Tuned OpenCL BLAS

The HPC toolbox: fused matrix multiplication, convolution, data-parallel strided tensor primitives, OpenMP facilities, SIMD, JIT Assembler, CPU detection, state-of-the-art vectorized BLAS for floats and integers

BLISlab: A Sandbox for Optimizing GEMM

Stretching GPU performance for GEMMs and tensor contractions.

Single file libraries for C/C++

DBCSR: Distributed Block Compressed Sparse Row matrix library

Code for testing the native float16 matrix multiplication performance on Tesla P100 and V100 GPU based on cublasHgemm

PyTorch bindings for openai-gemm

code for benchmarking GPU performance based on cublasSgemm and cublasHgemm

The repository targets the OpenCL gemm function performance optimization. It compares several libraries clBLAS, clBLAST, MIOpenGemm, Intel MKL(CPU) and cuBLAS(CUDA) on different matrix sizes/vendor's hardwares/OS. Out-of-the-box easy as MSVC, MinGW, Linux(CentOS) x86_64 binary provided. 在不同矩阵大小/硬件/操作系统下比较几个BLAS库的sgemm函数性能，提供binary，开盒即用。

GEMM

fast 2D convolution implementation benchmark

Low Precision Arithmetic for Convolutional Neural Network Inference

Serial and parallel implementations of matrix multiplication

gemm baseline code.

Specialized Parallel Linear Algebra, providing distributed GEMM functionality for specific matrix distributions with optional GPU acceleration.

Yet another rust BLAS

My experiments on optimizing GEMM

High Performance Computing - Algorithms and Applications Course in WS18-19 at TUM

PROJECT: GEMM Optimization

CUDA version GEMM

Low-precision matrix multiplication

My experiments with convolution