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Description
As the computer industry retools to leverage massively parallel graphics processing units (GPUs), this book is designed to meet the needs of working software developers who need to understand GPU programming with CUDA and increase efficiency in their projects. CUDA Application Design and Development starts with an introduction to parallel computing concepts for readers with no previous parallel experience, and focuses on issues of immediate importance to working software developers: achieving high performance, maintaining competitiveness, analyzing CUDA benefits versus costs, and determining application lifespan.
The book then details the thought behind CUDA and teaches how to create, analyze, and debug CUDA applications. Throughout, the focus is on software engineering issues: how to use CUDA in the context of existing application code, with existing compilers, languages, software tools, and industry-standard API libraries.
Using an approach refined in a series of well-received articles at Dr Dobb's Journal, author Rob Farber takes the reader step-by-step from fundamentals to implementation, moving from language theory to practical coding.
Key Features
- Includes multiple examples building from simple to more complex applications in four key areas: machine learning, visualization, vision recognition, and mobile computing
- Addresses the foundational issues for CUDA development: multi-threaded programming and the different memory hierarchy
- Includes teaching chapters designed to give a full understanding of CUDA tools, techniques and structure.
- Presents CUDA techniques in the context of the hardware they are implemented on as well as other styles of programming that will help readers bridge into the new material
Readership
Software engineers, programmers, hardware engineers, advanced students
Table of Contents
CHAPTER 1 First Programs and How to Think in CUDA
Source Code and Wiki
Distinguishing CUDA from Conventional Programming with a Simple Example
Choosing a CUDA API
Some Basic CUDA Concepts
Understanding Our First Runtime Kernel
Three Rules of GPGPU Programming
Big-O Considerations and Data Transfers
CUDA and Amdahl’s Law
Data and Task Parallelism
Hybrid Execution: Using Both CPU and GPU Resources
Regression Testing and Accuracy
Silent Errors
Introduction to Debugging
UNIX Debugging
Windows Debugging with Parallel Nsight
Summary
CHAPTER 2 CUDA for Machine Learning and Optimization
Modeling and Simulation
Machine Learning and Neural Networks
XOR: An Important Nonlinear Machine-Learning Problem
Performance Results on XOR
Performance Discussion
Summary
The C++ Nelder-Mead Template
CHAPTER 3 The CUDA Tool Suite: Profiling a PCA/NLPCA
Functor
PCA and NLPCA
Obtaining Basic Profile Information
Gprof: A Common UNIX Profiler
The NVIDIA Visual Profiler: Computeprof
Parallel Nsight for Microsoft Visual Studio
Tuning and Analysis Utilities (TAU)
Summary
CHAPTER 4 The CUDA Execution Model
GPU Architecture Overview
Warp Scheduling and TLP
ILP: Higher Performance at Lower Occupancy
Little’s Law
CUDA Tools to Identify Limiting Factors
Summary
CHAPTER 5 CUDA Memory
The CUDA Memory Hierarchy
GPU Memory
L2 Cache
L1 Cache
CUDA Memory Types
Global Memory
Summary
CHAPTER 6 Efficiently Using GPU Memory
Reduction
Utilizing Irregular Data Structures
Sparse Matrices and the CUSP Library
Graph Algorithms
SoA, AoS, and Other Stru
Details
- No. of pages:
- 336
- Language:
- English
- Copyright:
- © 2012
- Published:
- 31st October 2011
- Imprint:
- Morgan Kaufmann
- eBook ISBN:
- 9780123884329
- Print ISBN:
- 9780123884268
About the author
Rob Farber
Rob Farber has served as a scientist in Europe at the Irish Center for High-End Computing as well as U.S. national labs in Los Alamos, Berkeley, and the Pacific Northwest. He has also been on the external faculty at the Santa Fe Institute, consultant to fortune 100 companies, and co-founder of two computational startups that achieved liquidity events. He is the author of “CUDA Application Design and Development” as well as numerous articles and tutorials that have appeared in Dr. Dobb's Journal and Scientific Computing, The Code Project and others.
Affiliations and Expertise
CEO/Publisher of TechEnablement.com, Wall Street Analyst, and consultant to scientific and commercial technology companies around the world.
Reviews
The book by Rob Faber on CUDA Application Design and Development is required reading for anyone who wants to understand and efficiently program CUDA for scientific and visual programming. It provides a hands-on exposure to the details in a readable and easy to understand form. Jack Dongarra, Innovative Computing Laboratory, EECS Department, University of Tennessee
GPUs have the potential to take computational simulations to new levels of scale and detail. Many scientists are already realising these benefits, tackling larger and more complex problems that are not feasible on conventional CPU-based systems. This book provides the tools and techniques for anyone wishing to join these pioneers, in an accessible though thorough text that a budding CUDA programmer would do well to keep close to hand. Dr. George Beckett, EPCC, University of Edinburgh
With his book, Farber takes us on a journey to the exciting world of programming multi-core processor machines with CUDA. Farber's pragmatic approach is effective in guiding the reader across challenges and their solutions. Farber's broader presentation of parallel programming with CUDA ranging from CUDA in Cloud and Cluster environments to CUDA for real problems and applications helps the reader learning about the unique opportunities this parallel programming language can offer to the scientific community. This book is definitely a must for students, teachers, and developers! Michela Taufer, Assistant Professor, Department of Computer and Information Sciences, University of Delaware
Rob Farber has written an enlightening and accessible book on the application to CUDA for real research tasks, with an eye to developing scalable and distributed GPU applications. He supplies clear and usable code examples combined with insight about _why_ one should use a particular approach. This is an excellent book filled with practical advice for experienc