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10th IEEE International Conference on Industrial and Information Systems (ICIIS)

作者： Wepathana, Y. M. R. D. Anthonys, G. Udugama, L. S. K. Open Univ Sri Lanka Fac Engn Technol Dept Elect & Comp Engn Nugegoda Sri Lanka

ISBN: (纸本)9781479918768

Knowledge of parallel programming is an essential requirement in multicore era. To meet this requirement, teaching parallel programming is important at university level. Further, students should have an exposure to different parallel architectures and programming models as well. In order to achieve this objective, it is appropriate to use an integrated system having different parallel architectures and supporting programming languages. Though it is difficult to find a system as stated above, Multi Core Students Experimental Processor (MCSEP) designed on the base of Students Experimental Processor provides an opportunity to develop such system. The MCSEP can be configured to one of the five architectures: SISD, SIMD, MIMD, Multiple-SIMD, and Multiple-MIMD. Each architecture can further be configured to one of six Instruction Set Architectures: Memory-Memory, Accumulator, Extended Accumulator, Stack, Register Memory, and Load Store. As there are no programming tools for the MCSEP, a compiler and a simplified programming language, SEPCom has been developed for using all the features of the multicore processor MCSEP. The SEPCom is a Java like programming language with parallel programming features. The test results show that SEPCom performs well in all architectures available in the MCSEP. Therefore SEPCom can be used for writing parallel programs for different parallel architectures. Consequently, students can develop appropriate programs to do their experiments, and moreover to analyze and measure performances in different parallel architectures. Further, students can also use it as a case study for learning compiler design.

关键词： compiler design multicore programming MIMD SIMD SISD teaching parallel programming

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Reo: A Dataflow Inspired Language for multicore 3

Reo: A Dataflow Inspired Language for Multicore

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3rd Workshop on Data-Flow Execution Models for Extreme Scale Computing (DFM)

作者： Jongmans, Sung-Shik T. Q. Halle, Sean Arbab, Farhad Formal Methods Cent Wiskunde & Informat Amsterdam Netherlands

ISBN: (纸本)9781479952472

The Reo language has been well documented to address difficulties in parallel programming. It separates interaction protocol from computation code, which allows separate development, reuse, and formal proofs about the protocol correctness. Modules of computation can be composed by externally defining a protocol, without concern for their internal details. Achieving acceptable performance for code generated from Reo specifications has been a major challenge. In this paper, we address this with a combination of implementing the circuit splitting optimization and using the proto-runtime approach as a base platform for the runtime system of the Reo language. Our results show that the overhead when running Reo is so low that the performance of a k-tuple benchmark protocol compiled from its Reo specification is now up to six times faster than a straightforward hand-written thread implementation and nearly equal to a carefully optimized thread implementation of the same protocol.

关键词： Reo coordination language multicore programming proto-runtime approach performance

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Variation aware cache partitioning for multithreaded programs 14

Variation aware cache partitioning for multithreaded program...

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51st Annual Design Automation Conference, DAC 2014

作者： Kozhikkottu, Vivek Pan, Abhisek Pai, Vijay Dey, Sujit Raghunathan, Anand School of Electrical and Computer Engineering Purdue University United States School of Electrical and Computer Engineering UC San Diego United States

ISBN: (纸本)9781479930173

Multithreaded programs are commonly written and optimized for homogeneous multi-core processors assuming equal perfor-mance from all the cores. This assumption greatly simplifies the partitioning and balancing of an application's workload across threads;however, it no longer holds when the frequen-cies of the cores differ due to within-die variations, leading to a degradation in performance. We observe that, in ad-dition to the frequency of the core that it executes on, the performance of a thread is also dependent on the share of shared system resources, such as last-level cache, that it re-ceives. We propose variation-aware cache partitioning as an approach to redress the variation-induced imbalance in the ex-ecution times of threads, thereby improving the performance of multi-threaded programs. We discuss the challenges involved in realizing our proposal, including synchronization (e.g., bar-riers) across threads, which results in faster threads being lim-ited by slower threads, the complex and non-linear relationship between a thread's performance and the cache capacity allo-cated to it, and the fact that different program phases, can re-spond quite differently to varying cache capacity. We propose a runtime scheme to perform spatio-temporal cache partitioning while considering both chip characteristics (frequency varia-tions) and program characteristics. We evaluate the proposed technique by applying it to an ensemble of variation-impacted multi-cores executing multi-threaded programs from the PAR-SEC and SPEC-OMP suites, and demonstrate that it results in an average performance improvement of 15% by mitigating the impact of frequency variations. Copyright 2014 ACM.

关键词： multicore programming

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Constraint functional multicore programming

Constraint functional multicore programming

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39th Jahrestagung der Gesellschaft fur Informatik e.V. (GI): Im Focus das Leben, INFORMATIK 2009

作者： Hofstedt, Petra Lorenzen, Florian Department of Software Engineering and Theoretical Computer Sciene Technische Universität Berlin Germany

ISBN: (纸本)9783885792482

In this paper we present the concurrent constraint functional programming language CCFL and an abstract machine for the evaluation of CCFL programs in a multicore environment. The source language CCFL is a simple lazy functional language with a polymorphic type system augmented by ask-/tell-constraints and conjunctions to express concurrent coordination patterns. As execution model for CCFL we propose the abstract machine ATAF. ATAF implements a G-machine to evaluate functional expressions and provides facilities to run multiple cooperating processes on a fixed set of CPUs. Processes communicate via a shared constraint store realizing residuation semantics and committed choice. We show a few scaling results for parallel programs obtained with a prototypical implementation of ATAF on a quadcore machine.

关键词： multicore programming

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Parallel astronomical data processing with Python: Recipes for multicore machines

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ASTRONOMY AND COMPUTING 2013年 2卷 1-10页

作者： Singh, Navtej Browne, Lisa-Marie Butler, Ray Natl Univ Ireland Galway Sch Phys Ctr Astron Galway Ireland

High performance computing has been used in various fields of astrophysical research. But most of it is implemented on massively parallel systems (supercomputers) or graphical processing unit clusters. With the advent of multicore processors in the last decade, many serial software codes have been re-implemented in parallel mode to utilize the full potential of these processors. In this paper, we propose parallel processing recipes for multicore machines for astronomical data processing. The target audience is astronomers who use Python as their preferred scripting language and who may be using PyRAF/IRAF for data processing. Three problems of varied complexity were benchmarked on three different types of multicore processors to demonstrate the benefits, in terms of execution time, of parallelizing data processing tasks. The native multiprocessing module available in Python makes it a relatively trivial task to implement the parallel code. We have also compared the three multiprocessing approaches-Pool/Map, Process/Queue and Parallel Python. Our test codes are freely available and can be downloaded from our website. (c) 2013 Elsevier B.V. All rights reserved.

关键词： Astronomical data processing Parallel computing multicore programming Python multiprocessing Parallel Python Deconvolution

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Multi-Core Processor Based Parallel Implementation For Finding Distribution Vectors In Markov Processes

Multi-Core Processor Based Parallel Implementation For Findi...

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Saudi International Electronics, Communications and Photonics Conference (SIECPC)

作者： Ismail, Muhammad Ali NED Univ Engn & Technol Dept Comp & Informat Syst Engn Karachi Pakistan

ISBN: (纸本)9781467361958;9781467361965

Stochastic processes can be best modeled using Markov processes and these are being used to describe many real time applications. Determining of a distribution / state vector for a Markov process efficiently and swiftly is always be a challenging task. Specially for a high order state and / or for a process having very large number of states. This paper deals in a parallel implementation of finding distribution vectors of a Markov process using repeated multiplications method on multi-core processors. This is done using newly developed parallel programming model for multi-core processors, The (SPCPM)-P-3 at NED University. The results obtained show that the proposed parallel implementation has greater performance and enhanced speedup over the many other serial and parallel implementations for the same process. Besides the implementation found more scalable and easily adoptable for higher number of cores.

关键词： Stochastic Process Markov Process Parallel programming multicore processors multicore programming

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Detection of Probabilistic Dangling References in Multi-core Programs Using Proof-Supported Tools

Detection of Probabilistic Dangling References in Multi-core...

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13th International Conference on Computational Science and Its Applications (ICCSA)

作者： El-Zawawy, Mohamed A. Al Imam Mohammad Ibn Saud Islamic Univ IMSIU Coll Comp & Informat Sci Riyadh Saudi Arabia

ISBN: (纸本)9783642396403

This paper presents a new technique for detection of probabilistic dangling references in multi-core programs. The technique has the form of a simply structured type system and provides a suitable framework for proof-carrying code applications like mobile code applications that have limited resources. The type derivation of each individual analysis serves as a proof for the correctness of the analysis. The type system is designed to analyze parallel programs with structured concurrent constructs: fork-join constructs, conditionally spawned cores, and parallel loops. For a given program S, a probabilistic threshold p(ms), and a probabilistic reference analysis for S, if S is well-typed in our proposed type system then all computational paths with probabilities greater than or equal to pms will contain no dangling pointers at run time. The soundness of the presented type system is proved in this paper with respect to a probabilistic operational semantics to our model language.

关键词： multicore programming

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Bringing safe, dynamic parallel programming to the spark verifiable subset of ada

Bringing safe, dynamic parallel programming to the spark ver...

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2013 ACM SIGAda Annual International Conference on High Integrity Language Technology, HILT 2013

作者： Taft, S. Tucker AdaCore 24 Muzzey Street Lexington MA 02421 United States

ISBN: (纸本)9781450324670

SPARK is a verifiable subset of Ada which has been in use for over 20 years for developing the most critical parts of complex real-time applications [1][2]. A restricted subset of the Ada tasking model is included in the newer versions of SPARK ("RavenSPARK"), but this is a very static model, with a fixed number of tasks and minimal task interaction [3]. In this presentation we will describe an extension of SPARK to support safe highly parallel programming, targeted at the growing number of multicore and manycore processors appearing on the market today. © 2013 ACM.

关键词： multicore programming

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Dynamic selection of speculative paths in two-path limited speculation method

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International Journal of Computers and Applications 2013年第2期35卷 86-95页

作者： Jutori, Hiroyoshi Ootsu, Kanemitsu Yokota, Takashi Baba, Takanobu Graduate School of Engineering Utsunomiya University Japan

Speculative multithreading is one of the most promising methods for speeding up the execution of programs in multicore systems. Each loop has numerous possible execution paths;however, in many cases, only a few of them are executed frequently. We focus on a two-path limited speculation method, which speculates on only the two most frequently executed paths based on path-profiling results of the whole program execution using path-profiling. To maximize the performance of the method, this paper discusses "phased behaviour" in program execution. This paper firstly shows actual behaviours in program execution in terms of execution paths. Then, we introduce practical methods of dynamic selection of speculation paths. Preliminary results show that, realistically, the optimal dynamic method increases the speed by 1.8 times at maximum and also that the practical dynamic method can increase the speculation success ratio by up to 30% compared with the static method.

关键词： multicore programming

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Accelerating analysis of void space in porous materials on multicore and GPU platforms

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2012年第4期26卷 347-357页

作者： Martin, Richard L. Prabhat Donofrio, David D. Sethian, James A. Haranczyk, Maciej Univ Calif Berkeley Lawrence Berkeley Natl Lab Computat Res Div Berkeley CA 94720 USA Univ Calif Berkeley Dept Math Berkeley CA 94720 USA

Developing computational tools that enable discovery of new materials for energy-related applications is a challenge. Crystalline porous materials are a promising class of materials that can be used for oil refinement, hydrogen or methane storage as well as carbon dioxide capture. Selecting optimal materials for these important applications requires analysis and screening of millions of potential candidates. Recently, we proposed an automatic approach based on the Fast Marching Method (FMM) for performing analysis of void space inside materials, a critical step preceding expensive molecular dynamics simulations. This breakthrough enables unsupervised, high-throughput characterization of large material databases. The algorithm has three steps: (1) calculation of the cost-grid which represents the structure and encodes the occupiable positions within the void space;(2) using FMM to segment out patches of the void space in the grid of (1), and find how they are connected to form either periodic channels or inaccessible pockets;and (3) generating blocking spheres that encapsulate the discovered inaccessible pockets and are used in proceeding molecular simulations. In this work, we expand upon our original approach through (A) replacement of the FMM-based approach with a more computationally efficient flood fill algorithm;and (B) parallelization of all steps in the algorithm, including a GPU implementation of the most computationally expensive step, the cost-grid generation. We report the acceleration achievable in each step and in the complete application, and discuss the implications for high-throughput material screening.

关键词： code optimization general purpose computation on GPUs multicore programming porous materials screening zeolites

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