Skip to Content
Hands-On GPU Programming with Python and CUDA
book

Hands-On GPU Programming with Python and CUDA

by Dr. Brian Tuomanen
November 2018
Intermediate to advanced
310 pages
7h 54m
English
Packt Publishing
Content preview from Hands-On GPU Programming with Python and CUDA

Chapter 6, Debugging and Profiling Your CUDA Code

  1. Memory allocations are automatically synchronized in CUDA.
  2. The lockstep property only holds in single blocks of size 32 or less. Here, the two blocks would properly diverge without any lockstep.
  3. The same thing would happen here. This 64-thread block would actually be split into two 32-thread warps.
  4. Nvprof can time individual kernel launches, GPU utilization, and stream usage; any host-side profiler would only see CUDA host functions being launched.
  5. Printf is generally easier to use for small-scale projects with relatively short, inline kernels. If you write a very involved CUDA kernel with thousands of lines, then probably you would want to use the IDE to step through and debug your kernel ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.

Read now

Unlock full access

More than 5,000 organizations count on O’Reilly

AirBnbBlueOriginElectronic ArtsHomeDepotNasdaqRakutenTata Consultancy Services

QuotationMarkO’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.
Head of Cybersecurity
QuotationMarkI 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.
Field Engineer
QuotationMarkI’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.
Data Platform Tech Lead
QuotationMarkI'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.
Mark W.
Embedded Software Engineer

You might also like

CUDA by Example: An Introduction to General-Purpose GPU Programming

CUDA by Example: An Introduction to General-Purpose GPU Programming

Jason Sanders, Edward Kandrot
Algorithms: 24-part Lecture Series

Algorithms: 24-part Lecture Series

Robert Sedgewick, Kevin Wayne
Programming Massively Parallel Processors, 4th Edition

Programming Massively Parallel Processors, 4th Edition

Wen-mei W. Hwu, David B. Kirk, Izzat El Hajj

Publisher Resources

ISBN: 9781788993913