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检索条件"任意字段=19th International Symposium on Parallel and Distributed Computing, ISPDC 2020"

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Proceedings - 2020 19th international symposium on parallel and distributed computing, ispdc 2020

Proceedings - 2020 19th International Symposium on Parallel ...

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19th international symposium on parallel and distributed computing, ispdc 2020

ISBN: (纸本)9781728189468

the proceedings contain 24 papers. the topics discussed include: robustness analysis of scaled resource allocation models using the imperial PEPA compiler;on-the-fly optimization of parallel computation of symbolic symplectic invariants;evaluation of SIMD instructions on bio-inspired algorithms;dynamic load balancing based on multi-objective extremal optimization;distributed and fault-tolerant construction of low stretch spanning tree;hybrid workflow provisioning and scheduling on edge cloud computing using a gradient descent search approach;accelerated implementation of FQSqueezer novel genomic compression method;and performance analysis and evaluation of Java-based InfiniBand solutions.

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19th IEEE international symposium on parallel and distributed Processing with Applications, 11th IEEE international Conference on Big Data and Cloud computing, 14th IEEE international Conference on Social computing and Networking and 11th IEEE international Conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021

19th IEEE International Symposium on Parallel and Distribute...

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19th IEEE international symposium on parallel and distributed Processing with Applications, 11th IEEE international Conference on Big Data and Cloud computing, 14th IEEE international Conference on Social computing and Networking and 11th IEEE international Conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021

ISBN: (纸本)9781665435741

the proceedings contain 222 papers. the topics discussed include: DRL-deploy: adaptive service function chains deployment with deep reinforcement learning;accuracy vs. efficiency: achieving both through hardware-aware quantization and reconfigurable architecture with mixed precision;cmss: collaborative modeling of safety and security requirements for network protocols;FGPA: fine-grained pipelined acceleration for depthwise separable CNN in resource constraint scenarios;Dyacon: JointCloud dynamic access control model of data security based on verifiable credentials;understanding the runtime overheads of deep learning inference on edge devices;and alleviating imbalance in synchronous distributed training of deep neural networks.

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Proceedings. 19th IEEE international parallel and distributed Processing symposium

Proceedings. 19th IEEE International Parallel and Distribute...

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international symposium on parallel and distributed Processing (IPDPS)

作者： R.F. van der Wijngaart M. Frumkin V.C. Bhavsar E. Aubanel T. Kielmann Vrije Univ. Amsterdam

HIPS-HPGC 2005 is a full-day workshop, focusing on high-performance grid computing and high-level parallel programming models. the papers deal with component models and service-based systems for grids, emphasizing on experiences with existing systems. Also the papers report on the state of the art of grid applications, both for academic and industrial problems

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Scalable State Space Search on the GPU with Multi-Level parallelism 19

Scalable State Space Search on the GPU with Multi-Level Para...

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19th international symposium on parallel and distributed computing (ispdc)

作者： Shipovalov, Egor Pryanichnikov, Valentin Sensorika Intl Lab Moscow Russia Keldysh Inst Appl Math Moscow Russia

ISBN: (纸本)9781728189468

Modern GPUs offer an accessible and scalable supercomputing platform. However, their use for state-space search has so far been auxiliary or in niche methods such as iterative deepening A* or random walks. We describe a scalable deterministic A* state space search implementation running entirely on the GPU. this is made possible by designing core algorithms for lock-step parallelism as well as using CUDA cooperative grids to implement hash-distributed A* load balancing scheme. Comparative benchmarking showed significant improvements in performance as well as resource efficiency.

关键词： state space search A* automated planning model checking parallel computation GPU GPGPU CUDA

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Semantically Correct and Intent Defined Commutativity in distributed Systems 19

Semantically Correct and Intent Defined Commutativity in Dis...

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19th international symposium on parallel and distributed computing (ispdc)

作者： Robinson, Courtney Univ Greenwich Dept Comp & Informat Syst London England

ISBN: (纸本)9781728189468

this paper reviews the problem of correctness in the context of scaleable distributed systems. It takes the concept of a strongly eventually consistent (SEC) data structure based on the work done on conflict free replicated data types and examines the theoretical basis of a practical application to generalised database management systems. It reasons that the condition required for a database management system to implement a monotonic semilattice and remain generic is not possible. It further proposes a framework which extends the SEC condition to capture enough information to make such a system practical to implement. Finally, it evaluates such an implementation using a modified storage engine for Apache Ignite demonstrating not just its practicality but its scaleability in Ignite and other database management systems like it. the key contributions of this work are Semantic and intent defined conflict free replicated data types, an enriched CRDT which enables generalised database systems to meet the SEC criteria for a monotonic semilattice object and Semantic Intent Configuration Language, SICL, a language and framework for distributed computing.

关键词： Semantics

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On-the-fly Optimization of parallel Computation of Symbolic Symplectic Invariants 19

On-the-fly Optimization of Parallel Computation of Symbolic ...

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19th international symposium on parallel and distributed computing (ispdc)

作者： Ben Geloun, Joseph Coti, Camille Malony, Allen D. Univ Sorbonne Paris Nord LIPN CNRS UMR7030 F-93430 Villetaneuse France Univ Oregon Eugene OR 97403 USA

ISBN: (纸本)9781728189468

Group invariants are used in high energy physics to define quantum field theory interactions. In this paper, we present the parallel algebraic computation of special invariants called symplectic and focus on one particular invariant that finds recent interest in physics. Our results will export to other invariants. the cost of performing basic computations on the multivariate polynomials evolves during the computation, as the polynomials get larger and/or have increasing numbers of terms. Interestingly, in some cases, they stay small. Traditionally, high-performance software is optimized by running experiments with sample data sets in order to profile and optimize expected behavior of workloads in practice. Since the (communication and computation) costs depend on the changing behavior of the symplectic invariant calculations, the standard optimization approach is insufficient. thus, it is necessary to implement online performance tuning methods that can track the algorithm's progress and state, evaluate performance data in situ, and control the parallel resources during execution.

关键词： High energy physics

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Efficient parallel Shortest Path Algorithms 19

Efficient Parallel Shortest Path Algorithms

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19th international symposium on parallel and distributed computing (ispdc)

作者： Alves, David R. Krishnakumar, Madan S. Garg, Vijay K. Univ Texas Austin Dept Elect & Comp Engn Austin TX 78712 USA

ISBN: (纸本)9781728189468

Finding the shortest path between nodes in a graph has wide applications in many important areas such as transportation and computer networks. However, the current reference algorithms for this task, Dijkstra's for single threaded environments and Delta-stepping for multi-threaded ones, leave performance and efficiency on the table by not taking advantage of additional information available about the graph. In this paper we present and experimentally evaluate novel algorithms SP1, SP2 and ParSP(2) that leverage these constraints to solve the problem faster and more efficiently in key metrics. In single threaded execution, we show how SP1 and SP2 out-perform Dijsktra's algorithm by up to 46%. In multi-threaded execution we show how our algorithms compare favorably to Delta-stepping algorithm in the ability to establish the shortest path between the source and the median node.

关键词： Single Source Shortest Path Problem Dijkstra's Algorithm

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Optimal Matrix Partitioning for Data parallel computing on Hybrid Heterogeneous Platforms 19

Optimal Matrix Partitioning for Data Parallel Computing on H...

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19th international symposium on parallel and distributed computing (ispdc)

作者： Malik, Tania Lastovetsky, Alexey Sch Comp Sci UCD Dublin Ireland

ISBN: (纸本)9781728189468

In this paper, we study the problem of partitioning a matrix over a small number of interconnected heterogeneous processors. this problem is crucial for data parallel dense linear algebra and other applications with similar communication patterns on modern hybrid servers, integrating several heterogeneous compute devices such as CPUs, GPUs and other accelerators. the objective is to balance the load of the heterogeneous devices while minimising the communication cost. While the problem has been solved for the case of two processors, it is still open for three and more processors. the state-of-the-art solution for the case of three processors uses a communication cost function, which does not accurately account for the total amount of data moved between processors and therefore leaves the question of its global optimality open. In this work, we propose a cost function, which accurately represents the total amount of data moved between processors. then, we formulate and solve the problem of optimal partitioning of a square computational domain, using this accurate communication cost function. Finally, we propose and implement an original experimental methodology for accurate measurement of the communication time of parallel applications on hybrid heterogeneous servers, integrating multi-core CPUs and various accelerators. We apply this methodology to experimental validation of our mathematical result.

关键词： Matrix multiplication data partitioning hybrid platforms heterogeneous platforms non-rectangular partitioning optimal partitioning communication optimization data parallelism

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Accelerated implementation of FQSqueezer novel genomic compression method 19

Accelerated implementation of FQSqueezer novel genomic compr...

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19th international symposium on parallel and distributed computing (ispdc)

作者： Amich, Monica De Luca, Pasquale Fiscale, Stefano Univ Campania Luigi Vanvitelli DiSTABiF Caserta Italy Univ Salerno Dept Comp Sci Fisciano Italy Univ Naples Parthenope Dept Sci & Technol Naples Italy

ISBN: (纸本)9781728189468

Biological data contain very important information for genoma analysis. In last decades, the size of these data is constantly growing. So the Next Generation Sequence (NGS) data has been introduced. these kind of data are represented by different data formats, such as FASTQ, FASTA, SAM, etc. In order to allow a good analysis and storing of them, due to large dimension of these data, several compressors have been performed. FQSqueezer is a novel genomic compressor for FASTQ data files. But several issues are present due to multithread version that runs on multi-core hardware. It is well-known that the number of cores in a CPU is limited and very minor with respect to GPUs' cores number. In order to increase the performance related to this compressor method, in this work we present a GPU-parallel implementation of cited compressor by exploiting CUDA framework. More precisely, a suitable domain decomposition is able to give an appreciable gain of performance in terms of time and reliability. Several execution tests confirm the gain of efficiency achieved by our parallel implementation.

关键词： Next Generation Sequence parallel algorithm GPU genomic compression FASTQ

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Generating Minimal Nondeterministic Finite Automata Using a parallel Algorithm 19

Generating Minimal Nondeterministic Finite Automata Using a ...

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19th international symposium on parallel and distributed computing (ispdc)

作者： Jastrzab, Tomasz Czech, Zbigniew J. Wieczorek, Wojciech Silesian Tech Univ Dept Algorithm & Software Gliwice Poland Silesia Univ Katowice Fac Sci & Technol Katowice Poland

ISBN: (纸本)9781728189468

the goal of this paper is to develop a parallel algorithm that, on input of a learning sample, identifies a regular language by means of a nondeterministic finite automaton (NFA). A sample is a pair of finite sets containing positive and negative examples. Given a sample, a minimal NFA or the range of possible sizes of such an NFA, that represents the target regular language is sought. We define the task of finding an NFA, which accepts all positive examples and rejects all negative ones, as a constraint satisfaction problem, and then propose a parallel algorithm to solve the problem. the results of computational experiments on the variety of test samples are reported.

关键词： parallel algorithm learning regular languages using nondeterministic finite automata constraint satisfaction and satisfiability problems grammatical inference

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