July 2024
Intermediate to advanced
436 pages
10h 46m
English
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Chapter 8: Multi-GPU programming
Abstract
This chapter covers how to write code that utilizes multiple GPUs. There are many possible configurations between host processes and devices one can use in multi-GPU code. In this chapter, we focus on two configurations: (1) a single host process with multiple GPUs using CUDA's peer-to-peer capabilities and (2) using MPI where each MPI process uses a separate GPU. As examples of these approaches, we implement peer-to-peer and MPI multi-GPU versions of the transpose example used in the previous chapter.
Keywords
Peer-to-peer; UVA (Unified Virtual Addressing); Direct transfer; Direct access; MPI (Message Passing Interface); Compute mode; nvidia-smi (NVIDIA System Management Interface)
There are many configurations ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.