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5th International Symposium on Computing and Networking (CANDAR)

作者： Loulergue, Frederic No Arizona Univ Sch Informat Comp & Cyber Syst Flagstaff AZ 86011 USA

ISBN: (纸本)9781538620878

This paper presents an extension of a library for the Coq interactive theorem prover that enables the development of correct functional parallel programs based on sequential program transformation and automatic parallelization using an algorithmic skeleton named accumulate. Such an algorithmic skeleton is a pattern of a parallel algorithm that is provided as a high-order function implemented in parallel. The use of this framework is illustrated with the bracket matching problem, including experiments on a parallel machine.

关键词： data parallel programming functional programming formal verification interactive theorem proving Coq bulk synchronous parallelism

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dataCENTER-SCALE COMPUTING Introduction

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IEEE MICRO 2010年第4期30卷 6-7页

作者： Barroso, Luiz Andre Ranganathan, Parthasarathy Google Mountain View CA 94043 USA HP Labs Mississauga ON Canada

Although the field of datacenter computing is arguably still in its relative infancy, a sizable body of work from both academia and industry is already available and some consistent technological trends have begun to emerge. This special issue presents a small sample of the work underway by researchers and professionals in this new field. The selection of articles presented reflects the key role that hardware-software codesign plays in the development of effective datacenter-scale computer systems.

关键词： datacenter Computing Hardware Multicore data parallel programming Networking Storage Energy Efficiency

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C++ components describing parallel domain decomposition and communication

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INTERNATIONAL JOURNAL OF parallel EMERGENT AND DISTRIBUTED SYSTEMS 2009年第6期24卷 467-477页

作者： Blatt, Markus Bastian, Peter Ruprechts Karls Univ Heidelberg Interdisziplinares Zentrum Wissensch Rech IWR Neuenheimer Feld 368 D-69120 Heidelberg Germany

Large-scale parallel codes require the data to be decomposed between the set of processes active in the computation. This data decomposition implies recurring communication schemes. T he paper introduces generic template classes in C++ for describing the data decomposition. The aim is to store the data in arbitrary existent efficient sequential data structures. Each entry in the sequential data structure corresponds to an entry in the virtual global view of the container. Once the decomposition is setup the needed communication schemes can be created automatically and can be used to communicate values from containers of various types. Even containers with a varying number of values associated with an entry are possible. The framework abstracts the decomposition information and the communication in the client code from the eventual parallel paradigm choice. A prototype based on Message Passing Interface standard is presented. It relieves the user from specifying information that is already known at compile time.

关键词： domain decomposition methods data parallel programming objectoriented programming generic programming finite element methods iterative solvers

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A HYBRID SHARED MEMORY EXECUTION MODEL FOR A data parallel LANGUAGE WITH I/O

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parallel PROCESSING LETTERS 2008年第1期18卷 23-37页

作者： Grelck, Clemens Kuthe, Steffen Scholz, Sven-Bodo Univ Lubeck Inst Software Technol & Programming Languages Ratzeburger Allee 160 D-23538 Lubeck Germany Univ Hertfordshire Dept Comp Sci Hatfield AL10 9AB Herts England

We propose a novel execution model for the implicitly parallel execution of data parallel programs in the presence of general I/O operations. This model is called hybrid because it combines the advantages of the standard execution models fork/join and SPMD. Based on program analysis the hybrid model adapts itself to one or the other on the granularity of individual instructions. We outline compilation techniques that systematically derive the organization of parallel code from data flow characteristics aiming at the reduction of execution mode switches in general and synchronization/communication requirements in particular. Experiments based on a prototype implementation show the effectiveness of the hybrid execution model for reducing parallel overhead.

关键词： Multithreaded execution execution models implicit parallelisation Single Assignment C declarative array programming data parallel programming

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Featherweight Transactions: Decoupling Threads and Atomic Blocks 07

Featherweight Transactions: Decoupling Threads and Atomic Bl...

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ACM SIGPLAN Symposium on Principles and Practice of parallel programming

作者： Marathe, Virendra J. Harris, Tim Larus, James R. Univ Rochester Rochester NY 14627 USA

No abstract available.

ISBN: (纸本)9781595936028

No abstract available.

关键词： atomicity transactional memory data parallel programming work groups

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SAC - A functional array language for efficient multi-threaded execution

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INTERNATIONAL JOURNAL OF parallel programming 2006年第4期34卷 383-427页

作者： Grelck, Clemens Scholz, Sven-Bodo Univ Lubeck Inst Software Technol & Programming Languages D-23538 Lubeck Germany Univ Hertfordshire Dept Comp Sci Hatfield AL10 9AB Herts England

We give an in-depth introduction to the design of our functional array programming language SAC, the main aspects of its compilation into host machine code, and its parallelisation based on multi-threading. The language design of SAC aims at combining high-level, compositional array programming with fully automatic resource management for highly productive code development and maintenance. We outline the compilation process that maps SAC programs to computing machinery. Here, our focus is on optimisation techniques that aim at restructuring entire applications from nested compositions of general fine-grained operations into specialised coarse-grained operations. We present our implicit parallelisation technology for shared memory architectures based on multi-threading and discuss further optimisation opportunities on this level of code generation. Both optimisation and parallelisation rigorously exploit the absence of side-effects and the explicit data flow characteristic of a functional setting.

关键词： compiler optimisation data parallel programming multi-threading Single Assignment C

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Support and optimization for parallel sparse programs with array intrinsics of Fortran 90

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parallel COMPUTING 2004年第4期30卷 527-550页

作者： Chang, RG Chuang, TR Lee, JK Natl Tsing Hua Univ Dept Comp Sci Hsinchu 30043 Taiwan Acad Sinica Inst Informat Sci Taipei 115 Taiwan Natl Chung Cheng Univ Dept CSIE Hsinchu Taiwan

Fortran 90 provides a rich set of array intrinsic functions that are useful for representing array expressions and data parallel programming. However, the application of these intrinsic functions to sparse data sets in distributed memory environments, is currently not supported by vendors of Fortran 90 and HPF compilers. Our recent research work has been aimed at, providing parallel processing supports for sparse array intrinsics of Fortran 90. Our supporting library uses the following two-level design: (1) in our low-level routines, a sparse input matrix needs to be specified with compression/distribution schemes by programmers, and (2) in the high-level representation, sparse array functions are overloaded for array intrinsic interfaces so that programmers need not be concerned about low-level details. This raises a very interesting optimization problem in the strategies used to transform high-level representations to low-level routines by the automatic selection of distribution and compression schemes for sparse data sets. In this paper, we propose solutions to address this optimization problem, which is shown to be NP-hard. We develop a heuristic algorithm based on annotated program graphs. To the best of our knowledge, our selection scheme, is the first to automatically select compression and distribution schemes for sparse data arrays with the array intrinsics of Fortran 90 in a distributed memory environment. Experimental results show that our selection algorithms are consistent with our cost model, and effective in selecting appropriate compression and distribution schemes for improving the performance of application programs that operate on sparse data sets. Our experiments were performed on an IBM SP-2 machine using our parallel sparse array intrinsics for Fortran 90. (C) 2004 Published by Elsevier B.V.

关键词： parallel sparse compiler Fortran 90 array intrinsics distributed environments optimizing compilers sparse computations data parallel programming

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A semantic framework to address data locality in data parallel languages

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parallel COMPUTING 2004年第1期30卷 139-161页

作者： Violard, E Univ Strasbourg LSIIT ICPS Strasbourg France

We developed a theory in order to address crucial questions of program design methodology. This theory deals with data locality which is a main issue in parallel programming. In this article, we regard this theory and its model as a minimum semantic domain for data parallel languages. The introduction of a semantic domain is justified because the classical data parallel languages (HPF and C*) have different intuitive semantics: Indeed, they use different concepts in order to express data locality. These concepts are alignment in HPF and shape in C*. Consequently these two languages define their own balance between compiler and programmer investments in order to reach program efficiency. We present our theory as a foundation for defining a better balance. (C) 2003 Elsevier B.V. All rights reserved.

关键词： data parallel programming equational languages semantics parallel programs design data locality

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VFC: the Vienna Fortran compiler

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Scientific programming 1999年第1期7卷 67-81页

作者： Benkner, Siegfried Institute for Software Technology and Parallel Systems University of Vienna Liechtenstein Strasse 22 A‐1090 Vienna Austria

High Performance Fortran (HPF) offers an attractive high-level language interface for programming scalable parallel architectures providing the user with directives for the specification of data distribution and delegating to the compiler the task of generating an explicitly parallel program. Available HPF compilers can handle regular codes quite efficiently, but dramatic performance losses may be encountered for applications which are based on highly irregular, dynamically changing data structures and access patterns. In this paper we introduce the Vienna Fortran Compiler (VFC), a new source-to-source parallelization system for HPF+, an optimized version of HPF, which addresses the requirements of irregular applications. In addition to extended data distribution and work distribution mechanisms, HPF+ provides the user with language features for specifying certain information that decisively influence a program's performance. This comprises data locality assertions, non-local access specifications and the possibility of reusing runtime-generated communication schedules of irregular loops. Performance measurements of kernels from advanced applications demonstrate that with a high-level data parallel language such as HPF+ a performance close to hand-written message-passing programs can be achieved even for highly irregular codes.

关键词： High Performance Fortran data parallel programming data distribution parallelizing compilers communication schedule reuse

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Which approach to parallelizing scientific codes - That is the question

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parallel COMPUTING 1997年第1-2期23卷 165-180页

作者： Berthou, JY Colombet, L CEA DI CISI F-38054 GRENOBLE 9 FRANCE

We present in this paper the strong points and limitations of semi-automatic parallelization, data parallel programming and message passing programming. We apply these on two numerical algorithms namely a bi-dimensional Fourier transform algorithm and a conjugate gradient programs. We implemented this program for each of the different methods on a Gray T3D. The results of these experiments demonstrate the accuracy of our proposition that when the three methods are combined, efficiency, portability and easiness of parallel programming may be achieved.

关键词： automatic parallelization message passing programming data parallel programming HPF MPI PVM

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