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Languages and Compilers for Parallel Computing

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Cover of 'Languages and Compilers for Parallel Computing'

Table of Contents

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    Book Overview
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    Chapter 1 McFLAT: A Profile-Based Framework for MATLAB Loop Analysis and Transformations
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    Chapter 2 Static Analysis of Dynamic Schedules and Its Application to Optimization of Parallel Programs
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    Chapter 3 Lowering STM Overhead with Static Analysis
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    Chapter 4 A Parallel Numerical Solver Using Hierarchically Tiled Arrays
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    Chapter 5 Tackling Cache-Line Stealing Effects Using Run-Time Adaptation
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    Chapter 6 Locality Optimization of Stencil Applications Using Data Dependency Graphs
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    Chapter 7 Array Regrouping on CMP with Non-uniform Cache Sharing
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    Chapter 8 Sublimation: Expanding Data Structures to Enable Data Instance Specific Optimizations
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    Chapter 9 Optimizing and Auto-tuning Belief Propagation on the GPU
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    Chapter 10 A Programming Language Interface to Describe Transformations and Code Generation
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    Chapter 11 Unified Parallel C for GPU Clusters: Language Extensions and Compiler Implementation
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    Chapter 12 How Many Threads to Spawn during Program Multithreading?
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    Chapter 13 Parallelizing Compiler Framework and API for Power Reduction and Software Productivity of Real-Time Heterogeneous Multicores
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    Chapter 14 Debugging Large Scale Applications in a Virtualized Environment
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    Chapter 15 Optimizing the Exploitation of Multicore Processors and GPUs with OpenMP and OpenCL
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    Chapter 16 CnC-CUDA: Declarative Programming for GPUs
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    Chapter 17 Parallel Graph Partitioning on Multicore Architectures
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    Chapter 18 The STAPL pView
Attention for Chapter 11: Unified Parallel C for GPU Clusters: Language Extensions and Compiler Implementation
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