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检索条件"任意字段=12th Euromicro Conference on Parallel, Distributed and Network-Based Processing"

共 1249 条记录，以下是161-170 订阅

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Deep Learning at Scale 27

Deep Learning at Scale

引用

27th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Viviani, Paolo Drocco, Maurizio Baccega, Daniele Colonnelli, Iacopo Aldinucci, Marco Noesis Solut NV Leuven Belgium Univ Torino Dept Comp Sci Turin Italy Pacific Northwest Natl Lab Richland WA 99352 USA

ISBN: (纸本)9781728116440

this work presents a novel approach to distributed training of deep neural networks (DNNs) that aims to overcome the issues related to mainstream approaches to data parallel training. Established techniques for data parallel training are discussed from both a parallel computing and deep learning perspective, then a different approach is presented that is meant to allow DNN training to scale while retaining good convergence properties. Moreover, an experimental implementation is presented as well as some preliminary results.

关键词： Training parallel processing Neural networks Convergence Computational modeling Data models Deep learning

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Arbor - a morphologically-detailed neural network simulation library for contemporary high-performance computing architectures 27

Arbor - a morphologically-detailed neural network simulation...

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27th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Akar, Nora Abi Cumming, Ben Karakasis, Vasileios Kuesters, Anne Klijn, Wouter Peyser, Alexander Yates, Stuart CSCS Sci Software & Lib Zurich Switzerland Forschungszentrum Julich SimLab Neurosci JSC IAS Julich Germany

ISBN: (纸本)9781728116440

We introduce Arbor, a performance portable library for simulation of large networks of multi-compartment neurons on HPC systems. Arbor is open source software, developed under the auspices of the HBP. the performance portability is by virtue of back-end specific optimizations for x86 multicore, Intel KNL, and NVIDIA GPUs. When coupled with low memory overheads, these optimizations make Arbor an order of magnitude faster than the most widely used comparable simulation software. the single-node performance can be scaled out to run very large models at extreme scale with efficient weak scaling.

关键词： HPC GPU neuroscience neuron software

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A MapReduce based tool for the analysis and discovery of novel therapeutic targets 27

A MapReduce based tool for the analysis and discovery of nov...

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27th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Parasiliti, Giuseppe Pennisi, Marzio Biondi, Pietro Sgroi, Giuseppe Russo, Giulia Napoli, Christian Pappalardo, Francesco Univ Catania Dept Math & Comp Sci Catania Italy Univ Catania Dept Biomed & Biotechnol Sci Catania Italy Univ Catania Dept Drug Sci Catania Italy

ISBN: (纸本)9781728116440

We present here a novel algorithm based on a MapReduce approach to facilitate the discovery of novel therapeutic targets. the proposed algorithm has been enabled to scan a set biological pathways in order to discover non-trivial ( less common) routes. Such routes represent a chain of biochemical interactions among different biological actors. these actors can be represented by quite distant nodes along the devised pathway. Our approach detects nodes that are far from the initial target nodes, also showing the number of times that a given route has been found inside the selected set of biological pathways.

关键词： MapReduce Biochemical Pathway therapeutic target gene MAPK1 Python

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Research on computer network security load balancing algorithm based on diversity feedback 12

Research on computer network security load balancing algorit...

引用

12th International conference on Measuring Technology and Mechatronics Automation, ICMTMA 2020

作者： Kong, Dewu Department of Information Engineering Henan College of Industry and Information Technology Jiaozuo Henan454000 China

ISBN: (数字)9781728170817

ISBN: (纸本)9781728170817

the cascade distributed computer network is subjected to multi-path interference, which leads to poor balance. a secure load balancing transmission model based on diversity feedback is proposed, the channel model of transmission symbol sequence dynamic link distribution in cascade distributed computer network is constructed, and the inter-symbol interference suppression of cascade distributed computer network is carried out by using autocorrelation cascade filtering detection method. the high-order statistical features of the network transmission symbol sequence are extracted, the diversity feedback control is carried out according to the symbol interval of the feature distribution, the secure load balancing processing of the computer network is realized by combining the diversity feedback control method, and the secure load balancing transmission control of the cascade distributed computer network is realized by using the channel spread spectrum modulation method. the simulation results show that the dynamic load transmission of cascade distributed computer network is balanced, the anti-interference ability between symbols is strong, and the output bit error rate and distortion are reduced. © 2020 IEEE.

关键词： Feedback control

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Deep Reinforcement Learning for distributed Computation Offloading in Massive-user Mobile Edge networks 12

Deep Reinforcement Learning for Distributed Computation Offl...

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12th International conference on Wireless Communications and Signal processing (WCSP)

作者： Jiang, Bo Li, Kuikui Zhou, Bo Tao, Meixia Chen, Zhiyong Shanghai Jiao Tong Univ Dept Elect Engn Shanghai Peoples R China Virginia Tech Wireless VT Bradley Dept Elect & Comp Engn Blacksburg VA USA

ISBN: (纸本)9781728172361

this work investigates the distributed task offloading problem in a mobile edge computing network with a massive number of users and one single base station (BS). Each user can decide, in a distributed manner, whether to compute its task locally or to offload to a common edge server equipped at the BS for execution. If edge computing, the user transmits its task data along with a unique but potentially non-orthogonal pilot sequence to the BS using a grant-free multiple-access scheme, and then the BS detects the offloading user and decodes the task data. the missed-detection case may occur, in which the missed-detection probability increases with the total number of offloading users. thus, the offloading decision of each user depends highly on the decisions of all other users. More specifically, if the number of users that decide to offload increases, the risk that each user is miss-detected becomes higher, resulting in extra system cost compared with local computing only. To solve this issue, we apply Deep Q-network (DQN) on each user and assume that the user can perceive the actions of other users in the last time slot as the observed state. then, users make decisions on task computation only based on the local task parameters and few information broadcasted by the BS. the simulation results demonstrate that the algorithm can significantly minimize the system computation cost and show remarkable advantages when the number of user is large.

关键词： Mobile edge computing computation offloading massive users deep Q-network

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A Dynamic Task-based D3Q19 Lattice-Boltzmann Method for Heterogeneous Architectures 27

A Dynamic Task-based D3Q19 Lattice-Boltzmann Method for Hete...

引用

27th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Lima, Joao V. F. Freytag, Gabriel Pinto, Vinicius Garcia Schepke, Claudio Navaux, Philippe O. A. Univ Fed Rio Grande do Sul Porto Alegre RS Brazil Univ Fed Santa Maria Santa Maria RS Brazil Univ Fed Pampa Campus Alegrete Alegrete Brazil

ISBN: (纸本)9781728116440

Nowadays computing platforms expose a significant number of heterogeneous processing units such as multicore processors and accelerators. the task-based programming model has been a de facto standard model for such architectures since its model simplifies programming by unfolding parallelism at runtime based on data-flow dependencies between tasks. Many studies have proposed parallel strategies over heterogeneous platforms with accelerators. However, to the best of our knowledge, no dynamic task-based strategy of the Lattice-Boltzmann Method (LBM) has been proposed to exploit CPU+GPU computing nodes. In this paper, we present a dynamic task-based D3Q19 LBM implementation using three runtime systems for heterogeneous architectures: OmpSs, StarPU, and XKaapi. We detail our implementations and compare performance over two heterogeneous platforms. Experimental results demonstrate that our task-based approach attained up to 8.8 of speedup over an OpenMP parallel loop version.

关键词： Task analysis Runtime Graphics processing units Computational modeling parallel processing Programming Computer architecture

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GPU parallelization of realistic Purkinje cells with complex morphology 27

GPU parallelization of realistic Purkinje cells with complex...

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27th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Torti, Emanuele Florimbi, Giordana Ticli, Marta Masoli, Stefano D'Angelo, Egidio Leporati, Francesco Univ Pavia Dept Elect Comp & Biomed Engn Pavia Italy Univ Pavia Dept Brain & Behav Sci Pavia Italy

ISBN: (纸本)9781728116440

High performance computing (HPC) is becoming mandatory for the simulation of complex and realistic neuronal models. the development of such realistic models will allow to discover innovative therapies and to study brain diseases without undertaking invasive experiments that are not always possible. However, the models complexity requires adopting suitable technologies in order to provide results in short times, hopefully in real-time. To address this issue, the authors decided to exploit Graphics processing Units (GPUs) in order to develop a realistic and morphologically detailed Purkinje cell model. this paper describes the simulation of the Purkinje cell activity adopting both single and multi-GPU strategy, together with the exploitation of different NVIDIA architectures. Results shows that the simulation times of 10000 cells is reduced from 13 days and 18 hours to about 2 hours.

关键词： Graphics processing units Computational modeling Cerebellar neuron simulation Biological system modeling Neuroscience

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A Radio Environment Mapping based Spectrum Awareness for Cognitive Space Information network with GEO and LEO Coexistence 12

A Radio Environment Mapping Based Spectrum Awareness for Cog...

引用

12th International conference on Wireless Communications and Signal processing (WCSP)

作者： Wang, Haitao Ren, Rongkai Qu, Dexin Zhang, Gengxin Nanjing Univ Posts & Commun Coll Telecommun & Informat Engn Nanjing Peoples R China

ISBN: (纸本)9781728172361

Cognitive radio provides a promising solution for contradiction between increasing service requirements and spectrum resource scarcity in space information network. A novel algorithm of space-borne spectrum awareness based on radio environment mapping (REM) with a hybrid dual-threshold approach of spectrum sensing (SS) is proposed for coexistence of geostationary earth orbit (GEO) incumbent down-links and low earth orbit (LEO) cognitive up-links in this paper. the constructed hybrid SS approach integrates single-node energy detector and equal-gain combining, and provides a good trade-off between the design complexity and the SS accuracy of a LEO cognitive system in an environment with highly uncertain noise. In addition, the concept of cognitive satellite position (CSP) is proposed to deal with negative effect of sparsely distributed LEO cognitive nodes and to enable space-borne hybrid SS and REM according to rapid movement of the LEO cognitive nodes. Spatial detection probability and spatial false alarm probability are drawn into the work to indicate spatial reliability of our space-based REM. the numerical results show that the created hybrid dual-threshold SS approach is robust to highly uncertain noise environment, and that the dynamic REM approach based on the SS results at LEO CSPs could provide spectrum awareness at the considered scenario with high spatial reliability. Furthermore, a simulated instance of space-borne REM application under GEO and LEO coexistence is afforded and an instructive observation from this instance is discussed. the work here offers fundamental support for spectrum sharing of space information network.

关键词： cognitive radio space information network radio environment mapping spectrum sensing spectrum sharing

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parallel Searching on Biological networks 27

Parallel Searching on Biological Networks

引用

27th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Bombieri, Nicola Bonnici, Vincenzo Giugno, Rosalba Univ Verona Dipartimento Informat Strata Grazie 15 I-37134 Verona Italy

ISBN: (纸本)9781728116440

Software applications for biological networks analysis rely on graphs to model the structure interactions. A great part of them requires searching for subgraphs in a target graph or in collections of graphs. Even though very efficient algorithms have been defined to solve such a subgraph isomorphisms problem, the complexity of current real biological networks make their sequential execution time prohibitive. On the other hand, parallel architectures, from multi-core to many-core, have become pervasive to deal with the problem of the data size. Nevertheless, the sequential nature of the graph searching algorithms makes their implementation for parallel architectures very challenging. this paper presents three different parallel solutions for the graph searching problem. the first two target the exact search for multi-core CPUs and many-core GPUs, respectively. the third one targets the approximate search for GPUs, which handles node, edge, and node label mismatches. the paper shows how different techniques have been developed in all the solutions to reduce the search space complexity. the paper shows the performance of the proposed solutions on representative biological networks containing antiviral chemical compounds and protein interactions networks.

关键词： Biology Search problems Complexity theory Graphics processing units Indexes Topology

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Stream parallelism on the LZSS Data Compression Application for Multi-Cores with GPUs 27

Stream Parallelism on the LZSS Data Compression Application ...

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27th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Stein, Charles Michael Griebler, Dalvan Danelutto, Marco Fernandes, Luiz Gustavo Tres de Maio Fac SETREM LARCC Tres De Maio Brazil Pontifical Catholic Univ Rio Grande Sul PUCRS Sch Technol Porto Alegre RS Brazil Univ Pisa UNIPI Dept Comp Sci Pisa Italy

ISBN: (纸本)9781728116440

GPUs have been used to accelerate different data parallel applications. the challenge consists in using GPUs to accelerate stream processing applications. Our goal is to investigate and evaluate whether stream parallel applications may benefit from parallel execution on both CPU and GPU cores. In this paper, we introduce new parallel algorithms for the Lempel-Ziv-Storer-Szymanski (LZSS) data compression application. We implemented the algorithms targeting both CPUs and GPUs. GPUs have been used with CUDA and OpenCL to exploit inner algorithm data parallelism. Outer stream parallelism has been exploited using CPU cores through SPar. the parallel implementation of LZSS achieved 135 fold speedup using a multi-core CPU and two GPUs. We also observed speedups in applications where we were not expecting to get it using the same combine data-stream parallel exploitation techniques.

关键词： Graphics processing units Microsoft Windows Data compression Libraries parallel algorithms Acceleration

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