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检索条件"任意字段=21st International Workshop on Languages and Compilers for Parallel Computing, LCPC 2008"

共 11 条记录，以下是1-10 订阅

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languages and compilers for parallel computing - 21st international workshop, lcpc 2008, Revised Selected Papers

Languages and Compilers for Parallel Computing - 21st Intern...

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21st international workshop on languages and compilers for parallel computing, lcpc 2008

ISBN: (纸本)3540897399

The proceedings contain 24 papers. The topics discussed include: CUDA-lite: reducing GPU programming complexity;MCUDA: an efficient implementation of CUDA kernels for multi-core CPUs;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 partition and effect agreements;a fully parallel LISP2 compactor with preservation of the sliding properties;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;and exploring the optimization space of dense linear algebra kernels.

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languages and compilers for parallel computing 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： José Nelson Amaral

ISBN: (数字)9783540897408

ISBN: (纸本)9783540897392

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).

关键词： Programming languages, compilers, Interpreters Programming Techniques Computer Communication Networks Data structures Artificial Intelligence Models and Principles

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languages and compilers for parallel computing 2008

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丛书名： Lecture Notes in Computer Science

2008年

作者： José Nelson Amaral

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Exploring the Optimization Space of Dense Linear Algebra Kernels

Exploring the Optimization Space of Dense Linear Algebra Ker...

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21st international workshop on languages and compilers for parallel computing

作者： Yi, Qing Qasem, Apan Univ Texas San Antonio San Antonio TX 78249 USA Texas State Univ Tyler TX USA

ISBN: (纸本)9783540897392

Dense linear algebra kernels such as matrix multiplication have been used as benchmarks to evaluate the effectiveness of many automated compiler optimizations. However, few studies have looked at collectively applying the transformations and parameterizing them for external search. In this paper, we take a detailed look at the optimization space of three dense linear algebra kernels. We rise a transformation scripting language (POET) to implement each kernel-level optimization as applied by ATLAS. We then extensively parameterize these optimizations from tire perspective of a, general-purpose compiler and rise a stand-alone empirical search engine to explore the optimization space using several different search strategies. Our exploration of the search space reveals key interaction among several transformations that must be considered by compilers to approach the level of efficiency obtained through manual timing of kernels.

关键词： Program compilers

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Register Bank Assignment for Spatially Partitioned Processors

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21st international workshop on languages and compilers for parallel computing

作者： Robatmili, Behnam Coons, Katherine Burger, Doug McKinley, Kathryn S. Univ Texas Austin Dept Comp Sci Austin TX 78712 USA

ISBN: (纸本)9783540897392

Demand for instruction level parallelism calls for increasing register bandwidth without increasing the number of register ports. Emerging architectures address this need by partitioning registers into multiple distributed banks, which offers a technology scalable substrate but a challenging compilation target. This paper introduces a register allocator for spatially partitioned architectures. The allocator performs bank assignment together with allocation. It minimizes spill code and optimizes bank selection based on a priority function. This algorithm is unique because it must reason about multiple competing resource constraints and dependencies exposed by these architect tires. We demonstrate an algorithm that uses critical path estimation, delays front registers to consuming functional units, and hardware resource constraints. We evaluate the algorithm on TRIPS, a functional, partitioned, tiled processor with register banks distributed on top of a 4 x 4 grid of ALUs. These results show that the priority banking algorithm implements a number of policies that improve performance, performance is sensitive to bank assignment, and the compiler manages this resource well.

关键词： Program compilers

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Compiler-Driven Dependence Profiling to Guide Program parallelization

Compiler-Driven Dependence Profiling to Guide Program Parall...

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21st international workshop on languages and compilers for parallel computing

作者： Wu, Peng Kejariwal, Arun Cascaval, Calin IBM Corp Programming Models & Tools Scalable Syst TJ Watson Res Ctr Yorktown Hts NY 10598 USA Univ Calif Irvine Ctr Embedded Comp Syst Irvine CA 92697 USA

ISBN: (纸本)9783540897392

As hardware systems move toward multicore and multi-threaded architectures, programmers increasingly rely on automated tools to help with both the parallelization of legacy codes and effective exploitation of all available hardware resources. Thread-level speculation (TLS) has been proposed as a technique to parallelize the execution of serial codes or serial sections of parallel codes. One of the key aspects of TLS is task selection for Speculative execution. In this paper we propose a cost model for compiler-driven task selection for TLS. The model employs profile-based analysis of may-dependences to estimate the probability of successful speculation. We discuss two techniques to eliminate potential inter-task dependences, thereby improving the rate Of Successful speculation. We also present a profiling tool, DProf, that is used to provide run-time information about may-dependences to the compiler and map dynamic dependences to the source code. This information is also made available to the programmer to assist in code rewriting aud/or algorithm redesign. We used DProf to quantify the potential of this approach and we present results on selected applications from the SPEC CPU2006 and SEQUOIA benchmarks.

关键词： Program compilers

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MCUDA: An Efficient Implementation of CUDA Kernels for Multi-core CPUs

MCUDA: An Efficient Implementation of CUDA Kernels for Multi...

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21st international workshop on languages and compilers for parallel computing

作者： stratton, John A. stone, Sam S. Hwu, Wen-mei W. Univ Illinois Ctr Reliable & High Performance Comp Urbana IL 61801 USA Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA

ISBN: (纸本)9783540897392

CUDA is a data parallel programming model that supports several key abstractions - thread blocks, hierarchical memory and barrier synchronization - for writing applications. This model has proven effective in programming GPUs. In this paper we describe a framework called MCUDA, which allows CUDA programs to be executed efficiently or) shared memory, multi-core CPUs. Our framework consists of a set of source-level compiler transformations and a runtime system for parallel execution. Preserving program semantics, the compiler transforms threaded SPMD functions into explicit loops, performs fission to eliminate barrier synchronizations, and converts scalar references to thread-local data to replicated vector references. We describe an implementation of this framework and demonstrate performance approaching that achievable from manually parallelized and optimized C code. With these results, we argue that CUDA can be an effective data-parallel programming model for more than just CPU architectures.

关键词： parallel programming

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An effective automated approach to specialization of code

An effective automated approach to specialization of code

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20th international workshop on languages and compilers for parallel computing

作者： Khan, Minhaj Ahmad Charles, H. -P. Barthou, D. Univ Versailles St Quentin Yvelines Versailles France

ISBN: (纸本)9783540852605

Application performance is heavily dependent on the compiler optimizations. Modern compilers rely largely on the information made available to them at the time of compilation. In this regard, specializing the code according to input values is an effective way to communicate necessary information to the compiler. However, the static specialization suffers from possible code explosion and dynamic specialization requires runtime compilation activities that may degrade the overall performance of the application. This article proposes an automated approach for specializing code that is able to address both the problems of code size increase and the overhead of runtime activities. We first obtain optimized code through specialization performed at static compile time and then generate a template that can work for a large set of values through runtime specialization. Our experiments show significant improvement for different SPEC benchmarks on Itanium-II(IA-64) and Pentium-IV processors using ice and gcc compilers.

关键词： Program compilers

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A Case study in Tightly Coupled Multi-paradigm parallel Programming

A Case Study in Tightly Coupled Multi-paradigm Parallel Prog...

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21st international workshop on languages and compilers for parallel computing

作者： Chakravorty, Sayantan Becker, Aaron Wilmarth, Terry Kale, Laxmikant Univ Illinois Dept Comp Sci 1304 W Springfield Ave Urbana IL 61801 USA Univ Illinois Ctr Simulat adv Rocket 1304 W Springfield Ave Urbana IL 61801 USA

ISBN: (纸本)9783540897392

Programming paradigms are designed to express algorithms elegantly and efficiently. There are many parallel programming paradigms, each suited to a certain class of problems. Selecting the best parallel programming paradigm for a. problem minimizes programming effort and maximizes performance. Given the increasing complexity of parallel applications, no one paradigm may be suitable for all components of an application. Today, most parallel scientific applications are programmed with a single paradigm and the challenge of multi-paradigm parallel programming remains unmet in the broader community. We believe that each component, of a parallel program should be programmed using the most suitable paradigm. Furthermore, it is not sufficient to simply bolt modules together: programmers should be able to switch between paradigms easily, and resource management across paradigms should be automatic. We present a pre-existing adaptive run-time system (ARTS) and show how it can be used to meet these challenges by allowing the simultaneous use of multiple parallel programming paradigms and supporting resource management across all of them. We discuss the implementation of some common paradigms within the ARTS and demonstrate the use of multiple paradigms within our feature-rich unstructured mesh framework. We show how this approach boosts performance and productivity for an application developed using this framework.

关键词： parallel programming

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On the Scalability of an Automatically parallelized Irregular Application

On the Scalability of an Automatically Parallelized Irregula...

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21st international workshop on languages and compilers for parallel computing

作者： Burtscher, Martin Kulkarni, Milind Prountzos, Dimitrios Pingali, Keshav Univ Texas Austin Ctr Grid & Distributed Comp Inst Computat Engn & Sci Austin TX 78712 USA

ISBN: (纸本)9783540897392

Irregular applications, i.e., programs that manipulate pointer-based data structures such as graphs and trees, constitute a challenging target for parallelization because the amount of parallelism is input dependent and changes dynamically. Traditional dependence analysis techniques are too conservative to expose this parallelism. Even manual parallelization is difficult, time consuming, and error prone. The Galois system parallelizes such applications using an optimistic approach that exploits higher-level semantics of abstract data types. In this paper, we study the performance and scalability of a Galoised, that is, automatically parallelized, version of Delaunay mesh refinement (DR) on a shared-memory system with 128 CPUs. DR is an important irregular application that is used, e.g., in graphics and finite-element codes. The parallelized program scales to 64 threads, where it reaches a speedup of 25.8. For large numbers of threads, the performance is hampered by the load imbalance and the nonuniform memory latency, both of which grow as the number of threads increases. While these two issues will have to be addressed in future work, we believe our results already show the Galois approach to be very promising.

关键词： parallel programming multicore processors sparse graph algorithm amorphous data-parallelism optimistic execution mesh refinement

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