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检索条件"任意字段=5th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

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AUTOMATIC ALIGNMENT OF ARRAY DATA AND PROCESSES TO REDUCE COMMUNICATION TIME ON DMPPS 95

AUTOMATIC ALIGNMENT OF ARRAY DATA AND PROCESSES TO REDUCE CO...

引用

5th acm sigplan symposium on principles and practice of parallel programming

作者： PHILIPPSEN, M ICSI International Computer Science Institute Berkeley CA and Dept. of Informatics University of Karlsruhe

ISBN: (纸本)9780897917001

this paper investigates the problem of aligning array data and processes in a distributed-memory implementation. We present complete algorithms for compile-time analysis, the necessary program restructuring, and subsequent code-generation, and discuss their complexity. We finally evaluate the practical usefulness by quantitative experiments. the technique presented analyzes complete programs, including branches, loops, and nested parallelism. Alignment is determined with respect to offset, stride, and general ass's relations. Pplacement of both data and processes are computed in a unifying framework based on an extended preference graph and its analysis. Dynamic redistributions are derived. the experimental results are very encouraging. the optimization algorithms implemented in our Modula-2* compiler improved the execution times of the programs by an average over 40% on a MasPar MP-1 with 16384 processors.

关键词： parallel processing systems

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Model and compilation strategy for out-of-core data parallel programs

Model and compilation strategy for out-of-core data parallel...

引用

Proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Bordawekar, Rajesh Choudhary, Alok Kennedy, Ken Koelbel, Charles Paleczny, Michael Syracuse Univ Syracuse United States

It is widely acknowledged in high-performance computing circles that parallel input/output needs substantial improvement in order to make scalable computers truly usable. We present a data storage model that allows processors independent access to their own data and a corresponding compilation strategy that integrates data-parallel computation with data distribution for out-of-core problems. Our results compare several communication methods and I/O optimizations using two out-of-core problems, Jacobi iteration and LU factorization.

关键词： parallel processing systems

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parallel skeletons for structured composition

Parallel skeletons for structured composition

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Proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Darlington, John Guo, Yi-ke To, Hing Wing Yang, Jin Imperial Coll London United Kingdom

In this paper, we propose a straightforward solution to the problems of compositional parallel programming by using skeletons as the uniform mechanism for structured composition. In our approach parallel programs are constructed by composing procedures in a conventional base language using a set of high-level, predefined, functional, parallel computational forms known as skeletons. the ability to compose skeletons provides us with the essential tools for building further and more complex application-oriented skeletons specifying important aspects of parallel computation. Compared with the process network based composition approach, such as PCN, the skeleton approach abstracts away the fine details of connecting communication ports to the higher level mechanism of making data distributions conform, thus avoiding the complexity of using lower level ports as the means of interaction. thus, the framework provides a natural integration of the compositional programming approach with the data parallel programming paradigm.

关键词： parallel processing systems

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GENERATING parallel CODE FROM OBJECT-ORIENTED MAthEMATICAL-MODELS

GENERATING PARALLEL CODE FROM OBJECT-ORIENTED MATHEMATICAL-M...

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5th acm sigplan symposium on principles and practice of parallel programming

作者： ANDERSSON, N FRITZSON, P Linkoping Univ Linkoping Sweden

For a long time efficient use of parallel computers has been hindered by dependencies introduced in software through low-level implementation practice. In this paper we present a programming environment and language called Object-Math (Object oriented Mathematical language for scientific computing), which aims at eliminating this problem by allowing the user to represent mathematical equation-based models directly in the system. the system performs analysis of mathematical models to extract parallelism and automatically generates parallel code for numerical solution. In the context of industrial applications in mechanical analysis, we have so far primarily explored generation of parallel code for solving systems of ordinary differential equations (ODEs), in addition to preliminary work on generating code for solving partial differential equations. Two approaches to extracting parallelism have been implemented and evaluated: extracting parallelism at the equation system level and at the single equation level, respectively. We found that for several applications the corresponding systems of equations do not partition well into subsystems. this means that the equation system level approach is of restricted general applicability. thus, we focused on the equation-level approach which yielded significant parallelism for ODE systems solution. For the bearing simulation applications we present here, the achieved speedup is however critically dependent on low communication latency of the parallel computer.

关键词： parallel processing systems

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Linear-time algorithm for computing the memory access sequence in data-parallel programs

Linear-time algorithm for computing the memory access sequen...

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Proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Kennedy, Ken Nedeljkovic, Nenad Sethi, Ajay Rice Univ Houston United States

Data-parallel languages, such as High Performance Fortran, are widely regarded as a promising means for writing portable programs for distributed-memory machines. Novel features of these languages call for the development of new techniques in both compilers and run-time systems. In this paper, we present an improved algorithm for finding the local memory access sequence in computations involving regular sections of arrays with cyclic(k) distributions. After establishing the fact that regular section indices correspond to elements of an integer lattice, we show how to find a lattice basis that allows for simple and fast enumeration of memory accesses. the complexity of our algorithm is shown to be lower than that of the previous solution for the same problem. In addition, the experimental results demonstrate the efficiency of our method in practice.

关键词： parallel algorithms

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High performance synchronization algorithms for multiprogrammed multiprocessors

High performance synchronization algorithms for multiprogram...

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Proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Wisniewski, Robert W. Kontothanassis, Leonidas I. Scott, Michael L. Univ of Rochester Rochester United States

Scalable busy-wait synchronization algorithms are essential for achieving good parallel program performance on large scale multiprocessors. Such algorithms include mutual exclusion locks, reader-writer locks, and barrier synchronization. Unfortunately, scalable synchronization algorithms are particularly sensitive to the effects of multiprogramming: their performance degrades sharply when processors are shared among different applications, or even among processes of the same application. In this paper we describe the design and evaluation of scalable scheduler-conscious mutual exclusion locks, reader-writer locks, and barriers, and show that by sharing information across the kernel/application interface we can improve the performance of scheduler-oblivious implementations by more than an order of magnitude.

关键词： parallel algorithms

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Distributed data access in AC

Distributed data access in AC

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Proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Carlson, William W. Draper, Jesse M. IDA Supercomputing Research Cent Bowie United States

We have modified the C language to support a programming model based on a shared address space with physically distributed memory. With this model users can write programs in which the nodes of a massively parallel processor can access remote memory without message passing. AC provides support for distributed arrays as well as pointers to distributed data. Simple array references and pointer dereferencing are sufficient to generate low-overhead remote reads and writes. We have implemented these ideas in a compiler based on the GNU C compiler and targeted at Cray Research's T3D. Initial performance measurements show that AC generates code for remote accesses which is considerably faster than that of the native compiler for structures up to about 16 words in size and virtually equivalent for larger transfers.

关键词： parallel processing systems

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Evaluating the locality benefits of active messages

Evaluating the locality benefits of active messages

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Proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Spertus, Ellen Dally, William J. Massachusetts Inst of Technology Cambridge United States

A major challenge in fine-grained computing is achieving locality without excessive scheduling overhead. We built two J-Machine implementations of a fine-grained programming model, the Berkeley threaded Abstract Machine. One implementation takes an Active Messages approach, maintaining a scheduling hierarchy in software in order to improve data cache performance. Another approach relies on the J-Machine's message queues and fast task switch, lowering the control costs at the expense of data locality. Our analysis measures the costs and benefits of each approach, for a variety of programs and cache configurations. the Active Messages implementation is strongest when miss penalties are high and for the finest-grained programs. the hardware-buffered implementation is strongest in direct-mapped caches, where it achieves substantially better instruction cache performance.

关键词： parallel processing systems

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Data and computation transformations for multiprocessors

Data and computation transformations for multiprocessors

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Proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Anderson, Jennifer M. Amarasinghe, Saman P. Lam, Monica S. Stanford Univ Stanford United States

Effective memory hierarchy utilization is critical to the performance of modem multiprocessor architectures. We have developed the first compiler system that fully automatically parallelizes sequential programs and changes the original array layouts to improve memory system performance. Our optimization algorithm consists of two steps. the first step chooses the parallelization and computation assignment such that synchronization and data sharing are minimized. the second step then restructures the layout of the data in the shared address space with an algorithm that is based on a new data transformation framework. We ran our compiler on a set of application programs and measured their performance on the Stanford DASH multiprocessor. Our results show that the compiler can effectively optimize parallelism in conjunction with memory subsystem performance.

关键词： parallel processing systems

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OPTIMAL MAPPING OF SEQUENCES OF DATA-parallel TASKS 95

OPTIMAL MAPPING OF SEQUENCES OF DATA-PARALLEL TASKS

引用

5th acm sigplan symposium on principles and practice of parallel programming

作者： SUBHLOK, J VONDRAN, G HEWLETT PACKARD CORP ADV LASER JET OPERAT BOISE ID 83714 USA

ISBN: (纸本)9780897917001

Many applications in a variety of domains including digital signal processing, image processing, and computer vision are composed of a sequence of tasks that act on a stream of input data sets in a pipelined manner. Recent research has established that these applications are best mapped to a massively parallel machine by dividing the tasks into modules and assigning a subset of the available processors to each module. this paper addresses the problem of optimally mapping such applications onto a massively parallel machine. We formulate the problem of optimizing throughput in task pipelines and present two new solution algorithms. the formulation uses a general and realistic model for inter-task communication, takes memory constraints into account, and addresses the entire problem of mapping which includes clustering tasks into modules, assignment of processors to modules, and possible replication of modules. the first algorithm is based on dynamic programming and finds the optimal mapping of k tasks onto P processors in O(P(4)k(2)) time. We also present a heuristic algorithm that is linear in the number of processors and establish with theoretical and practical results that the solutions obtained are optimal in practical situations. the entire framework is implemented as an automatic mapping tool for the Fx parallelizing compiler for High Performance Fortran. We present experimental results that demonstrate the importance of choosing a good mapping and show that the methods presented yield efficient mappings and predict optimal performance accurately.

关键词： parallel processing systems

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