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Hands-On GPU Programming with Python and CUDA

You're reading from Hands-On GPU Programming with Python and CUDA

Product type Book

Published in Nov 2018

Publisher Packt

ISBN-13 9781788993913

Pages 310 pages

Edition 1st Edition

Languages

Concepts

Graphics Programming

Author (1):

Dr. Brian Tuomanen

Table of Contents (15) Chapters

Preface

1. Why GPU Programming?

2. Setting Up Your GPU Programming Environment

3. Getting Started with PyCUDA

4. Kernels, Threads, Blocks, and Grids

5. Streams, Events, Contexts, and Concurrency

6. Debugging and Profiling Your CUDA Code

7. Using the CUDA Libraries with Scikit-CUDA

8. The CUDA Device Function Libraries and Thrust

9. Implementation of a Deep Neural Network

10. Working with Compiled GPU Code

11. Performance Optimization in CUDA

12. Where to Go from Here

13. Assessment

14. Other Books You May Enjoy

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Using the Nsight IDE for CUDA-C development and debugging

Let's now learn how to use the Nsight IDE for developing CUDA-C programs. We will see how to import the program we just wrote, and compile and debug it from within Nsight. Note that there are differences between the Windows and Linux versions of Nsight, since it is effectively a plugin of the Visual Studio IDE under Windows and in the Eclipse IDE under Linux. We will cover both in the following two subsections; feel free to skip whatever operating system does not apply to you here.

Using Nsight with Visual Studio in Windows

Open up Visual Studio, and click on File, then choose New | Project.... A window will pop up where you set the type of project: choose the...

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Authors (1)

Dr. Brian Tuomanen

Dr. Brian Tuomanen has been working with CUDA and General-Purpose GPU Programming since 2014. He received his Bachelor of Science in Electrical Engineering from the University of Washington in Seattle, and briefly worked as a Software Engineer before switching to Mathematics for Graduate School. He completed his Ph.D. in Mathematics at the University of Missouri in Columbia, where he first encountered GPU programming as a means for studying scientific problems. Dr. Tuomanen has spoken at the US Army Research Lab about General Purpose GPU programming, and has recently lead GPU integration and development at a Maryland based start-up company. He currently lives and works in the Seattle area.

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