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Design of a concentrated torus topology with channel buffers and efficient crossbars in NoCs

Design of a concentrated torus topology with channel buffers...

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2013 ieee 37th annual computer Software and Applications Conference, COMPSAC 2013

作者： Ditomaso, Dominic Morris, Randy Jolley, Evan Sarathy, Ashwini Louri, Ahmed Kodi, Avinash Electrical Engineering and Computer Science Ohio University Athens OH 45701 United States Electrical and Computer Engineering University of Arizona Tucson AZ 85721 United States

ISBN: (纸本)9780769549798

Excess power dissipation along with increased leakage currents in router buffers and crossbars are becoming a major constraint that is affecting the performance of Network-on-Chips (NoCs) architectures. In this paper, we design channel buffers and router crossbars in a concentrated torus topology (CTorus) which is a dual network without the additional area overhead. When compared to other dual networks, CTorus improves saturation throughput by 11-20% for synthetic traffic and improves speedup by 1.78-2.15X for real benchmark traces such as PARSEC and SPEC CPU2006. When the energy-efficient buffer and crossbar organization was inserted into our CTorus topology, we reduced energy dissipation by 32% and area by 53% on average over mesh2X, CMesh2X and FBfly2X. © 2013 ieee.

关键词： Topology

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MapReduce algorithms for GIS polygonal overlay processing

MapReduce algorithms for GIS polygonal overlay processing

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2013 ieee 37th annual computer Software and Applications Conference, COMPSAC 2013

作者： Puri, Satish Agarwal, Dinesh He, Xi Prasad, Sushil K. Department of Computer Science Georgia State University Atlanta 30303 United States

ISBN: (纸本)9780769549798

Polygon overlay is one of the complex operations in computational geometry. It is applied in many fields such as Geographic Information Systems (GIS), computer graphics and VLSI CAD. Sequential algorithms for this problem are in abundance in literature but there is a lack of distributed algorithms especially for MapReduce platform. In GIS, spatial data files tend to be large in size (in GBs) and the underlying overlay computation is highly irregular and compute intensive. the MapReduce paradigm is now standard in industry and academia for processing large-scale data. Motivated by the MapReduce programming model, we revisit the distributed polygon overlay problem and its implementation on MapReduce platform. Our algorithms are geared towards maximizing local processing and minimizing the communication overhead inherent with shuffle and sort phases in MapReduce. We have experimented with two data sets and achieved up to 22x speedup with dataset 1 using 64 CPU cores. © 2013 ieee.

关键词： MapReduce

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Teaching parallel and distributed computing to undergraduate computer science students

Teaching parallel and distributed computing to undergraduate...

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2013 ieee 37th annual computer Software and Applications Conference, COMPSAC 2013

作者： Arroyo, Marcelo Departamento de Computación Universidad Nacional de Río Cuarto Río-Cuarto Argentina

ISBN: (纸本)9780769549798

Parallel and distributed systems programming skills has become a common requirement in the development of modern applications. It is imperative that any updated curriculum in computer science must include these topics not only as advanced (often elective) programming courses. there is a general consensus that parallel programming topics should be spread throughout the undergraduate *** this paper we describe how parallel and distributed computing and, specifically concurrent and parallel programming topics, are being included in the updated computer science curriculum of the degree in computer science at the Río Cuarto National University, Argentina. Also, we cover some suggested approaches for teaching parallel programming topics in a set of core courses to achieve a consistent, increasing and complete training in high performance computing. To achieve these goals, we propose a set of modules which includes basic and advanced high performance computing and some parallel and distributed systems programming topics, to be included in core courses. Finally, we describe the use of existing tools and the development of new high level tools, as parallel patterns, useful for teaching parallel programming which can be used in different courses. the aim of using these tools and techniques is to reduce the gap between sequential and parallel programming. © 2013 ieee.

关键词： Parallel programming

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Briareus: Accelerating python applications with cloud

Briareus: Accelerating python applications with cloud

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2013 ieee 37th annual computer Software and Applications Conference, COMPSAC 2013

作者： Zhu, Zhaomeng Zhang, Gongxuan Zhang, Yongping Guo, Jian Xiong, Naixue School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing Jiangsu 210094 China School of Computer Science Colorado Technical University Colorado Spring CO 80907 United States

ISBN: (纸本)9780769549798

Briareus provides convenient tools to make use of computing resources provided by cloud to accelerate Python applications. In this paper, three techniques are presented. First, some of the functions in a Python program can be migrated to cloud and be evaluated using the hardware and software provided by that cloud platform, while the other parts still running locally. Second, Briareus can automatically parallelize specified loops in a program to accelerate it. And third, specified functions can be called asynchronously after being patched, so that two or more functions can be evaluated simultaneously. By combining these three methods, a Python application can make part of itself to run in a remote cloud platform in parallel. To use Briareus, developers do not need to modify the existing source much, but only need to insert some descriptive comments and invoke a patching function at the beginning. Experiments show that Briareus can significantly speed up the running of programs written by Python, especially for those for scientific and engineering computing. the early beta version of Briareus has been developed for testing and all sources are accessible to public via Github and installable via PyPI. © 2013 ieee.

关键词： Python

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Efficient parallel and distributed algorithms for GIS polygonal overlay processing

Efficient parallel and distributed algorithms for GIS polygo...

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2013 ieee 37th annual computer Software and Applications Conference, COMPSAC 2013

作者： Puri, Satish Prasad, Sushil K. Department of Computer Science Georgia State University Atlanta 30303 GA United States

ISBN: (纸本)9780769549798

Polygon overlay is one of the complex operations in Geographic Information Systems (GIS). In GIS, a typical polygon tends to be large in size often consisting of thousands of vertices. Sequential algorithms for this problem are in abundance in literature and most of the parallel algorithms concentrate on parallelizing edge intersection phase only. Our research aims to develop parallel algorithms to find overlay for two input polygons which can be extended to handle multiple polygons and implement it on General Purpose Graphics Processing Units (GPGPU) which offers massive parallelism at relatively low cost. Moreover, spatial data files tend to be large in size (in GBs) and the underlying overlay computation is highly irregular and compute intensive. MapReduce paradigm is now standard in industry and academia for processing large-scale data. Motivated by MapReduce programming model, we propose to develop and implement scalable distributed algorithms to solve large-scale overlay processing in this dissertation. © 2013 ieee.

关键词： MapReduce

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Issues in communication heterogeneity for message-passing concurrent computing

Issues in communication heterogeneity for message-passing co...

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2013 ieee 37th annual computer Software and Applications Conference, COMPSAC 2013

作者： Slawinski, Jaroslaw Villa, Umberto Passerini, Tiziano Veneziani, Alessandro Sunderam, Vaidy Dept. of Mathematics and Computer Science Emory University Atlanta United States

ISBN: (纸本)9780769549798

Heterogeneity in interconnection network throughput and latency has recently become a major issue for parallel computing applications. With the universal prevalence of multicore processors, large scale clusters and, most critically, cloud platforms, variations in communication characteristics of orders of magnitude are possible within a single execution environment. When applications also exhibit heterogeneity and irregularity in their communication patterns, process placement can make the difference between good and unacceptable performance. We discuss techniques for analyzing and addressing these factors in the context of a computational fluid dynamics application for the study of blood flow, on typical parallel platforms: a local parallel machine, a workstation network, and IaaS cloud-based cluster. Our experiences show problem sizes and platform sizes for which communication variations have significant impact, and suggest methods for process mapping that are likely to alleviate the detrimental effects of communication heterogeneity in different environments. © 2013 ieee.

关键词： Message passing

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Dataset scaling and mapreduce performance

Dataset scaling and mapreduce performance

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2013 ieee 37th annual computer Software and Applications Conference, COMPSAC 2013

作者： Zhang, Fan Sakr, Majd Department of Computer Science Carnegie Mellon University in Qatar Doha Qatar

ISBN: (纸本)9780769549798

Predicting execution behavior of MapReduce applications when scaling the input dataset presents a challenging problem. the difficulty lies in the distributed locations of input data and the distributed, virtualized compute resources that utilize different network substrates. the potential payoff lies in using small datasets and limited test runs to understand how applications will behave with big data. Our research has developed an in-depth understanding of MapReduce application performance and analyzed the impact of scaling input datasets. While we might expect that embarrassingly parallel MapReduce jobs should scale linearly with input dataset size, our results show that execution time sometimes increases nonlinearly. To verify our predictions, we identify a benchmark set of Map-, Shuffle-, and Reduce-intensive applications. Experimental results show that our execution-time analysis distinguishes four typical application behaviors when scaling input datasets. © 2013 ieee.

关键词： MapReduce

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Asynchronous p systems for the maximum independent set and related graph problems

Asynchronous p systems for the maximum independent set and r...

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2013 ieee 37th annual computer Software and Applications Conference, COMPSAC 2013

作者： Tanaka, Kohei Fujiwara, Akihiro Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Fukuoka 820-8502 Japan

ISBN: (纸本)9780769549798

In the present paper, we consider fully asynchronous parallelism in membrane computing, and propose asynchronous P systems for three graph problems, which are the maximum independent set, the minimum vertex cover, and the maximum clique. We first propose an asynchronous P system that solves the maximum independent set for a graph with n nodes, and show that the proposed P system works in O(n2 ·2n) sequential steps or O(n2) parallel steps using O(n2) kinds of objects. We next propose an asynchronous P system that solves the minimum vertex cover and the maximum clique for a graph with n nodes by reduction to the maximum independent set, and show that the proposed P system works in O(n2 ·2n) sequential steps or O(n2) parallel steps using O(n2) kinds of objects. © 2013 ieee.

关键词： Bioinformatics

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Sustained resilience via live process cloning

Sustained resilience via live process cloning

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2013 ieee 37th annual computer Software and Applications Conference, COMPSAC 2013

作者： Rezaei, Arash Mueller, Frank Department of Computer Science North Carolina State University Raleigh NC United States

ISBN: (纸本)9780769549798

More flexible fault tolerance approaches with lower overhead are a must for the next generation of supercomputers that rely on massive numbers of computational elements. this work proposes a reactive method for fault resilience in high-performance computing (HPC) systems based on forward execution instead of rollback to checkpoints. We study the feasibility of combining redundancy with live process cloning to create highly reliable HPC systems. the main motivation is to avoid costly checkpoint restart approaches. We present live process cloning as a mechanism to create a copy of a running process on-the-fly. We show that the reliability of a dual redundant system with live process cloning is as good as a triple redundant system even for very large systems. We also investigate the effect of node failure and the changes in Mean time to Interrupt (MTTI) of the application. this provides a better understanding of the available time to recover from a failure by cloning a healthy replica. © 2013 ieee.

关键词： Cloning

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A compiler analysis to determine useful cache size for energy efficiency

A compiler analysis to determine useful cache size for energ...

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2013 ieee 37th annual computer Software and Applications Conference, COMPSAC 2013

作者： Tavarageri, Sanket Sadayappan, P. Dept. of Computer Science and Engineering Ohio State University United States

ISBN: (纸本)9780769549798

As processor and memory system speeds have significantly diverged, system designers have introduced ever larger caches in an effort to supply the processor with data at a rate it is capable of processing it. However, application characteristics vary and not all programs can effectively utilize large caches due to their inherent data reuse properties. the inability to use all the available cache capacity leads to wasted cache power dissipation. the rising specter of dark silicon makes it critical to avoid wasted power on a *** this paper, we develop a compile-time approach to analyze data reuse characteristics of affine computations and deduce the useful cache size(s) for a given system configuration. the non-useful cache can be power-gated to save power. Analysis of benchmarks shows that significant fractions of the last level cache of current processors may be turned off with no performance loss. © 2013 ieee.

关键词： Energy efficiency

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