Items related to Hands-On GPU Programming with Python and CUDA
Synopsis
Build GPU-accelerated high performing applications with Python 2.7, CUDA 9, and open source libraries such as PyCUDA and scikit-cuda. We recommend the use of Python 2.7 as this version has stable support across all libraries used in this book.
Key Features
- Get to grips with GPU programming tools such as PyCUDA, scikit-cuda, and Nsight
- Explore CUDA libraries such as cuBLAS, cuFFT, and cuSolver
- Apply GPU programming to modern data science applications
Book Description
GPU programming...
About the Author
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...
"About this title" may belong to another edition of this title.
- PublisherPackt Publishing
- Publication date2018
- ISBN 10 1788993918
- ISBN 13 9781788993913
- BindingPaperback
- LanguageEnglish
- Number of pages310
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