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检索条件"任意字段=International Conference on Embedded Computer Systems Architectures Modeling and Simulation"

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Confronting machine-learning with neuroscience for neuromorphic architectures design

Confronting machine-learning with neuroscience for neuromorp...

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international Joint conference on Neural Networks

作者： Lyes Khacef Nassim Abderrahmane Benoit Miramond University Côte d’Azur / LEAT / CNRS UMR 7248 Sophia Antipolis France

Artificial neural networks are experiencing today an unprecedented interest thanks to two main changes: the explosion of open data that is necessary for their training, and the increasing computing power of today's computers that makes the training part possible in a reasonable time. The recent results of deep neural networks on image classification has given neural networks the leading role in machine learning algorithms and artificial intelligence research. However, most applications such as smart devices or autonomous vehicles require an embedded implementation of neural networks. Their implementation in CPU/GPU remains too expensive, mostly in energy consumption, due to the non-adaptation of the hardware to the computation model, which becomes a limit to their use. It is therefore necessary to design neuromorphic architectures, i.e. hardware accelerators that fit to the parallel and distributed computation paradigm of neural networks for reducing their hardware cost implementation. We mainly focus on the optimization of energy consumption to enable integration in embedded systems. For this purpose, we implement two models of artificial neural networks coming from two different scientific domains: the multi-layer perceptron derived from machine learning and the spiking neural network inspired from neuroscience. We compare the performances of both approaches in terms of accuracy and hardware cost to find out the most attractive architecture for the design of embedded artificial intelligence.

关键词： Neurons Biological neural networks Hardware Biological system modeling computer architecture Computational modeling Brain modeling

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Design of Polymorphic Real-Time Computational Model for UAV Application

Design of Polymorphic Real-Time Computational Model for UAV ...

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international conference on computer and Information Science (ACIS)

作者： Mei Luo Linlin Li Baocheng Wang Kailong Zhang Computer Lab Research Inst. Of Hi-Tech Xi’an China School of Computer Northwest Polytechnical University Xi’an China

According to the requirements of informational weapon equipment, the application of polymorphic real-time computation technology in complex embedded system is studied in this paper. The polymorphic real-time computation model for unmanned aerial vehicle(UAV) is designed and verified from the aspects of modal management and polymorphic tasks. The simulation results show that the proposed model can provide modal decision and ensure its real-time calculation to adapt the demand change of UAV system.

关键词： Task analysis Real-time systems Computational modeling computer architecture Unmanned aerial vehicles Adaptation models Target tracking

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Designing and Executing Software architectures Models Using SysADL Studio

Designing and Executing Software Architectures Models Using ...

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Software Architecture Companion (ICSA-C)

作者： Jair Leite Thais Batista Flavio Oquendo Eduardo Silva Lidiane Santos Victor Cortez Department of Computer Science Federal University of Rio Grande do Norte Natal Brazil IRISA - UMR CNRS University of South Britanny Vannes France

This paper introduces SysADL Studio, an architecture modeling tool for software-intensive systems that implements the SysADL language. The tool supports multiple views, cross-view checking, and architecture execution simulation. In SysADL Studio, the architect can design a system using a combination of graphical and textual notations and simulate the execution of the designed architecture using a built-in model simulator. SysADL Studio is a free, open-source tool implemented as a plug-in for Eclipse IDE using well-established frameworks (EMF, Xtext, and Sirius). The tool contributes to the advance of the current architecture design practice by supporting a syntactically correct model, reuse of standard architectural elements, and execution simulation at design-time. The rigorous formalism that grounds the language is also implemented by the tool in an extensive manner, allowing the architect to simulate a model behavior in a controlled environment. It has been successfully used in an academic environment in the last years, by students and researchers in Brazil and France that have evaluated the tool in controlled experiments.

关键词： Unified modeling language Tools Resource management Biological system modeling computer architecture Semantics Connectors

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Optimizing Task Assignment with Minimum Cost on Heterogeneous embedded Multicore systems Considering Time Constraint 3

Optimizing Task Assignment with Minimum Cost on Heterogeneou...

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IEEE 3rd international conference on Big Data Security on Cloud (BigDataSecurity) / 3rd IEEE international conference on High Performance and Smart Computing (HPSC) / 2nd IEEE international conference on Intelligent Data and Security (IDS)

作者： Zheng, Hua Zhang, Xi Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Peoples R China

ISBN: (纸本)9781509062966

Time and cost are the most critical performance metrics for computer systems including embedded system, especially for the battery-based embedded systems, such as PC, mainframe computer, and smart phone. Most of the previous work focuses on saving energy in a deterministic way by taking the average or worst scenario into account. However, such deterministic approaches usually are inappropriate in modeling energy consumption because of uncertainties in conditional instructions on processors and time-varying external environments. Through studying the relationship between energy consumption, execution time and completion probability of tasks on heterogeneous multi-core architectures this paper proposes an optimal energy efficiency and system performance model and the OTHAP (Optimizing Task Heterogeneous Assignment with Probability) algorithm to address the Processor and Voltage Assignment with Probability (PVAP) problem of data-dependent aperiodic tasks in real-time embedded systems, ensuring that all the tasks can be done under the time constraint with a guaranteed probability. We adopt a task DAG (Directed Acyclic Graph) to model the PVAP problem. We first use a processor scheduling algorithm to map the task DAG onto a set of voltage-variable processors, and then use our dynamic programming algorithm to assign a proper voltage to each task and The experimental results demonstrate our approach outperforms state-of-the-art algorithms in this field (maximum improvement of 24.6%).

关键词： Heterogeneous embedded Multicore System Minimum Cost Time Constraint Guaranteed Probability Energy Efficiency Task Assignment

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Short Course: Efficient Alternatives and Extensions to Deep-Learning-Based Solutions

Short Course: Efficient Alternatives and Extensions to Deep-...

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IEEE international conference on Solid-State Circuits (ISSCC)

作者： Naveen Verma Princeton University Princeton NJ

ISBN: (数字)9781509049400

ISBN: (纸本)9781538622278

Deep-learning systems have had profound impacts in a broad range of applications. However, it is important to remember that these represent only one class ofmachine learning. In this segment of the short course, we start by probing what the critical attributes are of deep learning, and what challenges in modeling andinference they solve. We then go on to consider the limitations of deep learning in emerging applications involving on-line learning (e.g. reinforcement learningwith embedded sensors) - namely the need for a large number of training instances and the need for very low energy. This motivates alternatives or extensions todeep learning, which make use of other forms of learning to enhance training and energy efficiency. Given the need for very low energy in many applications, weexplore how the statistical-learning can enable new hardware architectures, substantially overcoming the tradeoffs limiting conventional architectures for sensingand computation. Finally, having examined how algorithmic techniques can enhance systems, we look at how systems, and emerging technologies for sensing,can enhance algorithms. As an illustration, we consider how object-associated sensing, as enabled by IoT devices, has the potential to provide semantic structure,leading to features that can enhance the generalization of learning with simpler and easier-to-train models.

关键词： Tutorials Radio frequency Wireless communication Transceivers Solid state circuits Quantum computing Optical transmitters computer architecture Wireless sensor networks Training

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Towards modeling Cyber-Physical systems with SysML/MARTE/pCCSL

Towards Modeling Cyber-Physical Systems with SysML/MARTE/pCC...

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IEEE Annual international computer Software and Applications conference (COMPSAC)

作者： Ping Huang Kaiqiang Jiang Chunlin Guan Dehui Du Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China

ISBN: (纸本)9781538626672

Cyber-Physical systems (CPS) are networks of heterogeneous embedded systems immersed within a physical environment. modeling such heterogeneous systems is actively researched. However, there still lacks a systematic approach to model characteristics of CPS. To solve the problem, we propose a flexible co-modeling approach that relies on SysML/MARTE/pCCSL to capture different aspects of CPS, including structure, behavior, clock constraints and NFP. The novelty of our approach lies in the use of logical clocks and SysML/MARTE/pCCSL to drive and coordinate different models, which supports a standard language-based modeling for CPS. To capture the characteristics of CPS such as stochastic behavior and continuous behavior, we extend some meta-models of SysML/MARTE. For the block diagram, we extend it with four new stereotypes of blocks and the type of model. We adopt a new stereotype FMIConnection to describe the information transmission between blocks, which denotes that the blocks will be exported as corresponding FMU components. It will be of great benefit to the co-simulation of CPS. For the state machine diagram, we attach Ordinary Differential Equation (ODE) and TimedDelay to a state, which models the continuous behavior and stochastic time delay. The consistency between various models is specified with pCCSL. To implement our approach, we develop the toolset based on GEMOC. Finally, to demonstrate the feasibility of our co-modeling approach, we present some multi-view models of an energy-aware building as a case study.

关键词： Unified modeling language Mathematical model Clocks Stochastic processes Computational modeling computer architecture Buildings

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A distributed cellular approach of large scale SOM models for hardware implementation

A distributed cellular approach of large scale SOM models fo...

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international Image Processing, Applications and systems conference (IPAS)

作者： Laurent Rodriguez Lyes Khacef Benoît Miramond University Côte d’Azur / LEAT / CNRS UMR 7248 France

ISBN: (纸本)9781728102481;9781728102474

Self-organization is a powerful bio-inspired feature that has been poorly investigated in the context of hardware computing architectures. The neural foundations of brain self-organization enable structural plasticity, continuous learning, and tolerance to lesions but at the cost of massive lateral synaptic connections. A cellular formulation of the related neural models would be able to tackle this limitation by iterating the propagation of the information in the network. This paper introduces the SOMA hardware architecture, which relies on this principle to develop a Self-Organizing Machine Architecture. We show the benefits of our cellular implementation compared to the existing neural models. This contribution leads to a hardware compliant algorithm thanks to decentralized operations and communications. A generalization of the technique is proposed to implement different Kohonen-like self-organizing models. This particular cellular implementation reaches the same behavior as the centralized models but drastically reduces their computing complexity. We present the performance results and discuss the benefits of cellular computing approaches in the perspective of designing hardware neural processors for embedded applications.

关键词： Neurons computer architecture Self-organizing feature maps Hardware Computational modeling Synapses Biological neural networks

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COMPASS: An Efficient GPU-based simulation Software for Adaptive Optics systems

COMPASS: An Efficient GPU-based Simulation Software for Adap...

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international conference on High Performance Computing & simulation (HPCS)

作者： Florian Ferreira Damien Gratadour Arnaud Sevin Nicolas Doucet Observatoire de Paris LESIA Univ. Paris Diderot Meudon France

ISBN: (纸本)9781538678800

For ground-based astronomical telescopes, Image resolution is directly dependent on aperture diameter. Practically however, atmospheric turbulence disturbs incoming wavefronts and sets dramatic limitations on imaging quality, which issue led to using Adaptive Optics (AO) systems to compensate wavefront disturbance and achieve optimal resolution. With the arrival of Extremely Large Telescopes, with aperture diameter above 20 meters, High Performance Computing (HPC) techniques are required to simulate and operate AO systems. With the advent of General Purpose Graphics Processing Units (GPGPU), many-core architectures of GPUs can be leveraged to accelerate AO simulation software. COMPASS (COMputing Platform for Adaptive opticS System) is an end-to-end AO simulation soft¬ware based upon Nvidia's Compute Unified Device Architecture (CUDA) toolkit. simulations performed on state-of-the-art Nvidia DGX-1 servers equipped with 8 Tesla V100-SXM2 and Dual 20- core Intel Xeon E5-2698 v4 show a speed up factor of up to 362 as compared to YAO, a feature-equivalent software with multi¬threaded CPU architecture. The COMPASS implementation ensures compatibility with any Nvidia architecture. A speed up by 5 was measured between a DGX-1 and a comparable server with 6-year old GPUs, with no line of code changed.

关键词： Telescopes Computational modeling Compass Graphics processing units Adaptive optics computer architecture

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A Mobile Platform for Model-Based Monitoring of Glucose-Insulin Homeostasis for Diabetics

A Mobile Platform for Model-Based Monitoring of Glucose-Insu...

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IEEE international conference on Connected Health: Applications, systems and Engineering Technologies (CHASE)

作者： Christian Tolks Christoph Ament Claudia Eberle Faculty of Applied Computer Science Augsburg University Augsburg Germany Dep. of Nursing and Health Sciences Fulda University of Applied Sciences Fulda Germany

ISBN: (纸本)9781538672075;9781538672068

This paper presents an embedded platform for a mobile model-based monitoring system for patients with type 1 or type 2 diabetes. The demonstrator consists of blood glucose and continuous glucose measurement sensors available on the market. Recordings from these devices are transmitted and stored automatically by an open source mobile application. The main feature is a model-based simulation environment including a mathematical model of the glucose-insulin homeostasis. State estimation provides a real-time estimate of the patient's status such as plasma glucose or plasma insulin concentrations. These information can be used for alerts, predictions, and closed-loop approaches to support patients in their daily diabetes management.

关键词： Sugar Mathematical model Computational modeling Insulin Homeostasis Monitoring Diabetes

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***: A Programming Framework for Sea Ice Model Algorithms Based on Sunway Many-core Processor 28

***: A Programming Framework for Sea Ice Model Algorithms Ba...

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28th IEEE international conference on Application-specific systems, architectures and Processors (ASAP)

作者： Li, Binyang Li, Bo Qian, Depei Beihang Univ Sino German Joint Software Inst Dept Comp Sci & Engn Beijing 100191 Peoples R China

ISBN: (纸本)9781509048250

Sea ice model is a typical high performance computing problem. CPU and GPU based parallel method has been proposed to accelerate the simulation process, but it is still hard to meet the large-scale calculation demand due to the compute-intensive nature of the model. Sunway TaihuLight supercomputer use the SW26010 processor as its computing unit and achieves high performance for large-scale scientific computing. In this paper we present a programming framework (***) for sea ice model algorithms based on Sunway many-core processor. Based on this framework, programmer can exploit the parallelism of existing sea ice model algorithms and achieve good performance. Several strategies are introduced to this framework, data dividing, data transfer as well as the load balance are the main aspects we currently concerned. This framework has been implemented and tested with two sea ice model algorithms by using real world dataset on Sunway many-core processors. The experiment demonstrates comparable performance to the traditional parallel implementation on Sunway many-core processor and our framework improves the performance up to 40%.

关键词： Sea ice Data transfer Computational modeling Bandwidth Programming computer architecture

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