Languages and compilers for parallel computing : 21st international workshop, LCPC 2008, Edmonton, Canada, July 31-August 2, 2008 : revised selected papers

書誌事項

Languages and compilers for parallel computing : 21st international workshop, LCPC 2008, Edmonton, Canada, July 31-August 2, 2008 : revised selected papers

José Nelson Amaral (ed.)

(Lecture notes in computer science, 5335 . LNCS sublibrary ; SL 1 . Theoretical computer science and general issues)

Springer, c2008

タイトル別名

Languages and compilers for parallel computing : 21th international workshop, LCPC 2008, Edmonton, Canada, July 31-August 2, 2008 : revised selected papers

大学図書館所蔵 件 / 3

この図書・雑誌をさがす

注記

Some copies' title on t.p.: Languages and compilers for parallel computing : 21th international workshop, LCPC 2008, Edmonton, Canada, July 31-August 2, 2008 : revised selected papers

Includes bibliographical references and author index

内容説明・目次

内容説明

In 2008 the Workshop on Languages and Compilers for Parallel Computing left the USA to celebrate its 21st anninversary in Edmonton, Alberta, Canada. Following its long-established tradition, the workshop focused on topics at the frontierofresearchanddevelopmentinlanguages,optimizingcompilers,appli- tions, and programming models for high-performance computing. While LCPC continues to focus on parallel computing, the 2008 edition included the pres- tation of papers on program analysis that are precursors of high performance in parallel environments. LCPC 2008 received 35 paper submissions. Eachpaper received at least three independent reviews, and then the papers and the referee comments were d- cussed during a Program Committee meeting. The PC decided to accept 18 papers as regular papers and 6 papers as short papers. The short papers appear at the end of this volume. The LCPC 2008 program was fortunate to include two keynote talks. Keshav Pingali's talk titled "Amorphous Data Parallelism in Irregular Programs" - gued that irregular programs have data parallelism in the iterative processing of worklists. Pingali described the Galois system developed at The University of Texas at Austin to exploit this kind of amorphous data parallelism. The second keynote talk, "Generic ParallelAlgorithms in Threading Building Bocks (TBB)," presented by Arch Robison from Intel Corporation addressed very practical aspects of using TBB, a production C++ library, for generic p- allel programming and contrasted TBB with the Standard Template Library (STL).

目次

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

「Nielsen BookData」 より

関連文献: 1件中  1-1を表示

詳細情報

ページトップへ