Distributed Communication-Optimal Matrix-Matrix Multiplication Algorithm

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

Floating-point matrix multiplication implementation (arbitrary precision)

Matrix multiplication on the NPU inside RK3588

Generate optimized MatMul cuda kernel automatically using tvm auto schedule.

ForMatmul - A Fortran library that overloads the matmul function to enable efficient matrix multiplication with/without coarray.

This project integrates a custom CUDA-based matrix multiplication kernel into a PyTorch deep learning model, leveraging GPU acceleration for matrix operations. The goal is to compare the performance of this custom kernel with PyTorch's built-in matrix multiplication and demonstrate how custom CUDA kernels can optimize compute-intensive operations.

Raspberry Pi Pico (RP2040) and Adafruit Metro M7 (NXP IMXRT10XX) benchmark

In this project, ınstruction numbers from a c program are counted with pin and c++.

OpenMP Matrix Multiplication Offloading Playground

The provided code is a Python script that uses the CuPy library to perform optimized GPU operations, specifically matrix multiplication. The script includes a custom CUDA kernel that is optimized for performance and energy consumption. The kernel uses half-precision floating-point numbers (float16) for improved performance and warp utilization.

📰 This repository contains time measurements of various algorithms on the CPU and GPU using PyCuda: matrix multiplication, Pi computation, and bilateral filtering.

This is the simple script that generate matrixes of size 4 by 4, for testing Matmul.

This repo contains the python scripts for MatMul's all modules testing.

Rust Basic Matrix Multiplication

CPU, GPU, and FPGA matrix multiplication examples via SYCL

Matrix-matrix multiplication implementations benchmarking

cuBLAS GEMM Example for FP32 MatMul

Check out the power of NumPy