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2nd international symposium on parallel and distributed Computing, ISPDC 2003

ISBN: (纸本)0769520693

The proceedings contain 40 papers. The topics discussed include: a parallel implementation of Chebyshev preconditioned conjugate gradient method;tuBiG - a layered infrastructure to provide support for grid functionalities;efficient code generation for automatic parallelization and optimization;graphical design tool for parallel programs with execution control based on global application states;strongly consistent global states detection using relative clock errors;a distributed platform based on web services for multimedia resource discovery;performance analysis of speculative concurrency control algorithms based on wait depth limited for distributed database systems;near-optimal dynamic task scheduling of precedence constrained coarse-grained tasks onto a computational grid;a Java middleware platform for resource-aware distributed applications;a simple scheduling heuristic for heterogeneous computing environments;and a negotiation protocol for database resource binding.

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Hierarchical Transactional Memory Protocol for distributed Mixed-Criticality Embedded Systems

Hierarchical Transactional Memory Protocol for Distributed M...

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IEEE international symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Zaher Owda Moisés Urbina Roman Obermaisser Mohammed Abuteir Institute of Embedded Systems University of Siegen

Transactional memories with support for real-time and reliability requirements are a research challenge for the deployment in safety-critical embedded systems. In addition, at present there are no transactional-memory architectures considering hierarchical systems of networked multi-core chips with both on-chip and off-chip networks. The presented work offers a predictable transactional memory solution for hierarchical distributed systems by executing a transactional memory protocol spanning both on-chip and off-chip networks to manage the memory operations of the cores at different multi-core chips. This includes relocating memory pages between the local caches at cores and the external memories while preserving the mixed-criticality requirements of the distributed system. The proposed protocol provides temporal predictability, fault isolation and bounded execution time assurances for safety-critical applications. An automotive use case with a simulation framework serves for the evaluation of the proposed solution.

关键词： Protocols Multicore processing Logic gates Memory management System-on-chip Embedded systems Real-time systems

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parallelizing Back Propagation Neural Network on Speculative Multicores

Parallelizing Back Propagation Neural Network on Speculative...

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international Conference on parallel and distributed Systems (ICPADS)

作者： Yaobin Wang Hong An Zhiqin Liu Tao Liu Dongmei Zhao Department of Computer Science and Technology University of Science and Technology of China China Department of Computer Science and Technology Southwest University of Science and Technology China

ISBN: (纸本)9781509053827

applications typically exhibit extremely different performance characteristics depending on the accelerator. Back propagation neural network (BPNN) has been parallelized into different platforms. However, it has not yet been explored on speculative multicore architecture thoroughly. This paper presents a study of parallelizing BPNN on a speculative multicore architecture, including its speculative execution model, hardware design and programming model. The implementation was analyzed with seven well-known benchmark data sets. Furthermore, it trades off several important design factors in coming speculative multicore architecture. The experimental results show that: (1) the BPNN performs well on speculative multicore platform. It can achieve similar speedup (17.7x to 57.4x) compared with graphics processors (GPU) while provides a more friendly programmability. (2) 64 cores' computing resources can be used efficiently and 4k is the proper speculative buffer capacity in the model.

关键词： Multicore processing Instruction sets Graphics processing units Programming Neural networks Hardware

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Performance Evaluation of parallelizing Algorithm Using Spanning Tree for Stream-Based Computing

Performance Evaluation of Parallelizing Algorithm Using Span...

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international symposium on Computing and Networking (CAndAR)

作者： Guyue Wang Koichi Wada Shinichi Yamagiwa Faculty of Engineering Information and Systems University of Tsukuba Tsukuba Ibaraki JAPAN

ISBN: (纸本)9781509026562

This paper proposes a detailed performance evaluation of an algorithm using spanning tree that automatically exploits the parallelism and determines an execution order of multiple kernel programs in distributed environment. In stream-based computing, efficient parallel execution requires careful scheduling of the invocation of the kernel programs. By mapping a kernel to a node and an I/O stream between kernels to an edge, the entire stream process can be treated as a spanning tree. The spanning tree, which allows feedback and feedforward edges, is effective for expressing dependencies that exist among kernels. In spanning tree, the nodes at the same depth do not have edges between them, and thus can be executed in parallel in the case parent nodes have been already executed. The series of the nodes can be executed in a pipelined manner. Thus, the proposed algorithm can extract both spatial and temporal parallelism. To evaluate the effectiveness of the proposed algorithm, two applications have been developed and parallelized based on the proposed algorithm. The results show that the parallel execution using four nodes of a GPU cluster obtained 3.5 times speedup in 2D-FFT and 3.0 times speedup in LU decomposition, compared to the sequential execution.

关键词： parallel processing Kernel Pipelines Graphics processing units Performance evaluation Clustering algorithms Central processing Unit

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Exploiting Longer SIMD Lanes in Dynamic Binary Translation

Exploiting Longer SIMD Lanes in Dynamic Binary Translation

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international Conference on parallel and distributed Systems (ICPADS)

作者： Ding-Yong Hong Sheng-Yu Fu Yu-Ping Liu Jan-Jan Wu Wei-Chung Hsu Institute of Information Science Academia Sinica Department of Computer Science and Information Engineering National Taiwan University

ISBN: (纸本)9781509053827

Recent trends in SIMD architecture have tended toward longer vector lengths and more enhanced SIMD features have been introduced in the newer vector instruction sets. However, legacy or proprietary applications compiled with short-SIMD ISA cannot benefit from the long-SIMD architecture, which supports improved parallelism and enhanced vector primitives, and thus only achieve a small fraction of potential peak performance. This paper presents a dynamic binary translation technique that enables short-SIMD binaries to exploit the benefits of the new SIMD architecture by rewriting short-SIMD loop code. We propose a general approach that translates loops consisting of short-SIMD instructions to machine-independent IR, conducts SIMD loop transformation/optimization at this IR level, and finally translates to long-SIMD instructions. Two solutions are presented to enforce SIMD load/store alignment, one for the problem caused by the binary translator's internal translation condition and one general approach using loop peeling optimization. The benchmark results show that an average speedup of 1.45X is achieved for NEON to AVX2 loop transformation.

关键词： Neon Computer architecture parallel processing Indexes Runtime Androids Humanoid robots

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2W-FD: A Failure Detector Algorithm with QoS 29

2W-FD: A Failure Detector Algorithm with QoS

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29th IEEE international parallel and distributed processing symposium (IPDPS)

作者： Tomsic, Alejandro Z. Sens, Pierre Garcia, Joao Arantes, Luciana Sopena, Julien Univ Paris 06 Sorbonne Univ CNRS InriaLIP6 F-75005 Paris France Univ Lisbon Inst Super Tecn P-1699 Lisbon Portugal

ISBN: (纸本)9781479986484

Failure detection plays a central role in the engineering of distributed systems. Furthermore, many applications have timing constraints and require failure detectors that provide quality of service (QoS) with some quantitative timeliness guarantees. Therefore, they need failure detectors that are fast and accurate. We introduce the Two Windows Failure Detector (2W-FD), an algorithm that provides QoS and is able to react to sudden changes in network conditions, a property that currently existing algorithms do not satisfy. We ran tests on real traces and compared the 2W-FD to state-of-the-art algorithms. Our results show that our algorithm presents the best performance in terms of speed and accuracy in unstable scenarios.

关键词： Failure Detectors Quality of Service Fault Tolerance distributed Algorithms Reliability Quiescence

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Stratified Sampling for Even Workload Partitioning Applied to IDA* and Delaunay Algorithms 29

Stratified Sampling for Even Workload Partitioning Applied t...

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29th IEEE international parallel and distributed processing symposium (IPDPS)

作者： Paudel, Jeeva Lelis, Levi H. S. Amaral, Jose Nelson Univ Alberta Dept Comp Sci Edmonton AB T6G 2M7 Canada Univ Fed Vicosa Dept Informat Vicosa MG Brazil

ISBN: (纸本)9781479986484

This work presents Workload Partitioning and Scheduling (WPS), a novel algorithm for evenly partitioning the computational workload of large implicitly-defined worklist-based applications on distributed/shared-memory systems. In WPS, a stratified sampling technique estimates the number of work items that will be processed in each step of the target application. Then WPS uses this estimation to evenly partition and distribute the computational workload. An empirical evaluation on large applications - Iterative-Deepening A* (IDA*) applied to (4x4)- and (5x5) - Sliding-Tile Puzzles, Delaunay Mesh Generation, and Delaunay Mesh Refinement - shows that WPS is applicable to a range of applications. A coordination between WPS and existing work-stealing schedulers for intranode load balancing yields additional speedups in the range of 18% to 40% compared to that achieved with the existing work-stealing schedulers alone. Such a coordination also outperforms an existing workload-partitioning scheme intended specifically for IDA* algorithms by 17% to 36%.

关键词： Delaunay Triangulation IDA Load Balancing Stratified Sampling Workload Partitioning international Development Association mesh generation Load balancing WPS Statistical sampling Workload

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Performance Impact of Batching Web-Application Requests Using Hot-spot processing on GPUs 29

Performance Impact of Batching Web-Application Requests Usin...

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29th IEEE international parallel and distributed processing symposium (IPDPS)

作者： Fjalling, Tobias Stenstrom, Per Admeta WideOrbit Gothenburg Sweden Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9781479986484

Web applications are a good fit for many-core servers because of their inherent high-degree of request-level parallelism. Yet, processing-intensive web-server requests can lead to low quality-of-service due to hot-spots, which calls for methods that can improve single-thread performance. This paper explores how to use off-chip GPUs to speed up web application hot-spots written in productivity-friendly environments (e.g. C#). First, we apply a number of straightforward optimizations through refactoring of a commercial-strength, web application code. This yields a speedup of 7.6 in a CPU multi-threaded, and multi-core test. Second, we then gather similar requests from different threads of the optimized code, by applying a technique called batching, to exploit SIMD parallelism provided by GPUs. Surprisingly, there is ample parallelism to be exploited from the already optimized code yielding a speedup of a factor between 2x to 3x compared to the best optimized CPU version.

关键词： GPU batching high-throughput web server web applications Speeding BATCHES GRAPPER PICK UP parallelism Synclitism Graphics processing Unit Online resources Hot spots Codes central processing units

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SparkCRF：一种基于Spark的并行CRFs算法实现

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计算机研究与发展 2016年第8期53卷 1819-1828页

作者：朱继召贾岩涛徐君乔建忠王元卓程学旗东北大学计算机科学与工程学院沈阳110819 中国科学院计算技术研究所网络数据科学与技术重点实验室北京100190

条件随机场(condition random fields,CRFs)可用于解决各种文本分析问题,如自然语言处理(natural language processing,NLP)中的序列标记、中文分词、命名实体识别、实体间关系抽取等.传统的运行在单节点上的条件随机场在处理大规模文本... 详细信息

条件随机场(condition random fields,CRFs)可用于解决各种文本分析问题,如自然语言处理(natural language processing,NLP)中的序列标记、中文分词、命名实体识别、实体间关系抽取等.传统的运行在单节点上的条件随机场在处理大规模文本时,面临一系列挑战.一方面,个人计算机遇到处理的瓶颈从而难以胜任;另一方面,服务器执行效率较低.而通过升级服务器的硬件配置来提高其计算能力的方法,在处理大规模的文本分析任务时,终究不能从根本上解决问题.为此,采用"分而治之"的思想,基于Apache Spark的大数据处理框架设计并实现了运行在集群环境下的分布式CRFs——SparkCRF.实验表明,SparkCRF在文本分析任务中,具有高效的计算能力和较好的扩展性,并且具有与传统的单节点CRF++相同水平的准确率.

关键词：大数据机器学习分布式计算 Spark 条件随机场

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Alleviation of Disk I/O Contention in Virtualized Settings for Data-Intensive Computing 2

Alleviation of Disk I/O Contention in Virtualized Settings f...

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international symposium on Big Data Computing

作者： Malensek, Matthew Pallickara, Sangmi Lee Pallickara, Shrideep Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA

ISBN: (纸本)9780769556963

Steady growth in storage and processing capabilities has led to the accumulation of large-scale datasets that contain valuable insight into the interactions of complex systems, long- and short-term trends, and real-world phenomena. Converged infrastructure, operating on cloud deployments and private clusters, has emerged as an energy-efficient and cost-effective means of coping with these computing demands. However, increased collocation of storage and processing activities often leads to greater contention for resources in high-use situations. This issue is particularly pronounced when running distributed computations (such as MapReduce applications), because overall execution times are dependent on the completion time of the slowest task(s). In this study, we propose a framework that makes opinionated disk scheduling decisions to ensure high throughput for tasks that use I/O resources conservatively, while still maintaining the average performance of long-running batch processing operations. Our solution does not require modification of client applications or virtual machines, and we illustrate its efficacy on a cluster of 1,200 VMs with a variety of datasets that span over 1 Petabyte of information;in situations with high disk interference, our algorithm resulted in a 20% improvement in MapReduce completion times.

关键词： Data-intensive computing I/O interference big data distributed I/O performance

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