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检索条件"任意字段=13th IEEE International Symposium on Parallel and Distributed Processing with Applications"

共 2574 条记录，以下是231-240 订阅

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17th ieee international Workshop on Automatic Performance Tuning (iWAPT2022)

17th IEEE International Workshop on Automatic Performance Tu...

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ieee international symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Che-Rung Lee Satoshi Ohshima

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

the goal of the Seventeenth international Workshop on Automatic Performance Tuning (iWAPT2022) is to bring together researchers who are investigating automated techniques for constructing and/or adapting algorithms and software for high-performance on modern complex machine architectures. iWAPT is a series of workshops that focus on research and techniques related to performance sustainability issues. the series provides an opportunity for researchers and users of automatic performance tuning (AT) technologies to exchange ideas and experiences acquired when applying such technologies to improve the performance of algorithms, libraries, and applications; in particular, on cutting edge computing platforms. the half-day workshops consist of presentations of research papers. Topics of interest include performance modeling; adaptive algorithms; autotuned numerical algorithms; libraries and scientific applications; empirical compilation; automated code generation; frameworks and theories of AT and software optimization; autonomic computing; and context-aware computing.

关键词： Conferences Tuning Software algorithms Software Libraries Sustainable development Scientific computing

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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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SPHYNX: Spectral Partitioning for HYbrid aNd aXelerator-enabled systems 34

SPHYNX: Spectral Partitioning for HYbrid aNd aXelerator-enab...

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

作者： Acer, Seher Boman, Erik G. Rajamanickam, Sivasankaran Sandia Natl Labs Ctr Comp Res POB 5800 Albuquerque NM 87185 USA

ISBN: (纸本)9781728174457

Graph partitioning has been an important tool to partition the work among several processors to minimize the communication cost and balance the workload. While accelerator-based supercomputers are emerging to be the standard, the use of graph partitioning becomes even more important as applications are rapidly moving to these architectures. However, there is no scalable, distributed-memory, multi-GPU graph partitioner available for applications. We developed a spectral graph partitioner, Sphynx, using the portable, accelerator-friendly stack of the Trilinos framework. We use Sphnyx to systematically evaluate the various algorithmic choices in spectral partitioning with a focus on GPU performance. We perform those evaluations on irregular graphs, because state-of-the-art partitioners have the most difficulty on them. We demonstrate that Sphynx is up to 17x faster on GPUs compared to the case on CPUs, and up to 580x faster compared to a state-of-the-art multilevel partitioner. Sphynx provides a robust alternative for applications looking for a GPU-based partitioner.

关键词： graph partitioning spectral partitioning GPUs distributed-memory systems

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Hardware resources analysis of BNNs splitting for FARD-based multi-FPGAs distributed Systems 34

Hardware resources analysis of BNNs splitting for FARD-based...

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

作者： Fiscaletti, Giorgia Speziali, Marco Stornaiuolo, Luca Santambrogio, Marco D. Sciuto, Donatella Politecn Milan Dipartimento Elettron Informaz & Bioingn DEIB Milan Italy

ISBN: (纸本)9781728174457

FPGAs have proven to be valid architectures to accelerate the inference phase of Convolutional Neural Networks (CNNs). State-of-the-art works also demonstrated that it is possible to take advantage of a distributed FPGA-base system to improve performance, power consumption and scalability of such algorithms. However, the hardware resource usage, communication, and the nodes management become main aspects when dealing with an embedded distributed scenario. In this context, FINN optimizes the FPGA-based CNNs with binarization and FARD is a framework that allows the acceleration of fog computing-based application with FPGAs. In this work, we present how to extend FARD to deal with job-based applications rather than the event-based fog computing scenario. In particular, we analyzed two PYNQ-Z1 connected each other and we implemented a distributed BNN algorithm based on FINN's CnvW2A2. Results show how hardware resources vary according to the division of the network when splitting after each convolutional layer.

关键词： Binarized Neural Networks BNN PYNQ embedded distributed

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Data parallel Large Sparse Deep Neural Network on GPU 34

Data Parallel Large Sparse Deep Neural Network on GPU

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

作者： Sattar, Naw Safrin Arifuzzaman, Shaikh Univ New Orleans Dept Comp Sci New Orleans LA 70148 USA

ISBN: (纸本)9781728174457

Sparse Deep Neural Network (DNN) is an emerging research area since deploying deep neural networks with limited resources is very challenging. In this work, we provide a scalable solution to the Sparse DNN Challenge-a challenge posed by MIT/ieee/Amazon ***-by designing data parallelism on GPUs. We provide a solution based on Python TensorFlow as it is a widely used tool in different scientific applications for deep learning. We use the datasets provided by GraphChallenge, derived from the MNIST handwritten letters. We use the Synthetic DNNs from RadiX-Net with varying number of neurons and layers. We implement a data parallel implementation of Sparse DNN using TensorFlow on GPU. Our solution shows up to 4.7x speedup over the basehne serial MATLAB implementation given in GraphChallenge. In addition to that, our TensorFlow GPU implementation demonstrates a 3-fold speedup over our TensorFloW CPU implementation.

关键词： deep neural network sparse data parallel computing GPU TensorFlow

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Methods and Experiences for Developing Abstractions for Data-intensive, Scientific applications 34

Methods and Experiences for Developing Abstractions for Data...

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

作者： Luckow, Andre Jha, Shantenu Ludwig Maximilians Univ Munchen Munich Germany Rutgers State Univ ECE RADICAL Piscataway NJ 08854 USA Brookhaven Natl Lab Upton NY 11973 USA

ISBN: (纸本)9781728174457

Developing software for scientific applications that require the integration of diverse types of computing, instruments, and data present challenges that are distinct from commercial software. these applications require scale, and the need to integrate various programming and computational models with evolving and heterogeneous infrastructure. Pervasive and effective abstractions for distributed infrastructures are thus critical;however, the process of developing abstractions for scientific applications and infrastructures is not well understood. While theory-based approaches for system development are suited for well-defined, closed environments, they have severe limitations for designing abstractions for scientific systems and applications. the design science research (DSR) method provides the basis for designing practical systems that can handle real-world complexities at all levels. In contrast to theory-centric approaches, DSR emphasizes both practical relevance and knowledge creation by building and rigorously evaluating all artifacts. We show how DSR provides a well-defined framework for developing abstractions and middleware systems for distributed systems. Specifically, we address the critical problem of distributed resource management on heterogeneous infrastructure over a dynamic range of scales, a challenge that currently limits many scientific applications. We use the pilot-abstraction, a widely used resource management abstraction for high-performance, high throughput, big data, and streaming applications, as a case study for evaluating the DSR activities. For this purpose, we analyze the research process and artifacts produced during the design and evaluation of the pilot-abstraction. We find DSR provides a concise framework for iteratively designing and evaluating systems. Finally, we capture our experiences and formulate different lessons learned.

关键词： Iterative methods

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On Overlapping Communication and File I/O in Collective Write Operation 34

On Overlapping Communication and File I/O in Collective Writ...

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

作者： Feki, Raafat Gabriel, Edgar Univ Houston Dept Comp Sci Parallel Software Technol Lab Houston TX 77204 USA

ISBN: (纸本)9781728174457

Many parallel scientific applications spend a significant amount of time reading and writing data files. Collective I/O operations allow to optimize the file access of a process group by redistributing data across processes to match the data layout on the file system. In most parallel I/O libraries, the implementation of collective I/O operations is based on the two-phase I/O algorithm, which consists of a communication phase and a file access phase. this papers evaluates various design options for overlapping two internal cycles of the two-phase I/O algorithm, and explores using different data transfer primitives for the shuffle phase, including non-blocking two-sided communication and multiple versions of one-sided communication. the results indicate that overlap algorithms incorporating asynchronous I/O outperform overlapping approaches that only rely on non-blocking communication. However, in the vast majority of the testcases one-sided communication did not lead to performance improvements over two-sided communication.

关键词： Data transfer

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Neksus: An Interconnect for Heterogeneous System-In-Package Architectures 34

Neksus: An Interconnect for Heterogeneous System-In-Package ...

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

作者： Goyal, Vidushi Wang, Xiaowei Bertacco, Valeria Das, Reetuparna Univ Michigan Dept Comp Sci & Engn Ann Arbor MI 48109 USA

ISBN: (纸本)9781728168760

In the embedded systems industry today, skyrocketing design and manufacturing costs of Systems-on-Chip (SoCs) are key limiting factors for growth. Emerging 2.5D-based System-In-Package (SiP) architectures show potential to lower these costs by enabling the reuse of hard core units and providing higher manufacturing yields due to small chiplet sizes. In this paper, we present Neksus, a novel architecture designed to lower SiP manufacturing costs, support modular "plug-and-play" chiplet integration, and leverage the unique properties of interposers. Key to Neksus is a new dedicated interconnect chiplet that addresses the limitations of SiP packaging technology by leveraging direct communication over a mini-chain IP-connection topology. In addition to satisfying SiP technology constraints, because our mini-chain design provides high-bandwidth IP-to-IP communication, it is particularly well-suited for bandwidth-intensive mobile applications. Our evaluation shows Neksus provides up to 28% performance improvement and 31% energy savings over recent SiP architecture.

关键词： 2.5D stacking interposer chiplets Mobile applications

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Scalability of Sparse Matrix Dense Vector Multiply (SpMV) on a Migrating thread Architecture 34

Scalability of Sparse Matrix Dense Vector Multiply (SpMV) on...

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

作者： Page, Brian A. Kogge, Peter M. Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (纸本)9781728174457

Sparse matrix dense vector multiplication (SpMV), exhibits the memory bandwidth and communication driven nature of many sparse linear algebra operations. Irregular memory accesses from the non-zero structure within a sparse matrix wreak havoc on performance. this paper presents strong scaling for communication avoiding SpMV implementations on a migrating thread system intended to address the lack of locality in sparse problems. We developed communication avoiding SpMV code to attempt to reduce off-node thread migration by using the hypergraph partitioning package HYPE to determine workload distribution. Additionally, we investigate the performance impact of overlapping communication and computation through the use of remote memory operations supported by the architecture. Incorporating remote memory operations with hypergraph partitioning we achieved 6.18X speedup for overall performance.

关键词： Emerging Architectures migrating threads irregular applications communication overhead HPC

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Continuous Debugging of Microservices 18

Continuous Debugging of Microservices

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18th ieee Int Symp on parallel and distributed Proc with Applicat (ISPA) / 10th ieee Int Conf on Big Data and Cloud Comp (BDCloud) / ieee Int Symp on Social Comp and Networking (SocialCom) / ieee Int Conf on Sustainable Comp and Commun (SustainCom)

作者： Zhu, Hong Bayley, Ian Wang, Hongbo Oxford Brookes Univ Sch Engn Comp & Math Oxford OX33 1HX England Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China

ISBN: (纸本)9781665414852

Debugging is one of the most difficult tasks during the development of cloud-native applications for the microservices architecture. this paper proposes a continuous debugging facility to support the DevOps continuous development methodology. It has been implemented and integrated into the Integrated DevOps Environment CIDE for microservices written in the agent-oriented programming language CAOPLE. the paper also reports controlled experiments with the debug facility. Experiment data show that the overhead is less than 3% of the execution time on average.

关键词： Software-as-a-Service Microservices Cloud native applications Integrated DevOps Environment Debug facility Continuous debugging

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