Languages and Compilers for Parallel Computing
Editat de Bill Pugh, Chau-Wen Tsengen Limba Engleză Paperback – 13 dec 2005
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Specificații
ISBN-13: 9783540307815
ISBN-10: 3540307818
Pagini: 396
Ilustrații: XII, 380 p.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.6 kg
Ediția:2005
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540307818
Pagini: 396
Ilustrații: XII, 380 p.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.6 kg
Ediția:2005
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
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 Microprocessors.- 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.- Fine-Grain Stacked Register Allocation for the Itanium Architecture.- Evaluating Iterative Compilation.