NumPy & SciPy for GPU

Python interface to GPU-powered libraries

Safe rust wrapper around CUDA toolkit

Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.

Hooked CUDA-related dynamic libraries by using automated code generation tools.

Deep Learning library using GPU(CUDA/cuBLAS)

🔥🔥🔥 A collection of some awesome public NVIDIA CUDA, cuBLAS, cuDNN, TensorRT, AMD ROCm and FPGA projects.

Parallel Computing Library for Linux and macOS & NVIDIA CUDA Wrapper

Algorithms implemented in CUDA + resources about GPGPU

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

code for benchmarking GPU performance based on cublasSgemm and cublasHgemm

Bandicoot: C++ library for GPU linear algebra & scientific computing - https://coot.sourceforge.io

Matrix multiplication on GPUs for matrices stored on a CPU. Similar to cublasXt, but ported to both NVIDIA and AMD GPUs.

Examples showing how to utilize the NVML library for GPU monitoring

Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.

Real-time GPU Beamformer for DSA110 written in C/CUDA

Escoin: Efficient Sparse Convolutional Neural Network Inference on GPUs

bilibili视频【CUDA 12.1 并行编程入门(C++语言版)】配套代码

Tools to run and parse MKL verbose mode

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。