8458

CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs

Shane Cook
CUDA Developer
Elsevier Science, Applications of GPU Computing Series, 2012
@book{cook2012cuda,

   title={CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs},

   author={Cook, S.},

   isbn={9780124159334},

   series={Applications of GPU Computing Series},

   url={http://books.google.com.ua/books?id=g3EzsZn4poUC},

   year={2012},

   publisher={Elsevier Science}

}

Download Download (PDF)   View View   Source Source   

3382

views

If you need to learn CUDA but don’t have experience with parallel computing, CUDA Programming: A Developer’s Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems.
VN:F [1.9.22_1171]
Rating: 3.2/5 (12 votes cast)
CUDA Programming: A Developer's Guide to Parallel Computing with GPUs, 3.2 out of 5 based on 12 ratings

* * *

* * *

Like us on Facebook

HGPU group

184 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1311 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: