• https://en.wikipedia.org/wiki/Matrix_multiplication

• https://en.wikipedia.org/wiki/Strassen_algorithm

• https://en.wikipedia.org/wiki/Cache-oblivious_algorithm

• https://github.com/flame/how-to-optimize-gemm

• BLISlab: A Sandbox for Optimizing GEMM

• Eigen

• BLAS-level CPU Performance in 100 Lines of C

• https://github.com/HazyResearch/blocking-tutorial

Emulation of FP32 and FP64 matmuls

DGEMM on Integer Matrix Multiplication Unit

Performance Enhancement of the Ozaki Scheme on Integer Matrix Multiplication Unit

Hardware Trends Impacting Floating-Point Computations In Scientific Applications

Recovering single precision accuracy from Tensor Cores while surpassing the FP32 theoretical peak performance

FP8 FP4 Quantization

• [CUDA] Using FP8 and FP4 with Transformer Engine

• Per-Tensor and Per-Block Scaling Strategies for Effective FP8 Training

• DeepSeek-V3 FP8量化浅析

• https://github.com/NVIDIA/cutlass/pull/1932

• https://github.com/NVIDIA/cutlass/pull/2037

• Blockwise FP8 Fused Gated GEMM

• Blockwise FP8 Fused Gated GEMM--v2 优化版

Optimization

• https://github.com/flame/how-to-optimize-gemm/wiki

• QNNPACK: Open source library for optimized mobile deep learning

• Tutorial: OpenCL SGEMM tuning for Kepler

• 通用矩阵乘（GEMM）优化算法

• 斯坦福CS217(三)GEMM计算加速

• https://github.com/AyakaGEMM/Hands-on-GEMM

TVM

• a hgemm tvm schedule
• tir effcient gemm

CUDA

• Cuda矩阵乘法GeMM性能优化

• 一步步优化 GEMM by Tensorcore

• 如何高效实现矩阵乘？万文长字带你从CUDA初学者的角度入门

• [施工中] CUDA GEMM 理论性能分析与 kernel 优化

• Nvidia CUDA Core-CUDA HGEMV Optimization : How to extremely optimize CUDA HGEMV with CUDA Core?

• Nvidia Tensor Core-CUDA HGEMM Advanced Optimization : How to extremely optimize CUDA HGEMM with Tensor Core?

• https://github.com/xgqdut2016/hpc_project/tree/main/cuda/matrix

DeepGEMM

• DeepGEMM: Unlocking the Efficient FP8 GEMM Library

• Optimizing DeepSeek-V3.2 Throughput on NVIDIA H200 GPUs

DeepGEMM V2

• CUDA专场-DeepGEMM 2.0 技术概述 ： 核心特性、整体架构以及在Blackwell 架构上的实现和优化

• https://github.com/deepseek-ai/DeepGEMM/issues/160

Marlin kernel

• Marlin W4A16&W4A8代码走读

Autotuning

• Improving GEMM Kernel Auto-Tuning Efficiency on NVIDIA GPUs with Heuristics and CUTLASS 4.2

BLAS

• https://stackoverflow.com/questions/1303182/how-does-blas-get-such-extreme-performance
• https://www.quora.com/What-algorithm-does-BLAS-use-for-matrix-multiplication-Of-all-the-considerations-e-g-cache-popular-instruction-sets-Big-O-etc-which-one-turned-out-to-be-the-primary-bottleneck
• GEMM: From Pure C to SSE Optimized Micro Kernels
• OpenBLAS矩阵乘法源码结构分析
• OpenBLAS项目与矩阵乘法优化 | AI 研习社

Systolic Array

• Experiment 3: Systolic-Array Implementation of Matrix-By-Matrix Multiplication

• 无废话说AI算子——Basic Matmul及其在NPU中的实现

• 无废话说AI算子——Basic Matmul在NPU中的时间局部性和多播优化