Table of Contents:
“...Front Cover -- Multicore and GPU
Programming: An Integrated Approach -- Copyright -- Dedication -- Contents -- List of Tables -- Preface -- What Is in This Book -- Using This Book as a Textbook -- Software and Hardware Requirements -- Sample Code -- Chapter 1: Introduction -- 1.1 The era of multicore machines -- 1.2 A taxonomy of parallel machines -- 1.3 A glimpse of contemporary
computing machines -- 1.3.1 The cell BE processor -- 1.3.2 Nvidia's Kepler -- 1.3.3 AMD's APUs -- 1.3.4 Multicore to many-core: tilera's TILE-Gx8072 and intel's xeon phi -- 1.4 Performance metrics -- 1.5 Predicting and measuring parallel
program performance -- 1.5.1 Amdahl's law -- 1.5.2 Gustafson-barsis's rebuttal -- Exercises -- Chapter 2: Multicore and parallel
program design -- 2.1 Introduction -- 2.2 The PCAM methodology -- 2.3 Decomposition patterns -- 2.3.1 Task parallelism -- 2.3.2 Divide-and-conquer decomposition -- 2.3.3 Geometric decomposition -- 2.3.4 Recursive
data decomposition -- 2.3.5 Pipeline decomposition -- 2.3.6 Event-
based coordination decomposition -- 2.4
Program structure patterns -- 2.4.1 Single-
program, multiple-
data -- 2.4.2 Multiple-
program, multiple-
data -- 2.4.3 Master-worker -- 2.4.4 Map-reduce -- 2.4.5 Fork/join -- 2.4.6 Loop parallelism -- 2.5 Matching decomposition patterns with
program structure patterns -- Exercises -- Chapter 3: Shared-memory
programming: threads -- 3.1 Introduction -- 3.2 Threads -- 3.2.1 What is a thread? ...
”
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