Originally developed to support video games, Graphics Processor units (GPUs) are now increasingly used for General-Purpose (non-graphics) applications ranging from machine learning to mining of cryptographic currencies.
This book should provide a valuable resource for those wishing to understand the architecture of Graphics Processor units (GPUs) used for acceleration of General-Purpose applications and to those who want to obtain an introduction to the rapidly growing body of research exploring how to improve the architecture of these GPUs..
Chapter 5 summarizes cross-cutting research impacting both the compute core and memory system.
After describing the architecture of existing systems, Chapters refch03 and refch04 provide an overview of related research.
Chapter 4 explores the architecture of the GPU memory system.
Chapter 3 explores the architecture of GPU compute cores.
Chapter 2 provides a summary of GPU programming models relevant to the rest of the book.
The first chapter of this book describes the basic hardware structure of GPUs and provides a brief overview of their history.
The authors led development of the GPGPU-Sim simulator widely used in academic research on GPU architectures.
It collects together information currently only found among a wide range of disparate sources.
This book provides an introduction to those interested in studying the architecture of GPUs that support General-Purpose computing.
In addition, their General-Purpose programmability makes contemporary GPUs appealing to software developers in comparison to domain-specific accelerators.
GPUs can achieve improved performance and efficiency versus central processing units (CPUs) by dedicating a larger fraction of hardware resources to computation.
Originally developed to support video games, Graphics Processor units (GPUs) are now increasingly used for General-Purpose (non-graphics) applications ranging from machine learning to mining of cryptographic currencies
