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Hands-On GPU Computing with Python

You're reading from   Hands-On GPU Computing with Python Explore the capabilities of GPUs for solving high performance computational problems

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789341072
Length 452 pages
Edition 1st Edition
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Author (1):
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Avimanyu Bandyopadhyay Avimanyu Bandyopadhyay
Author Profile Icon Avimanyu Bandyopadhyay
Avimanyu Bandyopadhyay
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Computing with GPUs Introduction, Fundamental Concepts, and Hardware FREE CHAPTER
2. Introducing GPU Computing 3. Designing a GPU Computing Strategy 4. Setting Up a GPU Computing Platform with NVIDIA and AMD 5. Section 2: Hands-On Development with GPU Programming
6. Fundamentals of GPU Programming 7. Setting Up Your Environment for GPU Programming 8. Working with CUDA and PyCUDA 9. Working with ROCm and PyOpenCL 10. Working with Anaconda, CuPy, and Numba for GPUs 11. Section 3: Containerization and Machine Learning with GPU-Powered Python
12. Containerization on GPU-Enabled Platforms 13. Accelerated Machine Learning on GPUs 14. GPU Acceleration for Scientific Applications Using DeepChem 15. Other Books You May Enjoy Appendix A

High-end budget

High-end configurations are undoubtedly the preference of advanced and expert users who are already experienced in the field. So, in this final section, we will look into the best options in hardware, considering the best performance. Feel free to tweak or modify the respective configurations, the links to which have been provided for each:

  • Intel CPU and NVIDIA GPU:

CPU

Intel – Core i7-9700K

$193.99

CPU Cooler

Corsair – H60 (2018) 57.2 CFM

$69.98

Motherboard

Asus – ROG STRIX Z390-E ATX LGA1151

$238.89

GPU

Gigabyte NVIDIA GeForce GTX 1080 Ti 11 GB

$754.98

RAM

Corsair Vengeance LPX 2x16GB

$200.00

SSD

ADATA – Ultimate SU800 256 GB

$44.99

HDD

Western Digital – Caviar Green 2 TB

$89.89

Case

Cooler Master – MasterBox Lite 5 ATX Mid Tower

$55.98

PSU

SeaSonic...

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