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检索条件"任意字段=17th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

共 368 条记录，以下是191-200 订阅

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DATA-FLOW EQUATIONS FOR EXPLICITLY parallel PROGRAMS 93

DATA-FLOW EQUATIONS FOR EXPLICITLY PARALLEL PROGRAMS

引用

4th SYMP ON principles AND practice OF parallel programming ( PPOPP )

作者： GRUNWALD, D SRINIVASAN, H UNIV COLORADO DEPT COMP SCIBOULDERCO 80309

ISBN: (纸本)9780897915892

We present a solution to the reaching definitions problem for programs with explicit lexically specified parallel constructs, such as cobegin/coend or parallel-sections, both with and without explicit synchronization operations, such as Post, Wait or Advance. the reaching definitions information for sequential programs is used to solve many standard optimization problems. In parallel programs, this information can also be used to explicitly direct communication and data ownership. Although work has been done on analyzing parallel programs to detect data races, little work has been done on optimizing such programs. We show how the memory consistency model specified by an explicitly parallel programming language can influence the complexity of the reaching definitions problem. By selecting the ''weakest'' memory consistency semantics, we can efficiently solve the reaching definitions problem for correct programs.

关键词： Computer software

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Poster: the Problem-Based Benchmark Suite PBBS), V2 27

Poster: The Problem-Based Benchmark Suite PBBS), V2

引用

27th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Anderson, Daniel Blelloch, Guy E. Dhulipala, Laxman Dobson, Magdalen Sun, Yihan Carnegie Mellon Univ Pittsburgh Pittsburgh PA USA Univ Maryland Coll Park MD USA UC Riverside Riverside Riverside CA USA

ISBN: (纸本)9781450392044

the Problem-Based Benchmark Suite (PBBS) is a set of benchmark problems designed for comparing algorithms, implementations and platforms. For each problem, the suite defines the problem in terms of the input-output relationship, and supplies a set of input instances along with input generators, a default implementation, code for checking correctness or accuracy, and a timing harness. the suite makes it possible to compare different algorithms, platforms (e.g. CPU vs CPU), and implementations using different programming languages or libraries. the purpose is to better understand how well a wide variety of problems parallelize, and what techniques/algorithms are most effective. the suite was first announced in 2012 with 14 benchmark problems. Here we describe some significant updates. In particular, we have added nine new benchmarks from a mix of problems in text processing, computational geometry and machine learning. We have further optimized the default implementations;several are the fastest available for multicore CPUs, often achieving near perfect speedup on the 72 core machine we test them on. the suite now also supplies significantly larger default test instances, as well as a broader variety, with many derived from real-world data.

关键词： benchmarking parallel algorithms performance

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Formal Verification of Practical MPI Programs

Formal Verification of Practical MPI Programs

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14th acm sigplan symposium on principles and practice of parallel programming

作者： Vo, Anh Vakkalanka, Sarvani DeLisi, Michael Gopalakrishnan, Ganesh Kirby, Robert M. thakur, Rajeev Univ Utah Sch Comp Salt Lake City UT 84112 USA Argonne Natl Lab Div Math & Comp Sci Argonne IL 60439 USA

ISBN: (纸本)9781605583976

this paper considers the problem of formal verification of MPI programs operating under a fixed test harness for safety properties without building verification models. In our approach, we directly model-check the MPI/C source code, executing its interleavings with the help of a verification scheduler. Unfortunately, the total feasible number of interleavings is exponential, and impractical to examine even for our modest goals. Our earlier publications formalized and implemented a partial order reduction approach that avoided exploring equivalent interleavings, and presented a verification tool called ISP. this paper presents algorithmic and engineering innovations to ISP, including the use of OpenMP parallelization, that now enables it to handle practical MPI programs, including: (i) ParMETIS - a widely used hypergraph partitioner, and (ii) MADRE - a Memory Aware Data Re-distribution Engine, both developed outside our group. Over these benchmarks, ISP has automatically verified up to 14K lines of MPI/C code, producing error traces of deadlocks and assertion violations within seconds.

关键词： Verification MPI Message Passing Interface distributed programming model checking dynamic partial order reduction

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A framework for practical parallel fast matrix multiplication 2015

A framework for practical parallel fast matrix multiplicatio...

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

作者： Benson, Austin R. Ballard, Grey Institute for Computational and Mathematical Engineering Stanford University StanfordCA United States Sandia National Laboratories LivermoreCA United States

ISBN: (纸本)9781450332057

Matrix multiplication is a fundamental computation in many scientific disciplines. In this paper, we show that novel fast matrix multiplication algorithms can significantly outperform vendor implementations of the classical algorithm and Strassen's fast algorithm on modest problem sizes and shapes. Furthermore, we show that the best choice of fast algorithm depends not only on the size of the matrices but also the shape. We develop a code generation tool to automatically implement multiple sequential and shared-memory parallel variants of each fast algorithm, including our novel parallelization scheme. this allows us to rapidly benchmark over 20 fast algorithms on several problem sizes. Furthermore, we discuss a number of practical implementation issues for these algorithms on shared-memory machines that can direct further research on making fast algorithms practical. Copyright 2015 acm.

关键词： Matrix algebra

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Accelerating CUDA Graph Algorithms at Maximum Warp 11

Accelerating CUDA Graph Algorithms at Maximum Warp

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16th acm symposium on principles and practice of parallel programming

作者： Hong, Sungpack Kim, Sang Kyun Oguntebi, Tayo Olukotun, Kunle Stanford Univ Comp Syst Lab Stanford CA 94305 USA

ISBN: (纸本)9781450301190

Graphs are powerful data representations favored in many computational domains. Modern GPUs have recently shown promising results in accelerating computationally challenging graph problems but their performance suffers heavily when the graph structure is highly irregular, as most real-world graphs tend to be. In this study, we first observe that the poor performance is caused by work imbalance and is an artifact of a discrepancy between the GPU programming model and the underlying GPU architecture. We then propose a novel virtual warp-centric programming method that exposes the traits of underlying GPU architectures to users. Our method significantly improves the performance of applications with heavily imbalanced workloads, and enables trade-offs between workload imbalance and ALU underutilization for fine-tuning the performance. Our evaluation reveals that our method exhibits up to 9x speedup over previous GPU algorithms and 12x over single thread CPU execution on irregular graphs. When properly configured, it also yields up to 30% improvement over previous GPU algorithms on regular graphs. In addition to performance gains on graph algorithms, our programming method achieves 1.3x to 15.1x speedup on a set of GPU benchmark applications. Our study also confirms that the performance gap between GPUs and other multi-threaded CPU graph implementations is primarily due to the large difference in memory bandwidth.

关键词： Algorithms Performance parallel graph algorithms CUDA GPGPU

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parallelISM IN LOGIC PROGRAMS

PARALLELISM IN LOGIC PROGRAMS

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17th ANNUAL SYMP OF thE ASSOC FOR COMPUTING MACHINERY : principles OF programming LANGUAGES

作者： RAMAKRISHNAN, R Univ of Wisconsin-Madison WI United States

ISBN: (纸本)0897913434

the author considers the parallel evaluation of logic programs. this has been the subject of much research in the logic programming and, recently, the deductive database communities. the author reviews this work, and observes that there is a commonly used measure of parallelism based on a top-down evaluation paradigm of identifying subgoals and answers. To formalize this intuition, he proposes a simple abstract model of computation that makes precise the tension between the objectives of restricting the computation on the one hand and extracting parallelism on the other. A survey of proposed parallel evaluation programs for logic programs.

关键词： Computer programming

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A programming model and runtime system for significance-aware energy-efficient computing 2015

A programming model and runtime system for significance-awar...

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

作者： Vassiliadis, Vassilis Parasyris, Konstantinos Chalios, Charalambos Antonopoulos, Christos D. Lalis, Spyros Bellas, Nikolaos Vandierendonck, Hans Nikolopoulos, Dimitrios S. Electrical and Computer Eng. Dept. University of Thessaly Greece Greece Queen's University Belfast United Kingdom

ISBN: (纸本)9781450332057

We introduce a task-based programming model and runtime system that exploit the observation that not all parts of a program are equally significant for the accuracy of the end-result, in order to trade off the quality of program outputs for increased energy-efficiency. this is done in a structured and flexible way, allowing for easy exploitation of different points in the quality/energy space, without adversely affecting application performance. the runtime system can apply a number of different policies to decide whether it will execute less-significant tasks accurately or approximately. the experimental evaluation indicates that our system can achieve an energy reduction of up to 83% compared with a fully accurate execution and up to 35% compared with an approximate version employing loop perforation. At the same time, our approach always results in graceful quality degradation.

关键词： Energy efficiency

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Scaling implicit parallelism via dynamic control replication 21

Scaling implicit parallelism via dynamic control replication

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26th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2021

作者： Bauer, Michael Lee, Wonchan Slaughter, Elliott Jia, Zhihao Di Renzo, Mario Papadakis, Manolis Shipman, Galen McCormick, Patrick Garland, Michael Aiken, Alex NVIDIA United States Slac National Accelerator Laboratory United States Carnegie Mellon University United States Sapienza University of Rome Italy Los Alamos National Laboratory United States Stanford University United States

ISBN: (纸本)9781450382946

We present dynamic control replication, a run-time program analysis that enables scalable execution of implicitly parallel programs on large machines through a distributed and efficient dynamic dependence analysis. Dynamic control replication distributes dependence analysis by executing multiple copies of an implicitly parallel program while ensuring that they still collectively behave as a single execution. By distributing and parallelizing the dependence analysis, dynamic control replication supports efficient, on-the-fly computation of dependences for programs with arbitrary control flow at scale. We describe an asymptotically scalable algorithm for implementing dynamic control replication that maintains the sequential semantics of implicitly parallel programs. An implementation of dynamic control replication in the Legion runtime delivers the same programmer productivity as writing in other implicitly parallel programming models, such as Dask or TensorFlow, while providing better performance (11.4X and 14.9X respectively in our experiments), and scalability to hundreds of nodes. We also show that dynamic control replication provides good absolute performance and scaling for HPC applications, competitive in many cases with explicitly parallel programming systems. © 2021 acm.

关键词： parallel programming

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Advanced synchronization techniques for task-based runtime systems 21

Advanced synchronization techniques for task-based runtime s...

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26th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2021

作者： Álvarez, David Sala, Kevin Maroñas, Marcos Roca, Aleix Beltran, Vincenç Barcelona Supercomputing Center Barcelona Spain

ISBN: (纸本)9781450382946

Task-based programming models like OmpSs-2 and OpenMP provide a flexible data-flow execution model to exploit dynamic, irregular and nested parallelism. Providing an efficient implementation that scales well with small granularity tasks remains a challenge, and bottlenecks can manifest in several runtime components. In this paper, we analyze the limiting factors in the scalability of a task-based runtime system and propose individual solutions for each of the challenges, including a wait-free dependency system and a novel scalable scheduler design based on delegation. We evaluate how the optimizations impact the overall performance of the runtime, both individually and in combination. We also compare the resulting runtime against state of the art OpenMP implementations, showing equivalent or better performance, especially for fine-grained tasks. © 2021 acm.

关键词： parallel programming

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INFINEL: An efficient GPU-based processing method for unpredictable large output graph queries 24

INFINEL: An efficient GPU-based processing method for unpred...

引用

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

作者： Park, Sungwoo Oh, Seyeon Kim, Min-Soo Korea Adv Inst Sci & Technol Seoul South Korea GraphAI Seoul South Korea

ISBN: (纸本)9798400704352

With the introduction of GPUs, which are specialized for iterative parallel computations, the execution of computationintensive graph queries using a GPU has seen significant performance improvements. However, due to the memory constraints of GPUs, there has been limited research on handling large-scale output graph queries with unpredictable output sizes on a GPU. Traditionally, two-phase methods have been used, where the query is re-executed after splitting it into sub-tasks while only considering the size of the output in a static manner. However, two-phase methods become highly inefficient when used with graph data with extreme skew, failing to maximize the GPU performance. this paper proposes INFINEL, which handles unpredictable large output graph queries in a one-phase method through chunk allocation per thread and kernel stop/restart methods. We also propose applicable optimization techniques due to the corresponding unique characteristics of operating with low time/space overhead and not heavily relying on the GPU output buffer size. through extensive experiments, we demonstrate that our one-phase method of INFINEL improves the performance by up to 31.5 times over the conventional twophase methods for triangle listing ULO query.

关键词： Graph query processing Large output parallel computing GPU

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