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检索条件"任意字段=21st International Symposium on Computer Architecture and High Performance Computing"

共 1769 条记录，以下是421-430 订阅

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Active blanket jamming identification method based on rough set and decision tree

Active blanket jamming identification method based on rough ...

引用

international symposium on Distributed computing and Applications to Business, Engineering and Science (DCABES)

作者： Jianghu Chen Yian Liu Hailing Song School of AI and Computer Science Jiangnan University Wuxi China Naval Research Institute Beijing China

ISBN: (纸本)9781665454636

Aiming at the classification or identification problem of active blanket jamming, a jamming identification method is proposed, which combines the upper approximation set, lower approximation set, border set theory of rough set and decision tree. The method first extracts the time-domain features of the signals, and divides the training set according to the degree of noise impact of the sample to train the decision tree respectively; then, the noise detection of the jamming signals is carried out by using the rough set theory; finally, the identification of three typical jamming patterns is realized through the decision tree. The comparison of simulation experiments shows that compared with the traditional method, this method has higher recognition accuracy, good real-time performance and noise robustness.

关键词： Training Rough sets Feature extraction Real-time systems Pattern recognition Noise robustness Decision trees

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Implementing a Scalable and Elastic computing Environment Based on Cloud Containers 21st

Implementing a Scalable and Elastic Computing Environment Ba...

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21st international Conference on Computational Science and Its Applications (ICCSA)

作者： Perri, Damiano Simonetti, Marco Tasso, Sergio Ragni, Federico Gervasi, Osvaldo Univ Florence Dept Math & Comp Sci Florence Italy Univ Perugia Dept Math & Comp Sci Perugia Italy Univ Perugia Informat Syst Div Perugia Italy

ISBN: (纸本)9783030866532;9783030866525

In this article we look at the potential of cloud containers and we provide some guidelines for companies and organisations that are starting to look at how to migrate their legacy infrastructure to something modern, reliable and scalable. We propose an architecture that has an excellent relationship between the cost of implementation and the benefits it can bring, based on the "Pilot Light" topology. The services are reconfigured inside small docker containers and the workload is balanced using load balancers that allow horizontal autoscaling techniques to be exploited in the future. By generating additional containers and utilizing the possibilities given by load balancers, companies and network systems experts may model and calibrate infrastructures based on the projected number of users. Containers offer the opportunity to expand the infrastructure and increase processing capacity in a very short time. The proposed approach results in an easily maintainable and fault-tolerant system that could help and simplify the work in particular of small and medium-sized organisations.

关键词： high availability Docker Load balancing Elastic computing Disaster recovery high performance computing Public cloud Private cloud Hybrid cloud

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Adaptive Regularization in ANN for Condition Monitoring and Fault Detection in Heavy-duty Hydraulic Machines

Adaptive Regularization in ANN for Condition Monitoring and ...

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IEEE international Conference on Cognitive Informatics

作者： Maryam Ghanbari Witold Kinsner Nariman Sepehri Department of Mechanical Engineering Department of Electrical and Computer Engineering University of Manitoba Winnipeg Canada

This paper presents an extended architecture of an artificial neural network (ANN) to enhance the detection of internal leakage in a single-rod energy-efficient electro-hydrostatic actuator (ERA). The goal is to monitor and identify the level of internal leakage in this type of actuator. A novel scheme based on a 3-layer ANN algorithm is proposed that can detect actuator leakage faults at various levels - low, medium, and high. The algorithm aims to maximize the efficacy of fault detection using an adaptive regularization technique. Experimental results show that the new algorithm detects internal leakage as low as 0.5 L/min with over 90% accuracy. It can also recognize the severity of fault level (low, medium or severe) with over 80% confidence. Cognitive informatics drives the algorithms used in this scheme through data acquisition, pertinent data selection, training, classification, decision-making, and performance enhancements.

关键词： Training Actuators Fault detection Decision making Artificial neural networks Hydraulic systems Energy efficiency

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Optimal Decomposable QAM Constellations for Minimizing Symbol-error Probability

Optimal Decomposable QAM Constellations for Minimizing Symbo...

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IEEE international symposium on Parallel and Distributed Processing with Applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Brett Wiens Daniel C. Lee School of Engineering Science Simon Fraser University Burnaby Canada

This paper presents signal space constellations that minimize symbol-error probability in an uncoded communications system. We develop a modified projected gradient optimization method to solve for these constellations that scales efficiently, enabling the optimization of very large constellations. The optimized constellation shapes show significant improvements in symbol-error probability over a wide range of channel conditions compared with uniformly-spaced constellations. At high SNR, small deviations from uniform spacing can make substantial improvements in system performance. These results have promising applications to low-complexity systems with real-time data transmission requirements.

关键词： Gradient methods Limiting Shape Quadrature amplitude modulation System performance Symbols Ubiquitous computing

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Placement Optimization for NoC-Enhanced FPGAs

Placement Optimization for NoC-Enhanced FPGAs

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Annual IEEE symposium on Field-Programmable Custom computing Machines (FCCM)

作者： Srivatsan Srinivasan Andrew Boutros Fatemehsadat Mahmoudi Vaughn Betz Department of Electrical and Computer Engineering University of Toronto Toronto ON Canada

Field-programmable gate array (FPGA) architectures have recently incorporated hardened networks-on-chip (NoCs) to enable more efficient and easier system-level integration. However, the embedding of hard NoCs presents a new challenge for FPGA computer-aided design (CAD); the tools need to optimize the placement of circuit netlist primitives to not only minimize total wirelength and critical path delay, but also consider the NoC traffic patterns between modules to minimize their aggregate bandwidth and/or meet latency constraints. This work enables flexible modeling of FPGA architectures with hard NoCs in the open-source versatile place & route (VPR) CAD flow, facilitating both CAD and architecture research. We enhance the placement engine in VPR to co-optimize traditional circuit implementation metrics (e.g. wirelength, critical path delay) and NoC performance metrics (e.g. congestion, bandwidth utilization, latency) when mapping an application design with NoC-attached modules to a candidate NoC-enhanced FPGA architecture. We test our VPR enhancements using a variety of synthetic benchmarks and verify that the placement engine can effectively optimize NoC aggregate bandwidth and meet specified latency constraints. Then, we present a complete flow that integrates VPR with a high-level SystemC architecture simulator, RAD-Sim, that can capture the NoC traffic flows of complete application designs and use it to drive VPR's placement optimizations. We showcase this combined flow using a real application design from the deep learning domain. The results show that our NoC-enhanced VPR flow can result in 2x reduction in NoC aggregate bandwidth (on average) compared to a NoC-agnostic flow, without affecting the design's wirelength or critical path delay.

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AutoSketch: automatic sketch-oriented compiler for query-driven network telemetry 24

AutoSketch: automatic sketch-oriented compiler for query-dri...

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Proceedings of the 21st USENIX symposium on Networked Systems Design and Implementation

作者： Haifeng Sun Qun Huang Jinbo Sun Wei Wang Jiaheng Li Fuliang Li Yungang Bao Xin Yao Gong Zhang National Key Laboratory for Multimedia Information Processing School of Computer Science Peking University Institute of Computing Technology CAS Northeastern University China Huawei Theory Department

ISBN: (纸本)9781939133397

Recent network telemetry witnesses tremendous progress in two directions: query-driven telemetry that targets expressiveness as the primary goal, and sketch-based algorithms that address resource-accuracy trade-offs. In this paper, we propose AutoSketch that aims to integrate the advantages of both classes. In a nutshell, AutoSketch automatically compiles high-level operators into sketch instances that can be readily deployed with low resource usage and incur limited accuracy drop. However, there remains a gap between the expressiveness of high-level operators and the underlying realization of sketch algorithms. AutoSketch bridges this gap in three aspects. First, AutoSketch extends its interface derived from existing query-driven telemetry such that users can specify the desired telemetry accuracy. The specified accuracy intent will be utilized to guide the compiling procedure. Second, AutoSketch leverages various techniques, such as syntax analysis and performance estimation, to construct efficient sketch instances. Finally, AutoSketch automatically searches for the most suitable parameter configurations that fulfill the accuracy intent with minimum resource usage. Our experiments demonstrate that AutoSketch can achieve high expressiveness, high accuracy, and low resource usage compared to state-of-the-art telemetry solutions.

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Scenario Approach for Parametric Markov Models 21st

Scenario Approach for Parametric Markov Models

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21st international symposium on Automated Technology for Verification and Analysis, ATVA 2023

作者： Liu, Ying Turrini, Andrea Hahn, Ernst Moritz Xue, Bai Zhang, Lijun State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Institute of Intelligent Software Guangzhou Guangzhou China Formal Methods and Tools University of Twente Enschede Netherlands

ISBN: (纸本)9783031453281

In this paper, we propose an approximating framework for analyzing parametric Markov models. Instead of computing complex rational functions encoding the reachability probability and the reward values of the parametric model, we exploit the scenario approach to synthesize a relatively simple polynomial approximation. The approximation is probably approximately correct (PAC), meaning that with high confidence, the approximating function is close to the actual function with an allowable error. With the PAC approximations, one can check properties of the parametric Markov models. We show that the scenario approach can also be used to check PRCTL properties directly – without synthesizing the polynomial at first hand. We have implemented our algorithm in a prototype tool and conducted thorough experiments. The experimental results demonstrate that our tool is able to compute polynomials for more benchmarks than state-of-the-art tools such as PRISM and storm, confirming the efficacy of our PAC-based synthesis. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Polynomial approximation

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Comprehensive Analysis of Computational and I/O Resource Patterns Across Queues

Comprehensive Analysis of Computational and I/O Resource Pat...

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international Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Huang Bin Xian Gang University Of Electronic Science And Technology Of China Chengdu China College of Computer Science and Technology National University of Defense Technology Changsha China

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

In the current computing landscape, with the explosive growth of computing tasks, effective job resource utilization is of utmost importance for enhancing system performance. This study conducts a comprehensive analysis of job resource usage, focusing on the running time of job queues, core and memory resource utilization, and the characteristic distribution of job read-write I/O. Using a dataset containing 51,987 jobs from the Gaia Cluster over 3 months, we explore various aspects. The running time analysis reveals that different queues have distinct job runtime distributions. For instance, the interactive queue has a significant proportion of short-runtime jobs (30%-40%) for rapid data operations and long-runtime jobs (30 % -40 % ) for complex tasks. The normal queue is dominated by medium-runtime jobs (50 % -60 % ) to balance resource utilization. Core resource usage shows a trend where medium-core jobs are predominant (60%-80%) across queues due to factors like task complexity and cost-effectiveness. Memory usage is closely related to runtime, with medium-memory jobs corresponding to medium runtime and large-memory jobs having longer runtimes. In terms of I/O, the interactive queue has a high proportion of read-intensive and write-intensive jobs, while the normal queue is mainly write-intensive. These findings provide a detailed understanding of job resource usage patterns and offer practical guidance for optimizing computing systems.

关键词： Runtime System performance Memory management Wavelet analysis Throughput Real-time systems Complexity theory Resource management Queueing analysis Optimization

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performance Portability of Generated Cardiac Simulation Kernels Through Automatic Dimensioning and Load Balancing on Heterogeneous Nodes

Performance Portability of Generated Cardiac Simulation Kern...

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IEEE international symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Vincent Alba Olivier Aumage Denis Barthou Raphaël Colin Marie-Christine Counilh stéphane Genaud Amina Guermouche Vincent Loechner Arun Thangamani LaBRI University of Bordeaux CNRS Bordeaux INP Inria Talence France Bordeaux INP Talence France ICube Lab. University of Strasbourg CNRS Inria Strasbourg France

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

Electrophysiology simulation applications, such as the community-developed openCARP framework for in-silico experiments, involve applying a broad range of ionic model kernels with different computational weights and arithmetic intensity characteristics. Efficiently processing such kernels on modern heterogeneous architectures necessitates to accurately dimension the set of computing resources to use and to actively balance the load on the available computing units, to account for discrepancies in kernel duration and distinct computing unit speeds. We thus propose the following contributions: 1) the adaptation of an existing load-balancing algorithm to transparently manage the mapping of these ionic model kernels onto the heterogeneous units of a computing node; 2) a resource dimensioning heuristic that constraints the number of devices that should be used to maximize efficiency, according to the selected ionic models' computational weight; 3) the integration of these mechanisms in openCARP, building on prior work that took advantage of LLVM's MLIR framework to generate multiple device-specialized variants of kernels from ionic models expressed in openCARP's high-level DSL; 4) a thorough experimentation of the mechanisms on a comprehensive series of 30 ionic models provided by openCARP. The experiments show that when using the combination of the load-balancing algorithm and the resource dimensioning heuristic to compute each ionic model, the geometric mean of speedup is 9.97× with respect to the original multi-threaded code on an architecture with two A100 GPUs and 2× 32-cores AMD Zen3 CPUs.

关键词： Adaptation models Energy consumption Computational modeling Heuristic algorithms computer architecture Load management Kernel

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Optimization of Resources Allocation in high performance computing Under Utilization Uncertainty 1

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21st international Conference on Computational Science, ICCS 2021

作者： Toporkov, Victor Yemelyanov, Dmitry Grigorenko, Maksim National Research University "MPEI" Ul. Krasnokazarmennaya 14 Moscow111250 Russia

ISBN: (数字)9783030779801

ISBN: (纸本)9783030779795

In this work, we study resources co-allocation approaches for a dependable execution of parallel jobs in high performance computing systems with heterogeneous hosts. Complex computing systems often operate under conditions of the resources availability uncertainty caused by job-flow execution features, local operations, and other static and dynamic utilization events. At the same time, there is a high demand for reliable computational services ensuring an adequate quality of service level. Thus, it is necessary to maintain a trade-off between the available scheduling services (for example, guaranteed resources reservations) and the overall resources usage efficiency. The proposed solution can optimize resources allocation and reservation procedure for parallel jobs’ execution considering static and dynamic features of the resources’ utilization by using the resources availability as a target criterion. © 2021, Springer Nature Switzerland AG.

关键词： Resource allocation

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