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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 CUDA-Lite: Reducing GPU Programming Complexity
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    Chapter 2 MCUDA: An Efficient Implementation of CUDA Kernels for Multi-core CPUs
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    Chapter 3 Automatic Pre-Fetch and Modulo Scheduling Transformations for the Cell BE Architecture
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    Chapter 4 Efficient Set Sharing Using ZBDDs
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    Chapter 5 Register Bank Assignment for Spatially Partitioned Processors
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    Chapter 6 Smashing: Folding Space to Tile through Time
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    Chapter 7 Identification of Heap–Carried Data Dependence Via Explicit Store Heap Models
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    Chapter 8 On the Scalability of an Automatically Parallelized Irregular Application
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    Chapter 9 Statistically Analyzing Execution Variance for Soft Real-Time Applications
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    Chapter 10 Minimum Lock Assignment: A Method for Exploiting Concurrency among Critical Sections
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    Chapter 11 Set-Congruence Dynamic Analysis for Thread-Level Speculation (TLS)
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    Chapter 12 Thread Safety through Partitions and Effect Agreements
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    Chapter 13 P-Ray: A Software Suite for Multi-core Architecture Characterization
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    Chapter 14 Scalable Implementation of Efficient Locality Approximation
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    Chapter 15 P-OPT: Program-Directed Optimal Cache Management
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    Chapter 16 Compiler-Driven Dependence Profiling to Guide Program Parallelization
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    Chapter 17 gluepy: A Simple Distributed Python Programming Framework for Complex Grid Environments
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    Chapter 18 A Fully Parallel LISP2 Compactor with Preservation of the Sliding Properties
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    Chapter 19 A Case Study in Tightly Coupled Multi-paradigm Parallel Programming
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    Chapter 20 ASYNC Loop Constructs for Relaxed Synchronization
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    Chapter 21 Design for Interoperability in stapl: pMatrices and Linear Algebra Algorithms
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    Chapter 22 Implementation of Sensitivity Analysis for Automatic Parallelization
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    Chapter 23 Just-In-Time Locality and Percolation for Optimizing Irregular Applications on a Manycore Architecture
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    Chapter 24 Exploring the Optimization Space of Dense Linear Algebra Kernels
Overall attention for this book and its chapters
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Citations

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5 Mendeley
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Title
Languages and Compilers for Parallel Computing
Published by
Springer Berlin Heidelberg, November 2008
DOI 10.1007/978-3-540-89740-8
ISBNs
978-3-54-089739-2, 978-3-54-089740-8
Editors

Amaral, José Nelson

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 20%
Unknown 4 80%

Demographic breakdown

Readers by professional status Count As %
Lecturer > Senior Lecturer 1 20%
Student > Bachelor 1 20%
Other 1 20%
Researcher 1 20%
Unknown 1 20%
Readers by discipline Count As %
Mathematics 1 20%
Business, Management and Accounting 1 20%
Computer Science 1 20%
Agricultural and Biological Sciences 1 20%
Unknown 1 20%