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检索条件"任意字段=Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming"

共 364 条记录，以下是191-200 订阅

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Communication-Centric Optimizations by Dynamically Detecting Collective Operations 12

Communication-Centric Optimizations by Dynamically Detecting...

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17th ACM SIGPLAN symposium on principles and practice of parallel programming

作者： Hoefler, Torsten Schneider, Timo Univ Illinois Dept Comp Sci Urbana IL USA Tech Univ Chemnitz Dept Comp Sci Chemnitz Germany

ISBN: (纸本)9781450311601

the steady increase of parallelism in high-performance computing platforms implies that communication will be most important in large-scale applications. In this work, we tackle the problem of transparent optimization of large-scale communication patterns using online compilation techniques. We utilize the Group Operation Assembly Language (GOAL), an abstract parallel dataflow definition language, to specify our transformations in a device-independent manner. We develop fast schemes that analyze dataflow and synchronization semantics in GOAL and detect if parts of the (or the whole) communication pattern express a known collective communication operation. the detection of collective operations allows us to replace the detected patterns with highly optimized algorithms or low-level hardware calls and thus improve performance significantly. Benchmark results suggest that our technique can lead to a performance improvement of orders of magnitude compared with various optimized algorithms written in Co-Array Fortran. Detecting collective operations also improves the programmability of parallel languages in that the user does not have to understand the detailed semantics of high-level communication operations in order to generate efficient and scalable code.

关键词： Performance Languages Collective Communication parallel Compiler Optimization parallel Dataflow

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Designing and auto-tuning parallel 3-D FFT for computation-communication overlap 14

Designing and auto-tuning parallel 3-D FFT for computation-c...

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

作者： Song, Sukhyun Hollingsworth, Jeffrey K. Department of Computer Science University of Maryland College Park United States

ISBN: (纸本)9781450326568

this paper presents a method to design and auto-tune a new parallel 3-D FFT code using the non-blocking MPI all-to-all operation. We achieve high performance by optimizing computation-communication overlap. Our code performs fully asynchronous communication without any support from special hardware. We also improve cache performance through loop tiling. To cope with the complex tradeoff regarding our optimization techniques, we parameterize our code and auto-tune the parameters efficiently in a large parameter space. Experimental results from two systems confirm that our code achieves a speedup of up to 1.76× over the FFTW library. Copyright © 2014 ACM.

关键词： Fast Fourier transforms

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Scaling LAPACK Panel Operations Using parallel Cache Assignment

Scaling LAPACK Panel Operations Using Parallel Cache Assignm...

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

作者： Castaldo, Anthony M. Whaley, R. Clint Univ Texas San Antonio Dept Comp Sci San Antonio TX 78249 USA

ISBN: (纸本)9781605587080

In LAPACK many matrix operations are cast as block algorithms which iteratively process a panel using an unblocked algorithm and then update a remainder matrix using the high performance Level 3 BLAS. the Level 3 BLAS have excellent weak scaling, but panel processing tends to be bus bound, and thus scales with bus speed rather than the number of processors (p). Amdahl's law therefore ensures that as p grows, the panel computation will become the dominant cost of these LAPACK routines. Our contribution is a novel parallel cache assignment approach which we show scales well with p. We apply this general approach to the QR and LU panel factorizations on two commodity 8-core platforms with very different cache structures, and demonstrate superlinear panel factorization speedups on both machines. Other approaches to this problem demand complicated reformulations of the computational approach, new kernels to be tuned, new mathematics, an inflation of the high-order flop count, and do not perform as well. By demonstrating a straight-forward alternative that avoids all of these contortions and scales with p, we address a critical stumbling block for dense linear algebra in the age of massive parallelism.

关键词： ATLAS LAPACK QR LU factorization parallel multicore multi-core GPU

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Scalable Top-K Retrieval with Sparta 20

Scalable Top-K Retrieval with Sparta

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

作者： Sheffi, Gali Basin, Dmitry Bortnikov, Edward Carmel, David Keidar, Idit Technion Haifa Israel Yahoo Res Haifa Israel Amazon Haifa Israel

ISBN: (纸本)9781450368186

Many big data processing applications rely on a top-k retrieval building block, which selects (or approximates) the k highest-scoring data items based on an aggregation of features. In web search, for instance, a document's score is the sum of its scores for all query terms. Top-k retrieval is often used to sift through massive data and identify a smaller subset of it for further analysis. Because it filters out the bulk of the data, it often constitutes the main performance bottleneck. Beyond the rise in data sizes, today's data processing scenarios also increase the number of features contributing to the overall score. In web search, for example, verbose queries are becoming mainstream, while state-of-the-art algorithms fail to process long queries in real-time. We present Sparta, a practical parallel algorithm that exploits multi-core hardware for fast (approximate) top-k retrieval. thanks to lightweight coordination and judicious context sharing among threads, Sparta scales both in the number of features and in the searched index size. In our web search case study on 50M documents, Sparta processes 12-term queries more than twice as fast as the state-of-the-art. On a tenfold bigger index, Sparta processes queries at the same speed, whereas the average latency of existing algorithms soars to be an order-of-magnitude larger than Sparta's.

关键词： parallel computing multi-threading performance information retrieval web search top-k search

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Identifying Scalability Bottlenecks for Large-Scale parallel Programs with Graph Analysis 20

Identifying Scalability Bottlenecks for Large-Scale Parallel...

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

作者： Jin, Yuyang Wang, Haojie Tang, Xiongchao Hoefler, Torsten Liu, Xu Zhai, Jidong Tsinghua Univ Beijing Peoples R China Swiss Fed Inst Technol Zurich Switzerland Coll William & Mary Williamsburg VA 23187 USA

ISBN: (纸本)9781450368186

Scaling a parallel program to modern supercomputers is challenging due to inter-process communication, code serialization, and resource contention. Performance analysis tools for finding such scaling bottlenecks either base on profiling or tracing. Profiling incurs lower overheads but does not capture detailed dependencies needed for root-cause analyses. Tracing collects all information at prohibitive overheads. In this work, we develop ScalAna that uses static analysis techniques to achieve the best of both worlds-it enables the analyzability of traces at a cost similar to profiling. We leverage compiler and runtime lightweight techniques to generate performance graph and perform graph analysis algorithm to detect the root cause of scaling issues. We evaluate ScalAna with real applications on the Tianhe-2 supercomputer. Results show that our approach can effectively locate the root cause of scalability bottlenecks for real applications and incur less than 6.38% overhead (1.89% on average) for up to 2,048 processes.

关键词： Profiling Tools Scaling Loss Analysis Performance Optimization

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Automatic Problem Size Sensitive Task Partitioning on Heterogeneous parallel Systems 13

Automatic Problem Size Sensitive Task Partitioning on Hetero...

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

作者： Grasso, Ivan Kofler, Klaus Cosenza, Biagio Fahringer, thomas Univ Innsbruck Inst Informat A-6020 Innsbruck Austria

ISBN: (纸本)9781450319225

In this paper we propose a novel approach which automatizes task partitioning in heterogeneous systems. Our framework is based on the Insieme Compiler and Runtime infrastructure [1]. the compiler translates a single-device OpenCL program into a multi-device OpenCL program. the runtime system then performs dynamic task partitioning based on an offline-generated prediction model. In order to derive the prediction model, we use a machine learning approach that incorporates static program features as well as dynamic, input sensitive features. Our approach has been evaluated over a suite of 23 programs and achieves performance improvements compared to an execution of the benchmarks on a single CPU and a single GPU only.

关键词： Languages Algorithms Performance heterogeneous computing compilers GPU task partitioning code analysis machine learning runtime system

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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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On the complexity of escape analysis 97

On the complexity of escape analysis

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the 1997 24th ACM SIGPLAN-SIGACT symposium on principles of programming Languages, POPL'97

作者： Deutsch, Alain INRIA Rocquencourt Le Chesnay France

ISBN: (纸本)9780897918534

Escape analysis is an abstract interpretation technique for statistically optimizing storage management devised by Park & Goldberg [30]. the main application of escape analysis is the optimization of storage management and data locality in garbage-collected languages such as ML or JAVA. We improve the previously known exponential complexity bound of Park & Goldberg: we show that first-order escape analysis (EA1) can be solved in almost linear time, and that second-order escape analysis (EA2) is DEXPTIME-hard. We exhibit a fast, equational, path-compression based abstract interpretation algorithm for EA1. We prove that it is sound and complete, and that its time complexity is O(n log2 n). We sketch an extension of the analysis to higher-order functions and imperative operations that is approximate. Finally we briefly present some experimental evidence that escape analysis may be useful in practice.

关键词： programming theory

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Determining the idle time of a tiling 97

Determining the idle time of a tiling

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the 1997 24th ACM SIGPLAN-SIGACT symposium on principles of programming Languages, POPL'97

作者： Hogstedt, Karin Carter, Larry Ferrante, Jeanne UCSD La Jolla CA United States

ISBN: (纸本)9780897918534

this paper investigates the idle time associated with a parallel computation, that is, the time that processors are idle because they are either waiting for data from other processors or waiting to synchronize with other processors. We study doubly-nested loops corresponding to parallelogram- or trapezoidal-shaped iteration spaces that have been parallelized by the well-known tiling transformation. We introduce the notion of rise r, which relates the shape of the iteration space to that of the tiles. For parallelogram-shaped iteration spaces, we show that when r ≤ -2, the idle time is linear in P, the number of processors, but when r ≥ -1, it is quadratic in P. In the context of hierarchical tiling, where multiple levels of tiling are used, a good choice of rise can lead to less idle time and better performance. While idle time is not the only cost that should be considered in evaluating a tiling strategy, current architectural trends (of deeper memory hierarchies and multiple levels of parallelism) suggest it has increasing importance.

关键词： parallel processing systems

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PPDP'06 - proceedings of the Eight ACM SIGPLAN symposium on principles and practice of Declarative programming

PPDP'06 - Proceedings of the Eight ACM SIGPLAN Symposium on ...

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PPDP'06 - 8th ACM SIGPLAN symposium on principles and practice of Declarative programming

ISBN: (纸本)1595933883

the proceedings contain 24 papers. the topics discussed include: typed polyadic pi-calculus in bigraphs;combining Fuzzy logic and behavioral similarity for non-strict program validation;type oriented construction of web user interfaces;an abductive framework for A-priori verification of web services;an efficient algorithms for XML type projection;type inference for spreadsheets;polymorphic algebraic data type reconstruction;extracting programs from type class proofs;computing constructor forms with non terminating rewrite programs;open data types and open functions;a historic functional and object-oriented calculus;combining algorithmic debugging and program slicing;practical type inference based on success typings;collection analysis for Horn clause programs;a model type system for multi-level generating extensions with persistent code;a type system equivalent to static single assignment;and poly-controlled partial evaluation.

关键词： Logic programming

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