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检索条件"任意字段=Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

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Multi-Core On-The-Fly SCC Decomposition 16

Multi-Core On-The-Fly SCC Decomposition

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21st acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Bloemen, Vincent Laarman, Alfons van de Pol, Jaco Univ Twente Formal Methods & Tools POB 217 NL-7500 AE Enschede Netherlands Vienna Univ Technol FORSYTE Vienna Austria

ISBN: (纸本)9781450340922

The main advantages of Tarjan's strongly connected component (SCC) algorithm are its linear time complexity and ability to return SCCs on-the-fly, while traversing or even generating the graph. Until now, most parallel SCC algorithms sacrifice both: they run in quadratic worst-case time and/or require the full graph in advance. The current paper presents a novel parallel, on-the-fly SCC algorithm. It preserves the linear-time property by letting workers explore the graph randomly while carefully communicating partially completed SCCs. We prove that this strategy is correct. For efficiently communicating partial SCCs, we develop a concurrent, iterable disjoint set structure (combining the union-find data structure with a cyclic list). We demonstrate scalability on a 64-core machine using 75 real-world graphs (from model checking and explicit data graphs), synthetic graphs (combinations of trees, cycles and linear graphs), and random graphs. Previous work did not show speedups for graphs containing a large SCC. We observe that our parallel algorithm is typically 10-30x faster compared to Tarjan's algorithm for graphs containing a large SCC. Comparable performance (with respect to the current state-of-the-art) is obtained for graphs containing many small SCCs.

关键词： strongly connected components SCC algorithm graph digraph parallel multi-core union-find depth-first search

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parallel-program transformation using a metalanguage 91

Parallel-program transformation using a metalanguage

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3rd acm sigplan symposium on principles and practice of parallel programming, PPOPP 1991

作者： Allan Yang, J. Choo, Young-Ii Department of Computer Science Yale University New HavenCT06520-2158 United States

ISBN: (纸本)0897913906

Thk paper describes how program transformation using a rnetalanguage can be an effective methodology for developim~ gcorrect and efficient parallel programs. As an example, a class of different parallel matrix multiplication programs are derived. Starting from a four-line, intuitive, easy-Toverify, though inefficient program, more sophisticated and eilicient programs are derived. All the transformation steps preserve the semantics of the initial program so that the transformation process is a verification of the equivalence among all the derived programs. The metalanguage provides a simple, flexible, extensible, and formal framework for expressing transformational schemes. It also automates tlhe cumbersome and error-prone part of the program transformation. © 1991 Association for Computing Machinery. All Rights Reserved.

关键词： parallel programming

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From Non-determinism to Goroutines: A Fair Implementation of Curry in Go 2021

From Non-determinism to Goroutines: A Fair Implementation of...

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23rd International symposium on principles and practice of Declarative programming (PPDP)

作者： Boehm, Jonas Hanus, Michael Teegen, Finn CAU Kiel Inst Informat Kiel Germany

ISBN: (纸本)9781450386890

The declarative programming language Curry amalgamates demand-driven evaluation from functional programming with non-determinism from logic programming. In contrast to Prolog, the search strategy for non-deterministic computations is not fixed so that complete or parallel strategies are reasonable for Curry. In particular, a desirable option is a fair strategy which frees the programmer from considering the influence of the search strategy to the success of a computation. In this paper we describe an implementation with this property. Based on recent developments on operational models for functional logic programming, we present a new implementation which transforms Curry programs in several transformation steps into Go programs. By exploiting lightweight threads in the form of goroutines, we obtain a complete and fair implementation which automatically uses multi-processing to speed up non-deterministic computations. This has the effect that, in some cases, non-deterministic algorithms are more efficiently evaluated than deterministic ones.

关键词： Declarative programming implementation parallelism

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RACE FRONTIER: Reproducing data parallel-program debugging 3

RACE FRONTIER: Reproducing data parallel-program debugging

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3rd acm sigplan symposium on principles and practice of parallel programming, PPOPP 1991

作者： Choi, Jong-Deok Mint, Sang Lyul I.B .M. T.J. Watson Research Center P.O. Box 704 Yorktown HeightsNY10598 United States Dept. of Computer Engineering Pusan National University Pusan609-735 Korea Republic of

ISBN: (纸本)0897913906

A data race is a typical case of unintended nondeterminism, which occurs when two or more processes concurrently access the same memory location, with at least one of the accesses being a write access. This paper presents a mechanism to debug data races in the execution of parallel programs. A RACE FRONTIER is a set of execution events, one event for each process, whose execution histories, including data races preceding them, can be reproduced. Data races can be debugged by first identifying a RACE FRONTIER and then reproducing all the events, including data-race events? up to the RACE FRONTIER. Reproducing and debugging data races up to a RACE FRONTIER will eventually result in an execution instance without any data races. This paper describes how to identify a RACE FRONTIER and how to reproduce the execution history of data races up to the RACE FRONTIER. © 1991 Association for Computing Machinery. All Rights Reserved.

关键词： Program debugging

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An open environment for building parallel programming systems

An open environment for building parallel programming system...

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1988 acm/sigplan Conference on parallel programming: Experience with Applications, Languages and Systems, PPEALS 1988

作者： Bershad, Brian N. Lazowska, Edward D. Levy, Henry M. Wagner, David B. Department of Computer Science University of Washington SeattleWA98195 United States

ISBN: (纸本)0897912764

PRESTO is a set of tools for building parallel programming systems on shared-memory multiprocessors. PRESTO'S goal is to provide a framework within which one can easily build efficient support for any of a wide variety of "models" of parallel programming. PRESTO is designed for easy modification and extension, not only at the level of the primitives and structures made available for the application programmer's use, but also at the level of the run-time kernel that supports parallel applications. PRESTO is implemented in me object-oriented language C++ on a Sequent Balance 21000 and has been used in a number of applications that are described in this paper. © 1988 acm.

关键词： parallel programming

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parallel Suffix Array and Least Common Prefix for the GPU 13

Parallel Suffix Array and Least Common Prefix for the GPU

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

作者： Deo, Mrinal Keely, Sean Adv Micro Devices Inc Sunnyvale CA 94088 USA Univ Texas Austin Austin TX 78712 USA

ISBN: (纸本)9781450319225

Suffix Array (SA) is a data structure formed by sorting the suffixes of a string into lexicographic order. SAs have been used in a variety of applications, most notably in pattern matching and Burrows-Wheeler Transform (BWT) based lossless data compression. SAs have also become the data structure of choice for many, if not all, string processing problems to which suffix tree methodology is applicable. Over the last two decades researchers have proposed many suffix array construction algorithm (SACAs). We do a systematic study of the main classes of SACAs with the intent of mapping them onto a data parallel architecture like the GPU. We conclude that skew algorithm [12], a linear time recursive algorithm, is the best candidate for GPUs as all its phases can be efficiently mapped to a data parallel hardware. Our OpenCL implementation of skew algorithm achieves a throughput of up to 25 MStrings/sec and a speedup of up to 34x and 5.8x over a single threaded CPU implementation using a discrete GPU and APU respectively. We also compare our OpenCL implementation against the fastest known CPU implementation based on induced copy in g and achieve a speedup of up to 3.7x. Using SA we construct BWT on GPU and achieve a speedup of 11x over the fastest known BWT on GPU. Suffix arrays are often augmented with the longest common prefix (LCP) information. We design a novel high-performance parallel algorithm for computing LCP on the GPU. Our GPU implementation of LCP achieves a speedup of up to 25x and 4.3x on discrete GPU and APU respectively.

关键词： Algorithms Performance Suffix Array Suffix Tree BWT Longest Common Prefix OpenCL GPU Prefix Sum Accelerated Processing Unit (APU)

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StreamScan: Fast Scan Algorithms for GPUs without Global Barrier Synchronization 13

StreamScan: Fast Scan Algorithms for GPUs without Global Bar...

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

作者： Yan, Shengen Long, Guoping Zhang, Yunquan Chinese Acad Sci Inst Software Lab Parallel Software & Computat Sci Beijing 100864 Peoples R China Chinese Acad Sci State Key Lab Comp Sci Beijing 100864 Peoples R China Chinese Acad Sci Grad Univ Beijing 100864 Peoples R China

ISBN: (纸本)9781450319225

Scan (also known as prefix sum) is a very useful primitive for various important parallel algorithms, such as sort, BFS, SpMV, compaction and so on. Current state of the art of GPU based scan implementation consists of three consecutive Reduce-Scan-Scan phases. This approach requires at least two global barriers and 3N (N is the problem size) global memory accesses. In this paper we propose StreamScan, a novel approach to implement scan on GPUs with only one computation phase. The main idea is to restrict synchronization to only adjacent workgroups, and thereby eliminating global barrier synchronization completely. The new approach requires only 2N global memory accesses and just one kernel invocation. On top of this we propose two important optimizations to further boost performance speedups, namely thread grouping to eliminate unnecessary local barriers, and register optimization to expand the on chip problem size. We designed an auto-tuning framework to search the parameter space automatically to generate highly optimized codes for both AMD and Nvidia GPUs. We implemented our technique with OpenCL. Compared with previous fast scan implementations, experimental results not only show promising performance speedups, but also reveal dramatic different optimization tradeoffs between Nvidia and AMD GPU platforms.

关键词： Scan prefix-sum OpenCL CUDA GPU parallel algorithms

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Scalable reader-writer synchronization for shared-memory multiprocessors 91

Scalable reader-writer synchronization for shared-memory mul...

引用

3rd acm sigplan symposium on principles and practice of parallel programming, PPOPP 1991

作者： Mellor-Crummey, John M. Scottt, Michael L. Computer Science Department University of Rochester RochesterNY14627 United States Center for Research on Parallel Computation Rice University P.O. Box 1892 HoustonTX77251-1892 United States

ISBN: (纸本)0897913906

Reader-writer synchronization relaxes the constraints of mutual exclusion to permit more than one process to inspect a shared object concurrently, as long as none of them changes its value. On uniprocessors, mutual exclusion and readerwriter locks are typically designed to de-schedule blocked processes;however, on shared-memory multiprocessors it is often advantageous to have processes busy wait. Unfortunately, implementations of busy-wait locks on sharedmemory multiprocessors typically cause memory and network contention that degrades performance. Several researchers have shown how to implement scalable mutual exclusion locks that exploit locality in the memory hierarchies of shared-memory multiprocessors to eliminate contention for memory and for the processor-memory interconnect. In this paper we present reader-writer locks that similarly exploit locality to achieve scalability, with variants for reader preference, writer preference, and reader-writer fairness. Performance results on a BBN TC2000 multiprocessor demonstrate that our algorithms provide low latency and excellent scalability. © 1991 Association for Computing Machinery. All Rights Reserved.

关键词： Locks (fasteners)

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Ligra: A Lightweight Graph Processing Framework for Shared Memory 13

Ligra: A Lightweight Graph Processing Framework for Shared M...

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

作者： Shun, Julian Blelloch, Guy E. Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450319225

There has been significant recent interest in parallel frameworks for processing graphs due to their applicability in studying social networks, the Web graph, networks in biology, and unstructured meshes in scientific simulation. Due to the desire to process large graphs, these systems have emphasized the ability to run on distributed memory machines. Today, however, a single multicore server can support more than a terabyte of memory, which can fit graphs with tens or even hundreds of billions of edges. Furthermore, for graph algorithms, shared-memory multicores are generally significantly more efficient on a per core, per dollar, and per joule basis than distributed memory systems, and shared-memory algorithms tend to be simpler than their distributed counterparts. In this paper, we present a lightweight graph processing framework that is specific for shared-memory parallel/multicore machines, which makes graph traversal algorithms easy to write. The framework has two very simple routines, one for mapping over edges and one for mapping over vertices. Our routines can be applied to any subset of the vertices, which makes the framework useful for many graph traversal algorithms that operate on subsets of the vertices. Based on recent ideas used in a very fast algorithm for breadth-first search (BFS), our routines automatically adapt to the density of vertex sets. We implement several algorithms in this framework, including BFS, graph radii estimation, graph connectivity, betweenness centrality, PageRank and single-source shortest paths. Our algorithms expressed using this framework are very simple and concise, and perform almost as well as highly optimized code. Furthermore, they get good speedups on a 40-core machine and are significantly more efficient than previously reported results using graph frameworks on machines with many more cores.

关键词： Algorithms Performance Shared Memory Graph Algorithms parallel programming

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Ownership Passing: Efficient Distributed Memory programming on Multi-core Systems 13

Ownership Passing: Efficient Distributed Memory Programming ...

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

作者： Friedley, Andrew Hoefler, Torsten Bronevetsky, Greg Lumsdaine, Andrew Ma, Ching-Chen Indiana Univ Bloomington IN 47405 USA ETH Zurich Switzerland Lawrence Livermore Natl Lab Livermore CA USA Rose Hulman Inst Technol Terre Haute IN 47803 USA

ISBN: (纸本)9781450319225

The number of cores in multi- and many-core high-performance processors is steadily increasing. MPI, the de-facto standard for programming high-performance computing systems offers a distributed memory programming model. MPI's semantics force a copy from one process' send buffer to another process' receive buffer. This makes it difficult to achieve the same performance on modern hardware than shared memory programs which are arguably harder to maintain and debug. We propose generalizing MPI's communication model to include ownership passing, which make it possible to fully leverage the shared memory hardware of multi-and many-core CPUs to stream communicated data concurrently with the receiver's computations on it. The benefits and simplicity of message passing are retained by extending MPI with calls to send (pass) ownership of memory regions, instead of their contents, between processes. Ownership passing is achieved with a hybrid MPI implementation that runs MPI processes as threads and is mostly transparent to the user. We propose an API and a static analysis technique to transform legacy MPI codes automatically and transparently to the programmer, demonstrating that this scheme is easy to use in practice. Using the ownership passing technique, we see up to 51% communication speedups over a standard message passing implementation on state-of-the art multicore systems. Our analysis and interface will lay the groundwork for future development of MPI-aware optimizing compilers and multi-core specific optimizations, which will be key for success in current and next-generation computing platforms.

关键词： Ownership Passing Distributed Memory Shared Memory Message Passing Multi-core

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