
gau-nernst.github.io
https://davekilian.com/acquire-release.html
davekilian.com
https://github.com/pranjalssh/fast.cu/blob/38eb642e0c081231d6f695978be63604bd7c689b/examples/matmul/matmul_2.cuh
github.com
Modular: Matrix Multiplication on Blackwell: Part 2 - Using Hardware Features to Optimize Matmul Read at the source ↗
modular.com
CUTLASS Tutorial: Fast Matrix-Multiplication with WGMMA on NVIDIA® Hopper™ GPUs Read at the source ↗
research.colfax-intl.com
https://github.com/gau-nernst/learn-cuda/blob/3b90ac9b/02e_matmul_sm100/matmul_v1.cu
github.com
https://github.com/deepseek-ai/DeepGEMM/blob/9b680f42/deep_gemm/include/deep_gemm/impls/sm100_bf16_gemm.cuh
github.com
https://gau-nernst.github.io/bank-conflict/
gau-nernst.github.io
https://github.com/gau-nernst/learn-cuda/blob/3b90ac9b/02e_matmul_sm100/matmul_v2.cu
github.com
https://github.com/nod-ai/amd-shark-ai/blob/v3.9.0/docs/amdgpu_kernel_optimization_guide.md
github.com
https://github.com/gau-nernst/learn-cuda/blob/3b90ac9b/02e_matmul_sm100/matmul_v3.cu
github.com
https://github.com/gau-nernst/learn-cuda/blob/3b90ac9b/02e_matmul_sm100/matmul_v4.cu
github.com
Modular: Matrix Multiplication on Blackwell: Part 3 - The Optimizations Behind 85% of SOTA Performance Read at the source ↗
modular.com
CUTLASS Tutorial: GEMM with Thread Block Clusters on NVIDIA® Blackwell GPUs Read at the source ↗
research.colfax-intl.com
https://github.com/gau-nernst/learn-cuda/blob/3b90ac9b/02e_matmul_sm100/matmul_v5.cu
github.com
https://github.com/gau-nernst/learn-cuda/blob/3b90ac9b/02e_matmul_sm100/profiler.h
github.com
https://github.com/gau-nernst/learn-cuda/blob/3b90ac9b/02e_matmul_sm100/main.py
github.com
https://github.com/gau-nernst/learn-cuda/raw/3b90ac9b/02e_matmul_sm100/trace_v5.json.gz
github.com
https://github.com/gau-nernst/learn-cuda/blob/3b90ac9b/02e_matmul_sm100/matmul_v6.cu
github.com
https://github.com/gau-nernst/learn-cuda/raw/3b90ac9b/02e_matmul_sm100/trace_v6.json.gz
github.com
https://github.com/deepseek-ai/DeepGEMM
github.com
https://www.modular.com/matrix-multiplication-on-blackwell
modular.com
https://ui.perfetto.dev/
ui.perfetto.dev