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检索条件"任意字段=16th ACM Symposium on Principles and Practice of Parallel Programming"

共 407 条记录，以下是151-160 订阅

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Expressing Graph Algorithms Using Generalized Active Messages 13

Expressing Graph Algorithms Using Generalized Active Message...

引用

18th acm SIGPLAN symposium on principles and practice of parallel programming

作者： Edmonds, Nick Willcock, Jeremiah Lumsdaine, Andrew Indiana Univ Bloomington IN 47405 USA

ISBN: (纸本)9781450319225

Recently, graph computation has emerged as an important class of high-performance computing application whose characteristics differ markedly from those of traditional, compute-bound, kernels. Libraries such as BLAS, LAPACK, and others have been successful in codifying best practices in numerical computing. the data-driven nature of graph applications necessitates a more complex application stack incorporating runtime optimization. In this paper, we present a method of phrasing graph algorithms as collections of asynchronous, concurrently executing, concise code fragments which may be invoked both locally and in remote address spaces. A runtime layer performs a number of dynamic optimizations, including message coalescing, message combining, and software routing. Practical implementations and performance results are provided for a number of representative algorithms.

关键词： parallel Graph Algorithms Active Messages parallel programming Models

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parallel breadth-first BDD construction

Parallel breadth-first BDD construction

引用

Proceedings of the 1997 6th acm SIGPLAN symposium on principles and practice of parallel programming

作者： Yang, Bwolen O'Hallaron, David R. Carnegie Mellon Univ Pittsburgh United States

With the increasing complexity of protocol and circuit designs, formal verification has become an important research area and binary decision diagrams (BDDs) have been shown to be a powerful tool in formal verification. this paper presents a parallel algorithm for BDD construction targeted at shared memory multiprocessors and distributed shared memory systems. this algorithm focuses on improving memory access locality through specialized memory managers and partial breadth-first expansion, and on improving processor utilization through dynamic load balancing. the results on a shared memory system show speedups of over two on four processors and speedups of up to four on eight processors. the measured results clearly identify the main source of bottlenecks and point out some interesting directions for further improvements.

关键词： parallel algorithms

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the lock-free k-LSM relaxed priority queue 2015

The lock-free k-LSM relaxed priority queue

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20th acm SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2015

作者： Wimmer, Martin Gruber, Jakob Träff, Jesper Larsson Tsigas, Philippas Faculty of Informatics Parallel Computing Vienna University of Technology Vienna/Wien1040 Austria Computer Science and Engineering Chalmers University of Technology Göteborg412 96 Sweden

ISBN: (纸本)9781450332057

We present a new, concurrent, lock-free priority queue that relaxes the delete-min operation to allow deletion of any of the ρ+1 smallest keys instead of only a minimal one, where ρ is a parameter that can be configured at runtime. It is built from a logarithmic number of sorted arrays, similar to log-structured merge-trees (LSM). For keys added and removed by the same thread the behavior is identical to a non-relaxed priority queue. We compare to state-of-the-art lock-free priority queues with both relaxed and non-relaxed semantics, showing high performance and good scalability of our approach.

关键词： parallel programming

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GraphCube: Interconnection Hierarchy-aware Graph Processing 24

GraphCube: Interconnection Hierarchy-aware Graph Processing

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29th acm SIGPLAN Annual symposium on principles and practice of parallel programming (PPoPP)

作者： Gan, Xinbiao Wu, Guang Qiu, Shenghao Xiong, Feng Si, Jiaqi Fang, Jianbin Dong, Dezun Gong, Chunye Li, Tiejun Wang, Zheng NUDT Beijing Peoples R China Univ Leeds Leeds W Yorkshire England Natl Supercomputer Ctr Tianjin Peoples R China

ISBN: (纸本)9798400704352

Processing large-scale graphs with billions to trillions of edges requires efficiently utilizing parallel systems. However, current graph processing engines do not scale well beyond a few tens of computing nodes because they are oblivious to the communication cost variations across the interconnection hierarchy. We introduce GraphCube, a better approach to optimizing graph processing on large-scale parallel systems with complex interconnections. GraphCube features a new graph partitioning approach to achieve better load balancing and minimize communication overhead across multiple levels of the interconnection hierarchy. We evaluate GraphCube by applying it to fundamental graph operations performed on synthetic and real-world graph datasets. Our evaluation used up to 79,024 computing nodes and 1.2+ million processor cores. Our large-scale experiments show that GraphCube outperforms state-of-the-art parallel graph processing methods in throughput and scalability. Furthermore, GraphCube outperformed the top-ranked systems on the Graph 500 list.

关键词： Graph processing Graph partitioning parallel computing Vectorization Graph500

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Work-stealing with Configurable Scheduling Strategies 13

Work-stealing with Configurable Scheduling Strategies

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18th acm SIGPLAN symposium on principles and practice of parallel programming

作者： Wimmer, Martin Traeff, Jesper Larsson Cederman, Daniel Tsigas, Philippas Vienna Univ Technol Fac Informat Res Grp Parallel Comp A-1040 Vienna Austria Chalmers Univ Technol S-41296 Gothenburg Sweden

ISBN: (纸本)9781450319225

Work-stealing systems are typically oblivious to the nature of the tasks they are scheduling. they do not know or take into account how long a task will take to execute or how many subtasks it will spawn. Moreover, task execution order is typically determined by an underlying task storage data structure, and cannot be changed. there are thus possibilities for optimizing task parallel executions by providing information on specific tasks and their preferred execution order to the scheduling system. We investigate generalizations of work-stealing and introduce a framework enabling applications to dynamically provide hints on the nature of specific tasks using scheduling strategies. Strategies can be used to independently control both local task execution and steal order. Strategies allow optimizations on specific tasks, in contrast to more conventional scheduling policies that are typically global in scope. Strategies are composable and allow different, specific scheduling choices for different parts of an application simultaneously. We have implemented a work-stealing system based on our strategy framework. A series of benchmarks demonstrates beneficial effects that can be achieved with scheduling strategies.

关键词： Algorithms Work-stealing scheduler hints strategies priorities

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High performance Fortran for highly irregular problems

High performance Fortran for highly irregular problems

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Proceedings of the 1997 6th acm SIGPLAN symposium on principles and practice of parallel programming

作者： Hu, Y.Charlie Johnsson, S.Lennart Teng, Shang-Hua Harvard Univ Cambridge United States

We present a general data parallel formulation for highly irregular problems in High Performance Fortran (HPF). Our formulation consists of (1) a method for linearizing irregular data structures (2) a data parallel implementation (in HPF) of graph partitioning algorithms applied to the linearized data structure, (3) techniques for expressing irregular communication and nonuniform computations associated with the elements of linearized data structures. We demonstrate and evaluate our formulation on a parallel, hierarchical N-body method for the evaluation of potentials and forces of nonuniform particle distributions. Our experimental results demonstrate that efficient data parallel (HPF) implementations of highly nonuniform problems are feasible with the proper language/compiler/runtime support. Our data parallel N-body code provides a much needed 'benchmark' code for evaluating and improving HPF compilers.

关键词： parallel processing systems

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Triolet: A programming system that unifies algorithmic skeleton interfaces for high-performance cluster computing 14

Triolet: A programming system that unifies algorithmic skele...

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2014 19th acm SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2014

作者： Rodrigues, Christopher Jablin, thomas Dakkak, Abdul Hwu, Wen-Mei University of Illinois at Urbana-Champaign United States

ISBN: (纸本)9781450326568

Functional algorithmic skeletons promise a high-level programming interface for distributed-memory clusters that free developers from concerns of task decomposition, scheduling, and communication. Unfortunately, prior distributed functional skeleton frameworks do not deliver performance comparable to that achievable in a low-level distributed programming model such as C with MPI and OpenMP, even when used in concert with high-performance array libraries. there are several causes: they do not take advantage of shared memory on each cluster node;they impose a fixed partitioning strategy on input data;and they have limited ability to fuse loops involving skeletons that produce a variable number of outputs per input. We address these shortcomings in the Triolet programming language through a modular library design that separates concerns of parallelism, loop nesting, and data partitioning. We show how Triolet substantially improves the parallel performance of algorithms involving array traversals and nested, variable-size loops over what is achievable in Eden, a distributed variant of Haskell. We further demonstrate how Triolet can substantially simplify parallel programming relative to C with MPI and OpenMP while achieving 23.100% of its performance on a 128-core cluster. Copyright © 2014 acm.

关键词： parallel programming

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Data Transformations Enabling Loop Vectorization on Multithreaded Data parallel Architectures

Data Transformations Enabling Loop Vectorization on Multithr...

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

作者： Jang, Byunghyun Mistry, Perhaad Schaa, Dana Dominguez, Rodrigo Kaeli, David Northeastern Univ Dept ECE Boston MA 02115 USA

ISBN: (纸本)9781605587080

Loop vectorization, a key feature exploited to obtain high performance on Single Instruction Multiple Data (SIMD) vector architectures, is significantly hindered by irregular memory access patterns in the data stream. this paper describes data transformations that allow us to vectorize loops targeting massively multithreaded data parallel architectures. We present a mathematical model that captures loop-based memory access patterns and computes the most appropriate data transformations in order to enable vectorization. Our experimental results show that the proposed data transformations can significantly increase the number of loops that can be vectorized and enhance the data-level parallelism of applications. Our results also show that the overhead associated with our data transformations can be easily amortized as the size of the input data set increases. For the set of high performance benchmark kernels studied, we achieve consistent and significant performance improvements (up to 11.4X) by applying vectorization using our data transformation approach.

关键词： Loop Vectorization Data Transformation GPGPU

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Fine-grain parallel megabase sequence comparison with multiple heterogeneous GPUs 14

Fine-grain parallel megabase sequence comparison with multip...

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2014 19th acm SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2014

作者： De Sandes, Edans F.O. Miranda, Guillermo Melo, Alba C.M.A. Martorell, Xavier Ayguadé, Eduard University of Brasilia Brazil Universitat Politècnica de Catalunya Barcelona Supercomputing Center Spain

ISBN: (纸本)9781450326568

this paper proposes and evaluates a parallel strategy to execute the exact Smith-Waterman (SW) algorithm for megabase DNA sequences in heterogeneous multi-GPU platforms. In our strategy, the computation of a single huge SW matrix is spread over multiple GPUs, which communicate border elements to the neighbour, using a circular buffer mechanism that hides the communication overhead. We compared 4 pairs of human-chimpanzee homologous chromosomes using 2 different GPU environments, obtaining a performance of up to 140.36 GCUPS (Billion of cells processed per second) with 3 heterogeneous GPUS.

关键词： Graphics processing unit

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Using Sample-Based Time Series Data for Automated Diagnosis of Scalability Losses in parallel Programs 20

Using Sample-Based Time Series Data for Automated Diagnosis ...

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

作者： Wei, Lai Mellor-Crummey, John Rice Univ Dept Comp Sci Houston TX 77005 USA Rice Univ Houston TX USA Pony Ai Fremont CA USA

ISBN: (纸本)9781450368186

the performance of many parallel applications has failed to scale as fast as successive generations of hardware on which these applications execute. To understand the cause of scalability losses, experts use performance tools to monitor and analyze application behavior. Profiles generated by performance tools can usually indicate the presence of scalability losses while time series data are generally necessary to pinpoint the root causes of such losses. However, manual analysis of time series data can be difficult in executions with a large number of processes, long running times, and deep call chains. this paper describes an automated framework that analyzes sample-based time series data to diagnose scalability losses in parallel executions. the framework's automated diagnosis of scalability losses indicates their symptoms, severity, and causes. Two case studies illustrate the effectiveness of this framework. When compared to a tool that analyzes performance using instrumentation-based traces, our overhead for collecting sample-based time series is 1/28 in time and 1/1600 in space while our automated analysis takes 1/25 of the time.

关键词： Performance automated diagnosis scalability losses sample-based time series data

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