Samples for CUDA Developers which demonstrates features in CUDA Toolkit

cuda cuda-kernels cuda-driver-api cuda-opengl

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README.md

matrixMul_nvrtc - Matrix Multiplication with libNVRTC

Description

This sample implements matrix multiplication and is exactly the same as the second example of the Shared Memory section of the programming guide. It has been written for clarity of exposition to illustrate various CUDA programming principles, not with the goal of providing the most performant generic kernel for matrix multiplication. To illustrate GPU performance for matrix multiply, this sample also shows how to use the CUDA 4.0+ interface for cuBLAS to demonstrate high-performance performance for matrix multiplication.

Key Concepts

CUDA Runtime API, Linear Algebra, Runtime Compilation

Supported SM Architectures

SM 5.0 SM 5.2 SM 5.3 SM 6.0 SM 6.1 SM 7.0 SM 7.2 SM 7.5 SM 8.0 SM 8.6 SM 8.7 SM 8.9 SM 9.0

Supported OSes

Linux, Windows, QNX

Supported CPU Architecture

x86_64, aarch64

CUDA APIs involved

CUDA Driver API

cuMemcpyDtoH, cuLaunchKernel, cuMemcpyHtoD, cuCtxSynchronize, cuMemAlloc, cuMemFree, cuModuleGetFunction

Dependencies needed to build/run

NVRTC

Prerequisites

Download and install the CUDA Toolkit for your corresponding platform. Make sure the dependencies mentioned in Dependencies section above are installed.