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parallel analysis of TACLeBench kernel benchmark's loop and procedure level speculation 19

Parallel analysis of TACLeBench kernel benchmark's loop and ...

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19th ieee international symposium on parallel and distributed processing with applications (ieee ISPA)

作者： Meng, Huiling Wang, Yaobin Li, Ling Musariri, Manasah Wang, Xinyi Southwest Univ Sci & Technol Mianyang Sichuan Peoples R China

ISBN: (纸本)9781665435741

Thread level speculation (TLS) technology has gained substantial international recognition due to its unique parallel program execution. It uses the potential parallel execution of programs to improve the utilization of multi-core resources. However, the kernel benchmark of TACLeBench has not effectively been analyzed using TLS parallelization. In response to this problem, we select 7 programs in the TACLeBench kernel benchmark to analyze its loop and procedure level speculation executions to measure their maximum potential parallelism. Furthermore, we discuss its runtime characteristics (thread size, speculative parallelism coverage, dependency feature) and the influence of program source code on speedup. Our experimental results illustrate that: 1) Most applications achieve impressive results. Bsort reaches 20.79x speedup in loop level speculation, and lms has 9.51x speedup in procedure level speculation;2) By using TLS to accelerate the TACLeBench kernel benchmark, most applications effectively utilize computing resources from 4 to 16 cores;3) The kernel benchmark is more suitable for developing parallelism in loop level speculation.

关键词： Thread level speculation (TLS) multi-core TACLeBench

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A Greedy-Genetic Local-Search Heuristic for the Traveling Salesman Problem 15

A Greedy-Genetic Local-Search Heuristic for the Traveling Sa...

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15th ieee international symposium on parallel and distributed processing with applications (ISPA) / 16th ieee international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Rashid, Mohammad Harun Mosteiro, Miguel A. Pace Univ Seidenberg Sch CSIS New York NY 10038 USA Pace Univ Comp Sci Dept New York NY 10038 USA

ISBN: (纸本)9781538637906

The Travelling Salesman Problem (TSP) is one of the typical combinatorial optimization problems that is easy to describe but hard to solve. In this work, we present a novel solution that integrates a genetic algorithm, local-search heuristics, and a greedy algorithm. For the genetic algorithm we keep the evolutionary technique to generate children from parents, which uses operators like mutation, selection of the most fitted element, and crossover, but the latter is enhanced with a local-search heuristic. We also use the local search heuristic for its strong climbing ability, as well as to find local optima efficiently in the TSP space. The greedy algorithm is used to generate new greedy children from parents. The experimental evaluation shows that the optimization algorithm presented provides higher quality solutions for TSP with respect to previous genetic algorithms, within reasonable computational time.

关键词： travelling salesman problem TSP genetic algorithms local search tabu search

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MediNER: Understanding Diabetes Management Strategies Based on Social Media Discourse 19

MediNER: Understanding Diabetes Management Strategies Based ...

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19th ieee international symposium on parallel and distributed processing with applications (ieee ISPA)

作者： Oyebode, Oladapo Orji, Rita Dalhousie Univ Fac Comp Sci Halifax NS Canada

ISBN: (纸本)9781665435741

Over the years, researchers have leveraged patients' discourse on social media to inform clinical and digital interventions. We contribute to these research efforts by mining and analyzing diabetes-related public posts on two social networks (online forums) with the aim of identifying management strategies adopted by diabetes patients and suggesting appropriate interventions. We develop a medical named entity recognition framework, MediNER, to identify named entities related to diabetes management and classify them into Food, Medication, Therapeutic Procedure, and Supplement. Our analysis shows that food-related strategies are most prevalent among both Type 1 and Type 2 diabetes patients, followed by medication-related strategies. Strategies involving supplements (such as vitamins) are the least utilized. We also investigate for gender differences in the strategies employed by diabetes patients. Finally, we offer design recommendations for digital interventions aimed at diabetes self-management based on our findings.

关键词： social media diabetes natural language processing named entity recognition application framework intervention design

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A Performance Analysis of Large Scale Scientific Computing applications from Log Archives 33

A Performance Analysis of Large Scale Scientific Computing A...

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33rd ieee international parallel and distributed processing symposium (IPDPS)

作者： Cao, Liqiang Liu, Xu Xu, Xiaowen Liu, Zhanjun Inst Appl Phys & Computat Math Beijing Peoples R China

ISBN: (纸本)9781538655559

A log archive for scientific computing applications is a set of logs for model and time of jobs in HPCs. We have developed light weight and fast performance analysis tools on top of log archives. We classify the job logs based on the similarity of the input models to form a model-based tree like archive. With linear regression, we analyze the relations of the step time of the jobs with the parameters in the model. We found that although there is some disturbance, the performance of most of the jobs showed good regularity. In one of the applications, we found the step time of job changes proportionally to the geometric parameters of model. And the most significant physical parameter determines step time up to 1.7 times. In another application, we find that the performance of each step scales 1.59 times with the number of process scales from 384 to 768.

关键词： performance analysis log archive linear regression performance predict

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Scaling Data-Intensive applications on Heterogeneous Platforms with Accelerators

Scaling Data-Intensive Applications on Heterogeneous Platfor...

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26th ieee international parallel and distributed processing symposium (IPDPS) / Workshop on High Performance Data Intensive Computing

作者： Balevic, Ana Kienhuis, Bart Leiden Inst Adv Comp Sci NL-2333 CA Leiden Netherlands

ISBN: (纸本)9780769546766

Heterogeneous parallel systems including accelerators such as Graphics processing Units (GPUs), are expected to play a major role in architecting the largest systems in the world, as well as the most powerful embedded devices. Impressive computational speedups have been reported for numerous algorithms in fields of medical image processing, digital signal processing, astrophysics, modeling and simulations. However, it is frequently assumed that the working data set of the application fits in the memory of the accelerator. In this paper, first we elevate this constraint by presenting a simple and scalable compile-time approach for processing large data sets based on I/O tiling. Second, we combine tiling with streaming in our asynchronous execution model, which enables efficient data-driven processing of large data sets on heterogeneous platforms with accelerators. Finally, we present results for several microbenchmarks and three data parallel kernels.

关键词： Accelerators Tile Dataset big data Platform

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An Adaptive Priority-Based Heuristic Approach for Scheduling DAG applications with Uncertainties 15

An Adaptive Priority-Based Heuristic Approach for Scheduling...

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15th ieee international symposium on parallel and distributed processing with applications (ISPA) / 16th ieee international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Zheng, Wei Zhang, Xinbo Tang, Lu Zhang, Dongzhan Chen, Jinjun Xiamen Univ Sch Informat Sci & Engn Dept Comp Sci Xiamen Peoples R China Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Peoples R China Swinburne Univ Technol Swinburne Data Sci Res Inst Hawthorn Vic Australia

ISBN: (纸本)9781538637906

In the context of large-scale distributed computing environments, among various DAG scheduling heuristics aiming at coping with severe uncertainties during task execution, those ones that try to maximize the parallelism of ready tasks seems to be promising. However, most of such heuristics consider only the DAG structure when making scheduling decision. When the information about task execution time (even though might be inaccurate) is given, it might be interesting to investigate whether this information should be taken into account during scheduling, and if yes, how to. This paper presents an adaptive priority based heuristic, which properly considers the task execution time estimate and the DAG structure attributes in the task prioritization. The evaluation result shows the proposed approach obtains better scheduling performance than existing solutions.

关键词： Task analysis Processor scheduling Scheduling Resource management Uncertainty Optimization Topology

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Dataflow programming using AGAPIA 13

Dataflow programming using AGAPIA

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13th ieee international symposium on parallel and distributed Computing (ISPDC)

作者： Paduraru, Ciprian I. Univ Bucharest Dept Comp Sci Bucharest Romania

ISBN: (纸本)9781479959198

As distributed applications became more commonplace and more sophisticated, new programming languages and models for distributed programming were created. In the context of continuously increasing data flows in parallel applications, there is a renewed interest in the dataflow paradigm. This paper shows why AGAPIA language is suitable for dataflow programming. AGAPIA is capable of expressing massive parallelism in a manageable way for programmers, allowing building dynamic nodes and links in the data flow graph at runtime. The nodes of the dataflow graph, also called programs, are modular and reusable. The communication is transparent for users allowing them to concentrate on the high level flow and algorithm. A complete application and an analysis in terms of productivity and performance are presented in order to demonstrate the AGAPIA's capabilities.

关键词： Arrays Computer languages parallel processing Programming Runtime Silicon Syntactics Computer Programming Languages Runtime Programming parallel processing (COMPUTERS) data flow Silicon data flow graphs arrays distributed software Computer personnel

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A Novel parallel Image Encryption Scheme Using Chaos 15

A Novel Parallel Image Encryption Scheme Using Chaos

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15th ieee international symposium on parallel and distributed processing with applications (ISPA) / 16th ieee international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Fu, Chong Zhang, Gao-yuan Zhu, Mai Cong, Li-ying Lei, Wei-min Northeastern Univ Sch Comp Sci & Engn Shenyang 110004 Liaoning Peoples R China

ISBN: (纸本)9781538637906

In recent years, chaos-based image cipher has been widely studied and a growing number of schemes based on permutation-substitution architecture have been proposed. To better meet the challenge of real-time secure image communication applications, this paper suggests a new image encryption scheme using a parallel substitution. In the permutation stage, the Arnold cat map is employed to shuffle the pixel positions so as to erase the strong relationship between adjacent pixels. In the substitution stage, the scrambled image is firstly decomposed into eight bit-planes which are then parallelly mixed with keystreams generated by the chaotic logistic map. Theoretically, the parallel substitution strategy runs eight times faster than the serial strategy on an 8-thread processor as the volume of data processed by each substitution unit is 1/8 of that of the input image. Experimental results show that the proposed parallel scheme runs more than five times faster than the serial scheme. Extensive security analysis is carried out with detailed analysis, demonstrating the satisfactory security of the proposed scheme.

关键词： image cipher Arnold cat map parallel substitution bit-plane logistic map

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Examining the Reproducibility of Using Dynamic Loop Scheduling Techniques in Scientific applications 31

Examining the Reproducibility of Using Dynamic Loop Scheduli...

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31st ieee international parallel and distributed processing symposium Workshops (IPDPS)

作者： Hoffeins, Franziska Ciorba, Florina M. Banicescu, Ioana Tech Univ Dresden Ctr Informat Serv & High Performance Comp D-01062 Dresden Germany Univ Basel Dept Math & Comp Sci CH-4051 Basel Switzerland Mississippi State Univ Dept Comp Sci & Engn Mississippi State MS 39762 USA

ISBN: (纸本)9780769561493

Reproducibility of the execution of scientific applications on parallel and distributed systems is a growing concern, underlying the trustworthiness of the experiments and the conclusions derived from experiments. Dynamic loop scheduling (DLS) techniques are an effective approach towards performance improvement of scientific applications via load balancing. These techniques address algorithmic and systemic sources of load imbalance by dynamically assigning tasks to processing elements. The DLS techniques have demonstrated their effectiveness when applied in real applications. Complementing native experiments, simulation is a powerful tool for studying the behavior of parallel and distributed applications. In earlier work, the scalability [1], robustness [2], and resilience [3] of the DLS techniques were investigated using the MSG interface of the SimGrid simulation framework [4]. The present work complements the earlier work and concentrates on the verification via reproducibility of the implementation of the DLS techniques in SimGrid-MSG. This work describes the challenges of verifying the performance of using DLS techniques in earlier implementations of scientific applications. The verification is performed via reproducibility of simulations based on SimGrid-MSG. To simulate experiments selected from earlier literature, the reproduction process begins by extracting the information needed from the earlier literature and converting it into the input required by SimGrid- MSG. The reproducibility study is carried out by comparing the performance of SimGrid-MSG-based experiments with those reported in two selected publications in which the DLS techniques were originally proposed. While the reproduction was not successful for experiments from one of the selected publications, it was successful for experiments from the other. This successful reproduction implies the verification of the DLS implementation in SimGrid- MSG for the considered applications and systems, and th

关键词： Verification via Reproducibility Simulation Scheduling Dynamic Loop Scheduling Scientific applications SimGrid-MSG

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PaPar: A parallel Data Partitioning Framework for Big Data applications 31

PaPar: A Parallel Data Partitioning Framework for Big Data A...

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31st ieee international parallel and distributed processing symposium (IPDPS)

作者： Wang, Hao Zhang, Jing Zhang, Da Pumma, Sarunya Feng, Wu-chun Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA

ISBN: (纸本)9781538639146

Today, big data applications can generate large-scale data sets at an unprecedented rate;and scientists have turned to parallel and distributed systems for data analysis. Although many big data processing systems provide advanced mechanisms to partition data and tackle the computational skew, it is difficult to efficiently implement skew-resistant mechanisms, because the runtime of different partitions not only depends on input data size but also algorithms that will be applied on data. As a result, many research efforts have been undertaken to explore user-defined partitioning methods for different types of applications and algorithms. However, manually writing application-specific partitioning methods requires significant coding effort, and finding the optimal data partitioning strategy is particularly challenging even for developers that have mastered sufficient application knowledge. In this paper, we propose PaPar, a parallel data Partitioning framework for big data applications, to simplify the implementations of data partitioning algorithms. PaPar provides a set of computational operators and distribution strategies for programmers to describe desired data partitioning methods. Taking an input data configuration file and a workflow configuration file as the input, PaPar can automatically generate the parallel partitioning codes by formalizing the user-defined workflow as a sequence of key-value operations and matrix-vector multiplications, and efficiently mapping to the parallel implementations with MPI and MapReduce. We apply our approach on two applications: muBLAST, a MPI implementation of BLAST algorithms for biological sequence search;and PowerLyra, a computation and partitioning method for skewed graphs. The experimental results show that compared to the partitioning methods of applications, the codes generated by PaPar can produce the same data partitions with comparable or less partitioning time.

关键词： Partition Skew Big Data MapReduce MPI

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