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检索条件"任意字段=9th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

共 385 条记录，以下是81-90 订阅

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DOJ: Dynamically parallelizing Object-Oriented Programs 12

DOJ: Dynamically Parallelizing Object-Oriented Programs

引用

17th acm sigplan symposium on principles and practice of parallel programming

作者： Eom, Yong Hun Yang, Stephen Jenista, James C. Demsky, Brian Univ Calif Irvine Irvine CA 92717 USA

ISBN: (纸本)9781450311601

We present Dynamic Out-of-Order Java (DOJ), a dynamic parallelization approach. In DOJ, a developer annotates code blocks as tasks to decouple these blocks from the parent execution thread. the DOJ compiler then analyzes the code to generate heap examiners that ensure the parallel execution preserves the behavior of the original sequential program. Heap examiners dynamically extract heap dependences between code blocks and determine when it is safe to execute a code block. We have implemented DOJ and evaluated it on twelve benchmarks. We achieved an average compilation speedup of 31.15x over OoOJava and an average execution speedup of 12.73x over sequential versions of the benchmarks.

关键词： Algorithms Performance parallel programming Dynamic Analysis Object-Oriented Analysis Heap Analysis parallelization

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Analysis of event synchronization in a parallel programming tool 90

Analysis of event synchronization in a parallel programming ...

引用

2nd acm sigplan symposium on principles and practice of parallel programming, PPOPP 1990

作者： Callahan, David Kennedy, Ken Subhlok, Jaspal Tera Computer Company 400 North 34th Street SeattleWA98103 United States Department of Computer Science Rice University HoustonTX77251-1892 United States

ISBN: (纸本)0897913507

Understanding synchronization is important for a parallel programming tool that uses dependence analysis as the basis for advising programmers on the correctness of parallel constructs. this paper discusses static analysis methods that can be applied to parallel programs with event variable synchronization. the objective is to be able to predict potential data races in a parallel program. the focus is on how dependences and synchronization statements inside loops can be used to analyze complete programs with parallel loop and parallel case style parallelism. © 1990 acm.

关键词： Synchronization

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OpenCL as a Unified programming Model for Heterogeneous CPU/GPU Clusters 12

OpenCL as a Unified Programming Model for Heterogeneous CPU/...

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17th acm sigplan symposium on principles and practice of parallel programming

作者： Kim, Jungwon Seo, Sangmin Lee, Jun Nah, Jeongho Jo, Gangwon Lee, Jaejin Seoul Natl Univ Sch Comp Sci & Engn Ctr Manycore Programming Seoul 151744 South Korea

ISBN: (纸本)9781450311601

In this paper, we propose an OpenCL framework for heterogeneous CPU/GPU clusters, and show that the framework achieves both high performance and ease of programming. the framework provides an illusion of a single system for the user. It allows the application to utilize multiple heterogeneous compute devices, such as multicore CPUs and GPUs, in a remote node as if they were in a local node. No communication API, such as the MPI library, is required in the application source. We implement the OpenCL framework and evaluate its performance on a heterogeneous CPU/GPU cluster that consists of one host node and nine compute nodes using eleven OpenCL benchmark applications.

关键词： Algorithm Design Experimentation Languages Measurement Performance OpenCL Clusters Heterogeneous computing programming models

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Provably and Practically Efficient Granularity Control 19

Provably and Practically Efficient Granularity Control

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24th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Acar, Umut A. Aksenov, Vitaly Chargueraud, Arthur Rainey, Mike Carnegie Mellon Univ Pittsburgh PA 15213 USA INRIA Paris France ITMO Univ St Petersburg Russia Univ Strasbourg ICube CNRS Strasbourg France Indiana Univ Bloomington IN 47405 USA

ISBN: (纸本)9781450362252

Over the past decade, many programming languages and systems for parallel-computing have been developed, e.g., Fork/Join and Habanero Java, parallel Haskell, parallel ML, and X10. Although these systems raise the level of abstraction for writing parallel codes, performance continues to require labor-intensive optimizations for coarsening the granularity of parallel executions. In this paper, we present provably and practically efficient techniques for controlling granularity within the run-time system of the language. Our starting point is "oracle-guided scheduling", a result from the functional-programming community that shows that granularity can be controlled by an "oracle" that can predict the execution time of parallel codes. We give an algorithm for implementing such an oracle and prove that it has the desired theoretical properties under the nested-parallel programming model. We implement the oracle in C++ by extending Cilk and evaluate its practical performance. the results show that our techniques can essentially eliminate hand tuning while closely matching the performance of hand tuned codes.

关键词： parallel programming languages granularity control

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An Overview of Medusa: Simplified Graph Processing on GPUs 12

An Overview of Medusa: Simplified Graph Processing on GPUs

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17th acm sigplan symposium on principles and practice of parallel programming

作者： Zhong, Jianlong He, Bingsheng Nanyang Technol Univ Singapore 639798 Singapore

ISBN: (纸本)9781450311601

Graphs are the de facto data structures for many applications, and efficient graph processing is a must for the application performance. GPUs have an order of magnitude higher computational power and memory bandwidth compared to CPUs and have been adopted to accelerate several common graph algorithms. However, it is difficult to write correct and efficient GPU programs and even more difficult for graph processing due to the irregularities of graph structures. To address those difficulties, we propose a programming framework named Medusa to simplify graph processing on GPUs. Medusa offers a small set of APIs, based on which developers can define their application logics by writing sequential code without awareness of GPU architectures. the Medusa runtime system automatically executes the developer defined APIs in parallel on the GPU, with a series of graph-centric optimizations. this poster gives an overview of Medusa, and presents some preliminary results.

关键词： Algorithms Performance GPGPU GPU programming Graph Processing Runtime Framework

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Statistical scalability analysis of communication operations in distributed applications 01

Statistical scalability analysis of communication operations...

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8th acm sigplan symposium on the principles and practice of parallel Computing

作者： Vetter, JS McCracken, MO Lawrence Livermore Natl Lab Ctr Appl Sci Comp Livermore CA 94551 USA

ISBN: (纸本)9781581133462

Current trends in high performance computing suggest that users will soon have widespread access to clusters of multiprocessors with hundreds, if not thousands, of processors. this unprecedented degree of parallelism will undoubtedly expose scalability limitations in existing applications, where scalability is the ability of a parallel algorithm on a parallel architecture to effectively utilize an increasing number of processors. Users will need precise and automated techniques for detecting the cause of limited scalability. this paper addresses this dilemma. First, we argue that users face numerous challenges in understanding application scalability: managing substantial amounts of experiment data, extracting useful trends from this data, and reconciling performance information with their application's design. Second, we propose a solution to automate this data analysis problem by applying fundamental statistical techniques to scalability experiment data. Finally, we evaluate our operational prototype on several applications, and show that statistical techniques offer an effective strategy for assessing application scalability. In particular, we find that non-parametric correlation of the number of tasks to the ratio of the time for communication operations to overall communication time provides a reliable measure for identifying communication operations that scale poorly.

关键词： Scalability Experimental data statistical techniques Consumers Communication Research Automated recording parallel architectures Surgery Multiprocessor High Performance Computing parallel algorithms

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Dynamic adaptation to available resources for parallel computing in an autonomous network of workstations 01

Dynamic adaptation to available resources for parallel compu...

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8th acm sigplan symposium on the principles and practice of parallel Computing

作者： Rencuzogullari, U Dwarkadas, S Univ Rochester Dept Comp Sci Rochester NY 14627 USA

ISBN: (纸本)9781581133462

Networks of workstations (NOWs), which are generally composed of autonomous compute elements networked together, axe an attractive parallel computing platform since they offer high performance at low cost. the autonomous nature of the environment, however, often results in inefficient utilization due to load imbalances caused by three primary factors: 1) unequal load (compute or communication) assignment to equally-powerful compute nodes, 2) unequal resources at compute nodes, and 3) multiprogramming. these load imbalances result in idle waiting time on cooperating processes that need to synchronize or communicate data. Additional waiting time may result due to local scheduling decisions in a multiprogrammed environment. In this paper, we present a combined approach of compile-time analysis, run-time load distribution, and operating system scheduler cooperation for improved utilization of available resources in an autonomous NOW. the techniques we propose allow efficient resource utilization by taking into consideration all three causes of load imbalance in addition to locality of access in the process of load distribution. the resulting adaptive load distribution and cooperative scheduling system allows applications to take advantage of parallel resources when available by providing better performance than when the loaded resources axe not used at all.

关键词： unbalanced load Load distribution parallel PROCESSING (COMPUTERS) networks of workstations Workstations autonomous network

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Structure-driven Optimizations for Amorphous Data-parallel Programs

Structure-driven Optimizations for Amorphous Data-parallel P...

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15th acm sigplan symposium on principles and practice of parallel programming

作者： Mendez-Lojo, Mario Nguyen, Donald Prountzos, Dimitrios Sui, Xin Hassaan, M. Amber Kulkarni, Milind Burtscher, Martin Pingali, Keshav Univ Texas Austin Inst Computat Engn & Sci Austin TX 78712 USA

ISBN: (纸本)9781605587080

Irregular algorithms are organized around pointer-based data structures such as graphs and trees, and they are ubiquitous in applications. Recent work by the Galois project has provided a systematic approach for parallelizing irregular applications based on the idea of optimistic or speculative execution of programs. However, the overhead of optimistic parallel execution can be substantial. In this paper, we show that many irregular algorithms have structure that can be exploited and present three key optimizations that take advantage of algorithmic structure to reduce speculative overheads. We describe the implementation of these optimizations in the Galois system and present experimental results to demonstrate their benefits. To the best of our knowledge, this is the first system to exploit algorithmic structure to optimize the execution of irregular programs.

关键词： Amorphous Data-parallelism Irregular Programs Optimistic parallelization Synchronization Overheads Cautious Operator Implementations One-shot Optimization Iteration Coalescing

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Effective Communication and Computation Overlap with Hybrid MPI/SMPSs

Effective Communication and Computation Overlap with Hybrid ...

引用

15th acm sigplan symposium on principles and practice of parallel programming

作者： Marjanovic, Vladimir Labarta, Jesus Ayguade, Eduard Valero, Mateo Barcelona Supercomp Ctr BSC CNS Dept Comp Sci Barcelona Spain Tech Univ Catalunya UPC Comp Architecture Dept Barcelona Spain

ISBN: (纸本)9781605587080

Communication overhead is one of the dominant factors affecting performance in high-performance computing systems. To reduce the negative impact of communication, programmers overlap communication and computation by using asynchronous communication primitives. this increases code complexity, requiring more development effort and making less readable programs. this paper presents the hybrid use of MPI and SMPSs (SMP superscalar, a task-based shared-memory programming model) that allows the programmer to easily introduce the asynchrony necessary to overlap communication and computation. We demonstrate the hybrid use of MPI/SMPSs with the high-performance LINPACK benchmark (HPL), and compare it to the pure MPI implementation, which uses the look-ahead technique to overlap communication and computation. the hybrid MPI/SMPSs version significantly improves the performance of the pure MPI version, getting close to the asymptotic performance at medium problem sizes and still getting significant benefits at small/large problem sizes.

关键词： Algorithms Performance Languages parallel programming model MPI hybrid MPI/SMPSs LINPACK

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parallel Determinacy Race Detection for Futures 20

Parallel Determinacy Race Detection for Futures

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25th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Xu, Yifan Singer, Kyle Lee, I-Ting Angelina Washington Univ St Louis St Louis MO 63130 USA

ISBN: (纸本)9781450368186

the use of futures can generate arbitrary dependences in the computation, making it difficult to detect races efficiently. Algorithms proposed by priorwork to detect races on programs with futures all have to execute the program sequentially. We propose F-Order, the first known parallel race detection algorithm that detects races on programs that use futures. Given a computation with work T-1 and span T-infinity, our algorithm detects races in time O((T-1 lg (k) over cap + k(2))/ P + T-infinity(k + lg r lg (k) over cap)) on P processors, where k is the number of future operations, r is the maximum number of readers per memory location, and (k) over cap is the maximum number of future operations done by a single future task, which is typically small. We have also implemented a prototype system based on the proposed algorithm and empirically demonstrates its practical efficiency and scalability.

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