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2023-03-20 21:38| 来源: 网络整理| 查看: 265

NVIDIA CUDA Installation Guide for Linux

The installation instructions for the CUDA Toolkit on Linux.

1. Introduction

CUDA® is a parallel computing platform and programming model invented by NVIDIA®. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU).

CUDA was developed with several design goals in mind:

Provide a small set of extensions to standard programming languages, like C, that enable a straightforward implementation of parallel algorithms. With CUDA C/C++, programmers can focus on the task of parallelization of the algorithms rather than spending time on their implementation.

Support heterogeneous computation where applications use both the CPU and GPU. Serial portions of applications are run on the CPU, and parallel portions are offloaded to the GPU. As such, CUDA can be incrementally applied to existing applications. The CPU and GPU are treated as separate devices that have their own memory spaces. This configuration also allows simultaneous computation on the CPU and GPU without contention for memory resources.

CUDA-capable GPUs have hundreds of cores that can collectively run thousands of computing threads. These cores have shared resources including a register file and a shared memory. The on-chip shared memory allows parallel tasks running on these cores to share data without sending it over the system memory bus.

This guide will show you how to install and check the correct operation of the CUDA development tools.

1.1. System Requirements

To use NVIDIA CUDA on your system, you will need the following installed:

CUDA-capable GPU

A supported version of Linux with a gcc compiler and toolchain

CUDA Toolkit (available at https://developer.nvidia.com/cuda-downloads)

The CUDA development environment relies on tight integration with the host development environment, including the host compiler and C runtime libraries, and is therefore only supported on distribution versions that have been qualified for this CUDA Toolkit release.

The following table lists the supported Linux distributions. Please review the footnotes associated with the table.

Table 1. Native Linux Distribution Support in CUDA 12.1

Distribution

Kernel1

Default GCC

GLIBC

GCC2,3

ICC3

NVHPC3

XLC3

CLANG

Arm C/C++

x86_64

RHEL 9.1

5.14.0-162

11.3.1

2.34

12.2

2021.7

22.11

NO

15.0

NO

RHEL 8.y (y



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