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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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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Computing with GPUs Introduction, Fundamental Concepts, and Hardware
2. Introducing GPU Computing FREE CHAPTER 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

Entry-level budget

Hardware requirements for beginners can be assumed to be a set of the minimum requirements to get started with the basics of GPU computing. So, in this section, we will explore different entry-level budget options that you can also access on PC Part Picker. So, let's enlist the PC configurations with their approximate prices, according to the following CPU-GPU combinations:

  • Intel CPU and NVIDIA GPU:

CPU

Intel Core i3-8100

$118.89

CPU Cooler

Cooler Master – Hyper 212 EVO

$24.99

Motherboard

Gigabyte H310M A

$55.14

GPU

Asus NVIDIA GeForce GTX 1050Ti 4GB

$201.12

RAM

Corsair Vengeance 2x8GB

$119.99

SSD

ADATA – Ultimate SU800 128 GB

$28.99

HDD

Western Digital – Caviar Green 1 TB

$44.89

Case

Cooler Master – MasterBox Lite 5 ATX Mid Tower

$55.98

PSU

SeaSonic ...

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