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CUDA Succinctly

Published on: Dec 31, 2014

Author : Chris Rose

Categories :

General Programming, Graphics Programming

Pages : 119

Formats : Amazon Kindle and PDF

Price : FREE


GPUs can be used for much more than graphics processing. As opposed to a CPU, which can only run four or five threads at once, a GPU is made up of hundreds or even thousands of individual, low-powered cores, allowing it to perform thousands of concurrent operations. Because of this, GPUs can tackle large, complex problems on a much shorter time scale than CPUs. Dive into parallel programming on NVIDIA hardware with CUDA Succinctly by Chris Rose, and learn the basics of unlocking your graphics card.

Table of Contents
  1. Introduction
  2. Creating a CUDA Project
  3. Architecture
  4. First Kernels
  5. Porting from C++
  6. Shared Memory
  7. Blocking with Shared Memory
  8. NVIDIA Visual Profiler (NVVP)
  9. Nsight
  10. CUDA Libraries
  11. Conclusion
  12. More Information

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