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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181-190 订阅

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Real-time cortical simulations: energy and interconnect scaling on distributed systems 27

Real-time cortical simulations: energy and interconnect scal...

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

作者： Simula, Francesco Pastorelli, Elena Paolucci, Pier Stanislao Martinelli, Michele Lonardo, Alessandro Biagioni, Andrea Capone, Cristiano Capuani, Fabrizio Cretaro, Paolo De Bonis, Giulia Lo Cicero, Francesca Pontisso, Luca Vicini, Piero Ammendola, Roberto Ist Nazl Fis Nucl Sez Roma Rome Italy Sapienza Univ Rome PhD Program Behav Neurosci Rome Italy Ist Nazl Fis Nucl Sez Tor Vergata Rome Italy Univ Roma Tor Vergata Dept Elect Engn Rome Italy

ISBN: (纸本)9781728116440

We profile the impact of computation and inter-processor communication on the energy consumption and on the scaling of cortical simulations approaching the real-time regime on distributed computing platforms. Also, the speed and energy consumption of processor architectures typical of standard HPC and embedded platforms are compared. We demonstrate the importance of the design of low-latency interconnect for speed and energy consumption. the cost of cortical simulations is quantified using the Joule per synaptic event metric on both architectures. Reaching efficient real-time on large scale cortical simulations is of increasing relevance for both future bio-inspired artificial intelligence applications and for understanding the cognitive functions of the brain, a scientific quest that will require to embed large scale simulations into highly complex virtual or real worlds. this work stands at the crossroads between the WaveScalES experiment in the Human Brain Project (HBP), which includes the objective of large scale thalamo-cortical simulations of brain states and their transitions, and the ExaNeSt and EuroExa projects, that investigate the design of an ARM-based, low-power High Performance Computing (HPC) architecture with a dedicated interconnect scalable to million of cores;simulation of deep sleep Slow Wave Activity (SWA) and Asynchronous aWake (AW) regimes expressed by thalamo-cortical models are among their benchmarks.

关键词： neural network real-time energy-to-solution interconnect scaling distributed computing

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Using network Emulation to study Blockchain distributed Systems: the Ethereum Case 27

Using Network Emulation to study Blockchain Distributed Syst...

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

作者： Geier, Maximiliano Tessone, Claudio J. Vanotti, Marco Vilerino, Silvio Gonzalez Marquez, David Mocskos, Esteban Univ Buenos Aires Fac Ciencias Exactas & Nat Comp Sci Dept C1428EGA Buenos Aires DF Argentina CSC CONICET C1425FQD RA-2390 Godoy Cruz Buenos Aires Argentina Univ Zurich URPP Social Networks Andreasstr 15 CH-8050 Zurich Switzerland

ISBN: (纸本)9781728116440

Large-scale distributed systems are becoming more widespread and, at the same time, their sizes grow day by day. In this type of systems, the adoption of blockchains is gaining particular traction for data storage in a secure and distributed manner. Nevertheless, design and testing of new protocols and features face the challenge of determining whether the proposed modifications would actually improve the system as expected. In the case of existing cryptocurrency systems, building an evaluation platform poses additional difficulties due to the resource-consuming nature of the associated processes. In this paper, we propose a novel methodology that relies on container-based network emulation to create scalable local testbeds in which Proof-of-Work-based blockchain systems can be evaluated. Using one of the mainstream Ethereum clients, we replaced the mining algorithm with a simulation model built upon the statistical characteristics of the mining process and instrumented the client to capture relevant network events. these events are used to create an offline reconstruction of the global view of the blockchain and all forking events, and to completely characterize the working conditions under arbitrary setups. based on the versatility and scalability of our platform, we are able to test several network scenarios of increasing size in which we analyze the incidence of the target time in the generation of contradictory views of the blockchain (i.e. forks). We show that even using a limited testbed constituted by just commodity hardware, it is possible to use our platform to study the dynamics of blockchain-based systems up to hundreds of nodes.

关键词： Global Positioning System Optical fibers Hafnium compounds

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Learning-based Dynamic Pinning of parallelized Applications in Many-Core Systems 27

Learning-based Dynamic Pinning of Parallelized Applications ...

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

作者： Chasparis, Georgios C. Janjic, Vladimir Rossbory, Michael Hammond, Kevin Software Competence Ctr Hagenberg GmbH Softwarepk 21 A-4232 Hagenberg Austria Univ St Andrews Sch Comp Sci St Andrews Fife Scotland

ISBN: (纸本)9781728116440

this paper introduces a learning-based framework for dynamic placement of threads of parallel applications to the cores of Non-Uniform Memory Access (NUMA) architectures. Adaptation takes place in two levels, where at the first level each thread independently decides on which group of cores (NUMA node) it will execute, and on the second level it decides to which particular core from the group it will be pinned. Naturally, these two adaptation levels run on different time-scales: a low-frequency switching for the NUMA-node adaptation, and a high-frequency switching for the CPU-node level adaptation. In addition, the learning dynamics have been designed to handle measurement noise and rapid variations in the performance of the threads. the advantage of the proposed learning scheme is the ability to easily incorporate any multi-objective criterion and easily adapt to performance variations during runtime. Our objective is to demonstrate that this framework is appropriate for supervising parallel processes and intervening with respect to better resource allocation. Under the multi-objective criterion of maximizing total completed instructions per second (i.e., both computational and memory-access instructions), we compare the performance of the proposed scheme with the Linux operating system scheduler. We have observed that performance improvement could be significant especially under limited availability of resources and under irregular memory-access patterns.

关键词： Instruction sets Optimization Switches Computer architecture Scheduling Current measurement Resource management

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Impact of Workload Distribution on Energy Consumption, Performance, and Reliability of Heterogeneous Devices 27

Impact of Workload Distribution on Energy Consumption, Perfo...

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

作者： Davila, Gabriel Piscoya Oliveira, Daniel Navaux, Philippe Rech, Paolo Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (纸本)9781728116440

Devices integrating cores of different nature in the same chip achieve very high computation efficiency by reducing the power consumption and latencies of moving data from a chip to an external device. Heterogeneous devices are commonly used in high performance computing applications and, lately, their market has expanded from portable and gaming to safety-critical applications. In this paper, we evaluate how the collaborative workload distribution impact the energy consumption, performance, and reliability of heterogeneous devices. then, we use the Energy-Delay-Fit Product (EDFP) to evaluate the trade off between the measured metrics and find how they correlate. To perform the proposed study we consider AMD Accelerated processing Units (APUs) that embed a CPU and a GPU. We run four applications, each one representing an algorithm class, gradually distributing the workload from the CPU to the GPU and measuring both the energy consumption and execution time. then, we take advantage of accelerated neutron beams to measure the realistic error rates of the different workload distributions. As we show in the paper, energy consumption and execution time are mold by the same trend while FIT rates highly depend on algorithm class and workload distribution. Additionally, we found that execution time is the most influencing factor for the device EDFP. the application EDFP varies of up tp 6 orders of magnitude depending on the workload distribution. An unwise configuration can then jeopardize the device efficiency and reliability.

关键词： Reliability Energy consumption Error analysis Performance evaluation Graphics processing units Central processing Unit

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HEATS: Heterogeneity- and Energy-Aware Task-based Scheduling 27

HEATS: Heterogeneity- and Energy-Aware Task-based Scheduling

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

作者： Rocha, Isabelly Gottel, Christian Felber, Pascal Pasin, Marcelo Rouvoy, Romain Schiavoni, Valerio Univ Neuchatel Neuchatel Switzerland Inria Lille Nord Europe Lille France

ISBN: (纸本)9781728116440

Cloud providers usually offer diverse types of hardware for their users. Customers exploit this option to deploy cloud instances featuring GPUs, FPGAs, architectures other than x86 (e.g., ARM, IBM Power8), or featuring certain specific extensions (e.g., Intel SGX). We consider in this work the instances used by customers to deploy containers, nowadays the de facto standard for micro-services, or to execute computing tasks. In doing so, the underlying container orchestrator (e.g., Kubernetes) should be designed so as to take into account and exploit this hardware diversity. In addition, besides the feature range provided by different machines, there is an often overlooked diversity in the energy requirements introduced by hardware heterogeneity, which is simply ignored by default container orchestrator's placement strategies. We introduce HEATS, a new task-oriented and energy-aware orchestrator for containerized applications targeting heterogeneous clusters. HEATS allows customers to trade performance vs. energy requirements. Our system first learns the performance and energy features of the physical hosts. then, it monitors the execution of tasks on the hosts and opportunistically migrates them onto different cluster nodes to match the customer-required deployment trade-offs. Our HEATS prototype is implemented within Google's Kubernetes. the evaluation with synthetic traces in our cluster indicate that our approach can yield considerable energy savings (up to 8.5%) and only marginally affect the overall runtime of deployed tasks (by at most 7%). HEATS is released as open-source.

关键词： Task analysis Heating systems Hardware Containers Scheduling Monitoring Runtime

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Model-based Reconfiguration Planning for a distributed On-board Computer 12

Model-Based Reconfiguration Planning for a Distributed On-bo...

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12th System Analysis and Modelling conference, SAM 2020, collocated with the 23rd International conference on Model-Driven Engineering and Systems, MODEL 2020

作者： Kovalov, Andrii Vishav, Vishav Franz, Tobias Gerndt, Andreas Watolla, Hannes Lüdtke, Daniel Institute for Software Technology Braunschweig Germany University of Bremen Bremen Germany

ISBN: (纸本)9781450381406

the ScOSA project (Scalable On-board Computing for Space Avionics) of the German Aerospace Center aims at combining radiation hardened space hardware together with unreliable, but high performance COTS (commercial off-the-shelf) components as the processing nodes in a heterogeneous on-board network in order to provide future space missions with the necessary processing capabilities. However, such a system needs to cope with node failures. Our approach is to use a static reconfiguration graph that controls how software tasks are mapped to the processing nodes, and how this mapping should change in response to possible node failures. In this paper we present a model-based approach and a tool for automatic generation of reconfiguration graphs. based on the software and hardware models, we traverse the graph of all possible failure situations. For every node of this graph we solve a combinatorial optimization problem of mapping tasks to processing nodes either with an SMT solver or using a genetic algorithm. the resulting reconfiguration graph can then be translated into the configuration files that are deployed on the target system, eliminating the need for tedious and error-prone manual configuration design. © 2020 Copyright held by the owner/author(s).

关键词： Mapping

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A Partitioning GPU-based Algorithm for processing the k Nearest-Neighbor Query 20

A Partitioning GPU-based Algorithm for Processing the k Near...

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12th International conference on Management of Digital EcoSystems

作者： Velentzas, Polychronis Vassilakopoulos, Michael Corral, Antonio Univ Thessaly Dept Elect & Comp Engn Data Structuring & Engn Lab Volos Greece Univ Almeria Dept Informat Almeria Spain

ISBN: (纸本)9781450381154

the kappa Nearest-Neighbor (kappa-NN) query is a common spatial query that appears in several big data applications. Typically, GPU devices have much larger numbers of processing cores than CPUs and faster device memory than main memory accessed by CPUs, thus, providing higher computing power. We propose and implement a new GPU-based partitioning algorithm for the kappa-NN query, using the CUDA runtime API. Due to partitioning, this algorithm avoids calculating distances for the whole dataset. Using synthetic and real datasets, we present an extensive experimental performance comparison against six existing algorithms. these algorithms are based on calculating distances for the whole in-memory dataset. this comparison shows that the new algorithm excels in all the conducted experiments and outperforms these six algorithms.

关键词： k Nearest-Neighbor Query GPU algorithms Spatial query Partitioning algorithms parallel computing

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Continuous QoE Prediction based on WaveNet 2020

Continuous QoE Prediction Based on WaveNet

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12th International conference on Computer and Automation Engineering (ICCAE)

作者： Phan Xuan Tan tho Nguyen Duc Chanh Minh Tran Kamioka, Eiji Shibaura Inst Technol SIT Res Labs Tokyo Japan Shibaura Inst Technol Grad Sch Engn & Sci Tokyo Japan

ISBN: (纸本)9781450376785

Continuous QoE prediction is crucial in the purpose of maximizing viewer satisfaction, by which video service providers could improve the revenue. Continuously predicting QoE is challenging since it requires QoE models that are capable of capturing the complex dependencies among QoE influence factors. the existing approaches that utilize Long-Short-Term-Memory (LSTM) network successfully model such long-term dependencies, providing the superior QoE prediction performance. However, the inherent drawback of sequential computing of LSTM will result in high computational cost in training and prediction tasks. Recently, WaveNet, a deep neural network for generating raw audio waveform, has been introduced. Immediately, it gains a great attention since it successfully leverages the characteristic of parallel computing of causal convolution and dilated convolution to deal with time-series data (e.g., audio signal). Being inspired by the success of WaveNet, in this paper, we propose WaveNet-based QoE model for continuous QoE prediction in video streaming services. the model is trained and tested upon on two publicly available databases, namely, LFOVIA Video QoE and LIVE Mobile Stall Video II. the experimental results demonstrate that the proposed model outperforms the baselines models in terms of processing time, while maintaining sufficient accuracy.

关键词： Video Streaming Quality of Experience (QoE) WaveNet Causal Convolution Deep Learning LSTM PixelCNN

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Practical parallelization of Scientific Applications

Practical Parallelization of Scientific Applications

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euromicro conference on parallel, distributed and network-based processing

作者： Valentina Cesare Iacopo Colonnelli Marco Aldinucci Physics and Computer Science Departments University of Turin Turin Italy

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

this work aims at distilling a systematic methodology to modernize existing sequential scientific codes with a limited re-designing effort, turning an old codebase into modern code, i.e., parallel and robust code. We propose an automatable methodology to parallelize scientific applications designed with a purely sequential programming mindset, thus possibly using global variables, aliasing, random number generators, and stateful functions. We demonstrate the methodology by way of an astrophysical application, where we model at the same time the kinematic profiles of 30 disk galaxies with a Monte Carlo Markov Chain (MCMC), which is sequential by definition. the parallel code exhibits a 12 times speedup on a 48-core platform.

关键词： parallel processing Data models parallel programming Tools Software Task analysis

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An Intelligent CFAR Algorithm based on Multi-strategy Fusion 12

An Intelligent CFAR Algorithm Based on Multi-strategy Fusion

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12th International conference on Digital Image processing (ICDIP)

作者： Ouyang, Siyuan Tang, Jun Yang, Wenming Liao, Qingmin Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)9781510638464

Constant false alarm rate (CFAR) detection is an important method which is widely used in radar automatic detection. However, the performance of CFAR detection degrades dramatically in non-homogeneous environment because of the existence of interference targets and clutter in the reference window of the test cell. To the end, an intelligent multi-strategy fusion (IMSF) CFAR detection algorithm is proposed in this paper. By combining the preprocessing results of FOCA-CFAR, BOCA-CFAR and OSVI-CFAR, IMSF-CFAR can utilize more suitable independent, identically distributed reference cells than conventional CFAR method, which means better detection performance. the simulation results reveal that the IMSF-CFAR maintains stable detection performance both in the homogeneous and heterogeneous environments.

关键词： Radar target detection multi-strategy fusion intelligent clutter partitioning multi-target detection

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