Accelerated Computing With HIP

Second Edition

Yifan Sun, Sabila Al Jannat, Trinayan Baruah

$118.95 $100.91

Paperback

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English

Sun, Al Jannat, Baruah, Kaeli
31 January 2025

Technology: general issues; Computing: general

This book is designed for programmers who wish to use GPUs to improve application performance, and it is suitable for both AMD and NVIDIA GPU programmers, as HIP is a portable language that runs on both platforms. ROCm is open sourced, allowing other GPU developers to support this platform. This book does not require knowledge of CUDA programming, however, we highlight how HIP differs from CUDA while explaining how to port those programs to HIP, promoting interoperability such that a single application can be executed on different underlying hardware. For non-CUDA programmers, our book starts with the basics by presenting how HIP is a full-featured parallel programming language. Then, we provide coding examples that cover a wide range of relevant programming paradigms.

By: Yifan Sun, Sabila Al Jannat, Trinayan Baruah
Imprint: Sun, Al Jannat, Baruah, Kaeli
Edition: Large type / large print edition
Dimensions: Height: 235mm, Width: 191mm, Spine: 21mm
Weight: 694g
ISBN: 9798218576578
Pages: 300
Publication Date: 31 January 2025
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active

Yifan Sun is an Assistant Professor in the Department of Computer Science at William & Mary, where he leads the Scalable Architecture Lab. He received his Ph.D. degree from the Department of Electrical and Computer Engineering at Northeastern University in 2020. His research interests lie in GPU architecture, performance evaluation, and performance modeling. Sabila Al Jannat is pursuing her Ph.D. in Computer Science at William and Mary. Her advisor is Prof. Yifan Sun. Prior to joining William and Mary, she completed her BS degree in Computer Science and Engineering at BRAC University in Bangladesh. Trinayan Baruah is Senior Member of the Technical Staff at AMD. He received his MS and Ph.D. degrees from the Department of Electrical and Computer Engineering at Northeastern University in 2020. His research interests include GPU microarchitecture, simulation, compilers and memory systems.