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IEEE General Meeting Power& Energy Society

作者： Tiago Norbiato dos Santos Andre Diniz Carnen Tancredo Borges DEA CEPEL - Brazilian Electric Energy Research Center Universidade Federal do Rio de Janeiro Rio de Janeiro RJ BR

ISBN: (纸本)9781538622131;9781538622124

Several optimization strategies are suitable for parallel processing, such as mathematical-programming based decomposition strategies, like Lagrangian Relaxation and twostage Benders decomposition, and evolutionary programminglike algorithms. In such cases, most subproblems can be solved independently by different processors. However, parallel processing is not suitable for some problems solved by nested Benders decomposition, due to the hierarchy between subproblems related to different time steps. In particular, for the deterministic case, parallel programming has been restricted to thread processing in lower-level machine computation and optimization solver codes. This paper proposes a new nested Benders decomposition strategy that is suitable for parallel processing, where time-coupled stages are solved simultaneously and an alternative procedure is employed to share initial conditions for the next stages as well as Benders cuts for the previous stages. The methodology is applied to the deterministic short term hydrothermal scheduling problem for the real large-scale Brazilian system, where the advantages of the proposed approach become more evident. In order to show the applicability of the method in low-budget and small parallel environments, the case study was processed with up to 24 process on multi-core computers.

关键词： Optimization Scheduling parallel programming Instruction sets Processor scheduling

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Analyzing and Predicting Concurrency Bugs in Open Source Systems

Analyzing and Predicting Concurrency Bugs in Open Source Sys...

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International Joint Conference on Neural Networks

作者： Paolo Ciancarini Francesco Poggi Davide Rossi Alberto Sillitti University of Bologna Italy Innopolis University Russian Federation

ISBN: (纸本)9781509061839

Background Software systems are relying more and more on multi-core hardware requiring a parallel approach to address the problems and improve performances. Unfortunately, parallel development is error prone and many developers are not very experienced with this paradigm also because identifying, reproducing, and fixing bugs is often difficult. Objective The main goal of this paper is the identification of an approach able to: (i) identify solved concurrency-related bugs to characterize them and help retrospective activities;(ii) identify concurrency-related bugs as soon as they are entered in the bug management system to support bug triage phase and allocate them to more experienced developers. Approach To this end, the paper analyzes bugs related to concurrency looking at their specific characteristics using different machine learning methods to automatically distinguish them from other kinds of bugs based on the data available in the issue tracking systems and in the code repositories. Results The overall best models we developed for Apache HTTP Server and MariaDB have a precision of 0.985 and 0.814 and a recall of 0.876 and 0.629 when considering linked bugs (bug reports information in bug repository and the corresponding fix in the version control system) and a precision of 0.978 and 0.779 and a recall of 0.889 and 0.569 when considering only the information from bug reports. Conclusions Such results allow the development of an automated system able to classify such bugs and support developers in the bug triage process.

关键词： Computer bugs Software Predictive models Concurrent computing Measurement Servers Control systems bugs Bugs Servers control systems Prediction models parallel programming computer software open source recall Mental Recall

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Executing dynamic data-graph computations deterministically using chromatic scheduling

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ACM Transactions on parallel Computing 2016年第1期3卷 1–31页

作者： Kaler, Tim Hasenplaugh, William Schardl, Tao B. Leiserson, Charles E. MIT CSAIL 32 Vassar Street CambridgeMA02139 United States

A data-graph computation-popularized by such programming systems as Galois, Pregel, GraphLab, PowerGraph, and GraphChi-is an algorithm that performs local updates on the vertices of a graph. During each round of a data-graph computation, an update function atomically modifies the data associated with a vertex as a function of the vertex's prior data and that of adjacent vertices. A dynamic data-graph computation updates only an active subset of the vertices during a round, and those updates determine the set of active vertices for the next round. This article introduces PRISM, a chromatic-scheduling algorithm for executing dynamic data-graph computations. PRISM uses a vertex coloring of the graph to coordinate updates performed in a round, precluding the need for mutual-exclusion locks or other nondeterministic data synchronization. A multibag data structure is used by PRISM to maintain a dynamic set of active vertices as an unordered set partitioned by color. We analyze PRISM using work-span analysis. Let G = (V, E) be a degree-ϵ graph colored with ? colors, and suppose that Q ? V is the set of active vertices in a round. Define size(Q) = |Q| +ϵv?Q deg(v), which is proportional to the space required to store the vertices of Q using a sparse-graph layout. We show that a P-processor execution of PRISM performs updates in Q using O(?(lg(Q/?) + lgϵ) + lg P) span and (size(Q) + P) work. These theoretical guarantees are matched by good empirical performance. To isolate the effect of the scheduling algorithm on performance, we modified GraphLab to incorporate PRISM and studied seven application benchmarks on a 12-core multicore machine. PRISM executes the benchmarks 1.2 to 2.1 times faster than GraphLab's nondeterministic lock-based scheduler while providing deterministic behavior. This article also presents PRISM-R, a variation of PRISM that executes dynamic data-graph computations deterministically even when updates modify global variables with associative operations. P

关键词： parallel programming

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Virtual orbital many-body expansions: A possible route towards the full configuration interaction limit

arXiv

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arXiv 2017年

作者： Eriksen, Janus J. Lipparini, Filippo Gauss, Jürgen Institut für Physikalische Chemie Johannes Gutenberg-Universität Mainz MainzD-55128 Germany Dipartimento di Chimica e Chimica Industriale Università di Pisa PisaI-56124 Italy

In the present letter, it is demonstrated how full configuration interaction (FCI) results in extended basis sets may be obtained to within sub-kJ/mol accuracy by de-composing the energy in terms of many-body expansions in the virtual orbitals of the molecular system at hand. This extension of the FCI application range lends itself to two unique features of the current approach, namely that the total energy calculation can be performed entirely within considerably reduced orbital subspaces and may be so by means of embarrassingly parallel programming. Facilitated by a rigorous and methodical screening protocol and further aided by expansion points different from the Hartree-Fock solution, all-electron numerical results are reported for H2O in polarized core-valence basis sets ranging from double-ζ (10 e, 28 o) to quadruple-ζ (10 e, 144 o) quality. Copyright © 2017, The Authors. All rights reserved.

关键词： parallel programming

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EPIC: A framework to exploit parallelism in irregular codes

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2017年第2期29卷

作者： Neves, Diogo Telmo Univ Minho Dept Informat Campus Gualtar Braga Portugal

To harness the performance potential of current multicore processors, a multitude of algorithms, frameworks and libraries have been developed. Nevertheless, it is still extremely difficult to take advantage of the full potential of multicore processors. Moreover, when using third-party tools and/or in the presence of asymmetric sets of tasks, this problem would only aggravate. The EPIC framework was developed to ease the exploitation of task parallelism in irregular applications that use third-party tools and/or generate asymmetric sets of tasks. It is based on a software design and implements two algorithms that, together, allow, in a seamlessly way, the efficient exploitation of coarse-grained parallelism, fine-grained parallelism, and the combination of both of these types. Thus, it becomes possible to make a better and transparent usage of the performance potential of current multicore processors on shared-memory systems. In this paper, we present two refinements to the EPIC framework: one that refines the software design of the EPIC framework and another that refines the scheduling algorithm of the EPIC framework. Together, these refinements allow to cope with a special class of sets of tasks: sets of tasks where asymmetry is insignificant or can be neglected. Thus, these refinements broaden the applicability of the EPIC framework to a large class of irregular applications where task parallelism can be exploited. To assess the feasibility and the benefit of using this new version of the EPIC framework to exploit task parallelism, we used four real-world irregular applicationsthree from phylogenetics and another from astrophysicsand several input data sets with different characteristics. Our studies show groundbreaking results in terms of the achieved speedups and that scalability is not impaired, even when using third-party tools and/or in the presence of (a)symmetric sets of tasks. Copyright (c) 2016 John Wiley & Sons, Ltd.

关键词： framework parallel programming software refinement irregular applications phylogenetics n-body problem

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A FRAMEWORK FOR UNIT TESTING WITH COARRAY FORTRAN 17

A FRAMEWORK FOR UNIT TESTING WITH COARRAY FORTRAN

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Simulation Multiconference

作者： Ambra Abdullahi Hassan Valeria Cardellini Salvatore Filippone University of Rome Tor Vergata Cranfield University

ISBN: (纸本)9781510838222

parallelism is a ubiquitous feature of modern computing architectures; indeed, we might even say that serial code is now automatically legacy code. Writing parallel code poses significant challenges to programs, and is often error-prone. Partitioned Global Address Space (PGAS) languages, such as Coarray Fortran (CAF), represent a promising development direction in the quest for a trade-off between simplicity and performance. CAF is a parallel programming model that allows a smooth migration from serial to parallel code. However, despite CAF simplicity, refactoring serial code and migrating it to parallel versions is still error-prone, especially in complex softwares. The combination of unit testing, which drastically reduces defect injection, and CAF is therefore a very appealing prospect; however, it requires appropriate tools to realize its potential. In this paper, we present the first CAF-compatible framework for unit tests, developed as an extension to the parallel Fortran Unit Test framework (pFUnit).

关键词： Coarray Fortran Test-Driven Development Unit tests PFUnit Refactoring Reconstructions Computer programming Languages Serial Publications Codes Unit Device Component Synclitism parallel programming parallel Lines

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Exploiting Decoupled OpenCL Work-Items with Data Dependencies on FPGAs: A Case Study

Exploiting Decoupled OpenCL Work-Items with Data Dependencie...

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IEEE International Symposium on parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Javier Alejandro Varela Norbert Wehn Qian Liang Songyin Tang Microelectronic Systems Design Research Group University of Kaiserslautern Germany BearingPoint GmbH Germany

In the field of high performance heterogeneous computing systems, field programmable gate arrays (FPGAs) have shown great advantages in terms of acceleration and energy efficiency. And with the inclusion of the OpenCL framework for parallel programming, the design complexity has been greatly reduced. However, the parallel implementation of applications containing data-dependent branches usually experiences an important loss in performance, which affects all platforms alike. This data dependency leads the execution of parallel threads, also called work-items in OpenCL, to diverge. Whereas fixed architectures like CPU, GPU and Xeon Phi cannot efficiently cope with this divergent execution, the flexibility offered by FPGAs in terms of architecture can be exploited to tackle this problem. In this work, we present a new approach for FPGA implementations that decouples the parallel OpenCL work-items, avoiding the interference of data-dependent branches between them. We also demonstrate the necessary workarounds to obtain the maximum performance in a pipelined design, when unpredictable for-loop exit conditions are caused by the data dependency. Furthermore, we show how to efficiently interleave computation with transfers to device global memory in each work-item. This approach is then evaluated with a real-life case study from Finance, with four different configurations implemented on FPGA with Xilinx SDAccel, and compared to the optimized implementation on CPU, GPU, and Xeon Phi. Our results show that FPGAs can deliver up to 5.5x speedup, whereas the system-level energy efficiency increases between 2x and 9.5x in all cases.

关键词： Field programmable gate arrays Computer architecture Hardware Graphics processing units Kernel parallel programming Runtime

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Assessing and Improving the Performance and Scalability of an Iterative Algorithm for Hadoop

Assessing and Improving the Performance and Scalability of a...

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Computing Conference

作者： Joao Paulo Barbosa Nascimento Daniel Oliveira Capanema Adriano Cesar Machado Pereira Dept. of Computing CEFET-MG Brazil Dept. of Computer Science (DCC) UFMG Brazil

ISBN: (纸本)9781509054442

Large volumes of data are generated and collected nowadays through sensors, devices, social networks, among others. The ability to handle large datasets has become an important expertise for the success of many organizations around the world, demanding increasingly parallel and distributed processing. parallel computing, based on multicore architecture, re-emerged in recent years as a solution for this challenge. To help developers to design parallel programs, there exists several parallel and distributed tools (frameworks), such as Apache Hadoop and Spark. These frameworks provide a plenty of configuration parameters (e.g., Hadoop has more than 200) and to configure all of them optimally is a non-trivial task. This work investigates the influence of various parameters on the performance of Apache Hadoop when process HEDA, an iterative algorithm that calculate metrics of centrality in large graphs. The execution of HEDA in a complex network is extremely important because there are several centrality measures that determine the importance of a node in the graph. The centrality of a node is a key issue in the analysis of complex networks, especially on social networks. It was observed that in some cases the improvement in execution time reached almost 80% by applying the proposed values in the selected parameters. Moreover, it was possible to increase CPU consumption four times and to achieve a Speedup of 92% of linearity. The work also describes the steps that were followed to perform the experiments, which can help other researchers to conduct new experiments.

关键词： Hadoop Graph Parameters Iterative Algorithm parallel programming

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Performance comparison of various STM concurrency control protocols using synchrobench

arXiv

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arXiv 2017年

作者： Singh, Ajay Peri, Sathya Monika, G. Kumari, Anila Dept. of Computer Science and Engineering IIT Hyderabad Hyderabad India

Writing concurrent programs for shared memory multiprocessor systems is a nightmare. This hinders users to exploit the full potential of multiprocessors. STM (Software Transactional Memory) is a promising concurrent programming paradigm which addresses woes of programming for multiprocessor systems. In this paper, we implement BTO (Basic Timestamp Ordering), SGT (Serialization Graph Testing) and MVTO(Multi-Version Time-Stamp Ordering) concurrency control protocols and build an STM(Software Transactional Memory) library to evaluate the performance of these protocols. The deferred write approach is followed to implement the STM. A SET data structure is implemented using the transactions of our STM library. And this transactional SET is used as a test application to evaluate the STM. The performance of the protocols is rigorously compared against the linked-list module of the Synchrobench benchmark. Linked list module implements SET data structure using lazy-list, lock-free list, lock-coupling list and ESTM (Elastic Software Transactional Memory). Our analysis shows that for a number of threads greater than 60 and update rate 70%, BTO takes (17% to 29%) and (6% to 24%) less CPU time per thread when compared against lazy-list and lock-coupling list respectively. MVTO takes (13% to 24%) and (3% to 24%) less CPU time per thread when compared against lazy-list and lock-coupling list respectively. BTO and MVTO have similar per thread CPU time. BTO and MVTO outperform SGT by 9% to 36%. Copyright © 2017, The Authors. All rights reserved.

关键词： parallel programming

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Comparative Performance and Optimization of Chapel in Modern Manycore Architectures

Comparative Performance and Optimization of Chapel in Modern...

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IEEE International Symposium on parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Engin Kayraklioglu Wo Chang Tarek El-Ghazawi Electrical & Computer Engineering Department The George Washington University DC USA

Chapel is an emerging scalable, productive parallel programming language. In this work, we analyze Chapel's performance using The parallel Research Kernels on two different manycore architectures including a state-of-the-art Intel Knights Landing processor. We discuss implementation techniques in Chapel and their relation to the OpenMP implementations of the PRK. We also suggest and prototype several optimizations in different layers of the software stack including the Chapel compiler. In our experiments we observed that base performance of Chapel ranges from 41%-184% that of OpenMP. The optimization techniques we discussed shows performance improvements ranging from 1.4x to 2x in Chapel.

关键词： Optimization Kernel Computer architecture Benchmark testing parallel programming Object oriented modeling

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