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检索条件"任意字段=4th International Symposium on Parallel and Distributed Processing and Applications"

共 3818 条记录，以下是151-160 订阅

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Massively parallel Technologies Based on Microelectromechanical Systems for Improving Effective Functioning of the Aircraft 4

Massively Parallel Technologies Based on Microelectromechani...

引用

4th IEEE international Conference Methods and Systems of Navigation and Motion Control (MSNMC)

作者： Serhii, Tovkach Natl Aviat Univ Kiev Ukraine

ISBN: (纸本)9781509010530

the problem of development adaptive control systems based on microelectromechanical systems for reduce turbulent flow of the aircraft has been considered. Complex solution based on microelectromechanical systems and graphic processing platform NVIDIA Tegra, which includes massively parallel technology, has been proposed. It develops parallel processing software based on algorithms that delivers scaling and speed up on distributed memory systems for high performance applications. the distributed microelectromechanical systems technique involves spreading integrated sense-compute-act modules over areas to sense the physical world and act upon it. Tiny elements can reduce drag by sensing vortices and interacting with them. It will help to reach better maneuverability, increase the range of aircraft payload and capability.

关键词： turbulent flow control microelectromechanical sysytems (MEMS) parallel computing scaling graphic processing unit

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Memory-Disaggregated In-Memory Object Store Framework for Big Data applications 36

Memory-Disaggregated In-Memory Object Store Framework for Bi...

引用

36th IEEE international parallel and distributed processing symposium (IEEE IPDPS)

作者： Abrahamse, Robin Hadnagy, Akos Al-Ars, Zaid Delft Univ Technol Accelerated Big Data Syst Delft Netherlands

ISBN: (纸本)9781665497473

the concept of memory disaggregation has recently been gaining traction in research. With memory disaggregation, data center compute nodes can directly access memory on adjacent nodes and are therefore able to overcome local memory restrictions, introducing a new data management paradigm for distributed computing. this paper proposes and demonstrates a memory disaggregated in-memory object store framework for big data applications by leveraging the newly introduced thymesisFlow memory disaggregation system. the framework extends the functionality of the pre-existing Apache Arrow Plasma object store framework to distributed systems by enabling clients to easily and efficiently produce and consume data objects across multiple compute nodes. this allows big data applications to increasingly leverage parallel processing at reduced development costs. In addition, the paper includes latency and throughput measurements that indicate only a modest performance penalty is incurred for remote disaggregated memory access as opposed to local (similar to 6.5 vs similar to 5.75 GiB/s). the results can be used to guide the design of future systems that leverage memory disaggregation as well as the newly presented framework. this work is open-source and publicly accessible at https://***/10.5281/zenodo.6368998.

关键词： Memory Disaggregation Apache Arrow Plasma thymesisFlow

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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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Balanced Coloring for parallel Computing applications 29

Balanced Coloring for Parallel Computing Applications

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

作者： Lu, Hao Halappanavar, Mahantesh Chavarria-Miranda, Daniel Gebremedhin, Assefaw Kalyanaraman, Ananth Washington State Univ Pullman WA 99164 USA Pacific Northwest Natl Lab Richland WA 99352 USA

ISBN: (纸本)9781479986484

Graph coloring is used to identify subsets of independent tasks in parallel scientific computing applications. Traditional coloring heuristics aim to reduce the number of colors used as that number also corresponds to the number of parallel steps in the application. However, if the color classes produced have a skew in their sizes, utilization of hardware resources becomes inefficient, especially for the smaller color classes. Equitable coloring is a theoretical formulation of coloring that guarantees a perfect balance among color classes, and its practical relaxation is referred to as balanced coloring. In this paper, we revisit the problem of balanced coloring in the context of parallel computing. the goal is to achieve a balanced coloring of an input graph without increasing the number of colors that an algorithm oblivious to balance would have used. We propose and study multiple heuristics that aim to achieve such a balanced coloring, present parallelization approaches for multi-core and manycore architectures, and cross-evaluate their effectiveness with respect to the quality of balance achieved and performance. Furthermore, we study the impact of the proposed balanced coloring heuristics on a concrete application - viz. parallel community detection, which is an example of an irregular application. the thorough treatment of balanced coloring presented in this paper from algorithms to application is expected to serve as a valuable resource to parallel application developers who seek to improve parallel performance of their applications using coloring.

关键词： Balanced coloring Tilera manycore architecture community detection graph algorithms

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

MediNER: Understanding Diabetes Management Strategies Based ...

引用

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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Causality filters: A tool for the online visualization and steering of parallel and distributed programs

Causality filters: A tool for the online visualization and s...

引用

11th international parallel processing symposium (IPPS 97)

作者： Kraemer, E Washington Univ St. Louis United States

ISBN: (纸本)0818677937

Interactive program steering is a promising technique for improving the performance of parallel and distributed applications. Steering decisions are typically based on visual presentations of some subset of the computation's current state, a historical view of the computation's behavior, or views of metrics based on the program's performance. As in any endeavor good decisions require accurate information. However the distributed nature of the collection process may result in distortions in the portrayal of the program's execution. these distortions stem from the merging of streams of information from distributed collection points into a single stream without enforcing the ordering relationships that held among the program components that produced the information. An ordering filter placed at the point at which the streams are merged can ensure a valid ordering, leading to more accurate visualizations and better informed steering decisions. In this paper we describe the implementation of such filters in the Falcon interactive steering toolkit, and present a methodology for their specification for automated generation.

关键词： Interactive computer systems

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Enhancing Java Streams API with PowerList Computation 34

Enhancing Java Streams API with PowerList Computation

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34th IEEE international parallel and distributed processing symposium (IPDPS)

作者： Niculescu, Virginia Bufnea, Darius Sterca, Adrian Babes Bolyai Univ Fac Math & Comp Sci Cluj Napoca Romania

ISBN: (纸本)9781728174457

Since they were introduced, Java streams were very fast embraced by the industry, being currently used at a large scale. the parallelism enabled by them is very easy to achieve, but it is constrained either by the used parallelism model (in some cases), or by the set of operations that could be specified using streams. We investigate in this paper the possibility to enhance the computation types that could be defined using the Java streams API by introducing into this infrastructure the PowerList theory based computation. Powerlists are recursive data structures that together with their associated algebraic theory offer both abstractions in order to ease the development of parallel applications, and also a methodology to design parallel algorithms. the Java streaming infrastructure could be adapted to support them in a great measure. We present here such an adaptation, and we analyse and discuss the advantages and constraints. this analysis is exemplified by application examples.

关键词： parallel programming streams recursive structures Java performance models

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Programmable and Scalable Reductions on Clusters

Programmable and Scalable Reductions on Clusters

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IEEE 27th international parallel and distributed processing symposium (IPDPS)

作者： Ciesko, Jan Bueno, Javier Puzovic, Nikola Ramirez, Alex Badia, Rosa M. Labarta, Jesus Barcelona Supercomp Ctr Barcelona Spain

ISBN: (纸本)9780769549712

Reductions matter and they are here to stay. Wide adoption of parallel processing hardware in a broad range of computer applications has encouraged recent research efforts on their efficient parallelization. Furthermore, trends towards high productivity languages in mainstream computing increases the demand for efficient programming support. In this paper we present a new approach on parallel reductions for distributed memory systems that provides both scalability and programmability. Using OmpSs, a task-based parallel programming model, the developer has the ability to express scalable reductions through a single pragma annotation. this pragma annotation is applicable for tasks as well as for work-sharing constructs (with implicit tasking) and instructs the compiler to generate the required runtime calls. the supporting runtime handles data and task distribution, parallel execution and data reduction. Scalability is achieved through a software cache that maximizes local and temporal data reuse and allows overlapped computation and communication. Results confirm scalability for up to 32 12-core cluster nodes.

关键词： reductions software cache parallel programming runtime systems distributed systems

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MobiStreams: A Reliable distributed Stream processing System for Mobile Devices

MobiStreams: A Reliable Distributed Stream Processing System...

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IEEE 28th international parallel & distributed processing symposium (IPDPS)

作者： Wang, Huayong Peh, Li-Shivan MIT Cambridge MA 02139 USA

ISBN: (纸本)9780769552071

Multi-core phones are now pervasive. Yet, existing applications rely predominantly on a client-server computing paradigm, using phones only as thin clients, sending sensed information via the cellular network to servers for processing. this makes the cellular network the bottleneck, limiting overall application performance. In this paper, we propose MobiStreams, a distributed Stream processing System (DSPS) that runs directly on smartphones. MobiStreams can offload computing from remote servers to local phones and thus alleviate the pressure on the cellular network. Implementing DSPS on smartphones faces significant challenges: 1) multiple phones can readily fail simultaneously, and 2) the phones' ad-hoc WiFi network has low bandwidth. MobiStreams tackles these challenges through two new techniques: 1) token-triggered checkpointing, and 2) broadcast-based checkpointing. Our evaluations driven by two real world applications deployed in the US and Singapore show that migrating from a server platform to a smartphone platform eliminates the cellular network bottleneck, leading to 0.78 similar to 42.6X throughput increase and 10%similar to 94.8% latency decrease. Also, MobiStreams' fault tolerance scheme increases throughput by 230% and reduces latency by 40% vs. prior state-of-the-art fault-tolerant DSPSs.

关键词： stream computing mobile computing reliability

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Proceedings - 11th international symposium on distributed Computing and applications to Business, Engineering and Science, DCABES 2012: Preface

Proceedings - 11th International Symposium on Distributed Co...

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11th international symposium on distributed Computing and applications to Business, Engineering and Science, DCABES 2012

作者： Guo, Qingping Lai, Choi-Hong Douglas, Craig Wuhan University of Technology China University of Greenwich United Kingdom University of Wyoming United States

ISBN: (纸本)9780769548180

the DCABES is a community working in the area of distributed Computing and applications in Business, Engineering, and Sciences, and is responsible for organizing meetings and symposia related to the field. DCABES intends to bring together researchers and developers in the academic field and industry from around the world to share their research experience and to explore research collaboration in the areas of distributed parallel processing and applications. the 11th international symposium on distributed Computing and applications to Business, Engineering and Science (DCABES 2012) will be held on October 19-22, 2012. All papers accepted by DCABES 2012 Proceedings have been peer reviewed and carefully modified. All papers contained in the Proceedings give us a glimpse of what future technology and applications are being studied in the distributed parallel computing area in the world. More papers concerning the distributed parallel algorithms and applications, the intelligent transportation as well as image processing have been selected and included in the DCABES 2012 Proceedings. © 2012 IEEE.

关键词： Image processing

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