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

Algorithms implemented in CUDA + resources about GPGPU

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

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

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

Harness the power of GPU acceleration for fusing visual odometry and IMU data with an advanced Unscented Kalman Filter (UKF) implementation. Developed in C++ and utilizing CUDA, cuBLAS, and cuSOLVER, this system offers unparalleled real-time performance in state and covariance estimation for robotics and autonomous system applications.

Use tensor core to calculate back-to-back HGEMM (half-precision general matrix multiplication) with MMA PTX instruction.

Lab exercise of Parallel Processing course in NTUA regarding CUDA programming

Library for profiling the execution time of CUDA official library functions

Simple VGG16 implemented in CUDA

Matrix Exponential Approximation using CUDA

CUDA kernel functions

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

Generalized Orthogonal Least-Squares in CUDA

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

Nonnegative matrix factorizations using CUDA

A MNIST handwritten digit classifier written from scratch in Cuda - C

GPGPU Inverse Distance Weighting using matrix vector multiplication

A library to extract DCT hashes with CUDA