gpumm - matrix-matrix multiplication by using CUDA, cublas, cublasxt and OpenACC.

SwiftCUBLAS is a wrapper for cuBLAS APIs with extra utilities for ease of usage, along with a suite of tests. The repository is tested on the newest (v12.5) CUDA runtime API on both Linux and Windows.

A general k-means algorithm with L2 distance using pyCUDA

matrix operation using gpu

GPU linear algebra functions callable from Python

cuBLAS GEMM Example for FP32 MatMul

NMF calculations are performed on NVIDIA GPUs using the Cuda API. (GEM released)

cuBLAS for pycu_interface.

Framework, toolkit and ready-to-use applications for numerical linear algebra dependent machine learning algorithms.

bilibili视频【CUDA 12.x 并行编程入门(Rust版)】配套代码

Newton's and Halley's Method for the Matrix Polar Decomposition using CUDA

NumPy-like API accelerated with CUDA

A CUDA approach for computing the multiplication of a transposed matrix with the initial one, using the cuBLAS library.

High-performance GPU-accelerated linear algebra library for scientific computing. Custom kernels outperform cuBLAS+cuSPARSE by 2.4x in iterative solvers. Built for circuit simulation workloads.

A CUBLAS‐CUDA Based Implementation of Multi-GPU Large Matrix Multiplication

Level 3 matrix multiplication using both cublas and mkl.

Dynamic bindings to the CuBLAS library for the D Programming Language.