Languages and Compilers for Parallel Computing 并行处理用语言与编译器/会议文集

作者简介

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   This book constitutes the thoroughly refereed post-proceedings of the 15th International Workshop on Languages and Compilers for Parallel Processing, LCPC 2002, held in College Park, MD, USA in July 2002.   The 26 revised full papers presented were carefully selected during two rounds of reviewing and improvement from 32 submissions. All current issues in parallel processing are addressed, in particular memory-constrained computation, compiler optimization, performance studies, high-level languages, programming language consistency models, dynamic parallelization, parallelization of data mining algorithms, parallelizing compilers, garbage collection algorithms, and evaluation of iterative compilation.

书籍目录

Memory-Constrained Communication Minimization for a Class of　Array Computations　Forward Communication Only Placements and Their Use for Parallel　Program Construction　Hierarchical Parallelism Control for Multigrain Parallel Processing　Compiler Analysis and Supports for Leakage Power Reduction on　Microprocessor　Automatic Detection of Saturation and Clipping Idioms　Compiler Optimizations with DSP-Specific Semantic Descriptions　Combining Performance Aspects of Irregular Gauss-Seidel Via Sparse　Tiling　A Hybrid Strategy Based on Data Distribution and Migration for　Optimizing Memory Locality　　　Compiler Optimizations Using Data 　Compression to Decrease Address　Reference Entropy　Towards Compiler Optimization of Codes Based on Arrays of Pointers　An Empirical Study on the Granularity of Pointer Analysis in C　Programs　Automatic Implementation of Programming Language Consistency　Models　Parallel Reductions: An Application of Adaptive Algorithm Selection　Adaptively Increasing Performance and Scalability of Automatically　Parallelized Programs　Selector: A Language Construct for Developing Dynamic Applications　Optimizing the Java Piped I/O Stream Library for Performance　A Comparative Study of Stampede Garbage Collection Algorithms　Compiler and Runtime Support for Shared Memory Parallelization of　Data Mining Algorithms　Performance Analysis of Symbolic Analysis Techniques for Parallelizing　Compilers　Efficient Manipulation of Disequalities During Dependence Analysis　Removing Impediments to Loop Fusion Through Code Transformations　Near-Optimal Padding for Removing Conflict Misses……Author Index

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