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Proceedings of the Winter Simulation Conference

作者： Alfredo González-Calvin Lía García-Perez José L. Risco-Martín Eva Besada-Portas Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid SPAIN

ISBN: (纸本)9798350369663

Harmful Algaeand Cyanobacteria Blooms(HACBs)are dangerous dynamic processes for the users/inhabitants of the hydric resources. Their development and contingency plans can be anticipated by using Autonomous Surface Vehicles (ASVs) equipped with a self-driven system capable of deciding how to displace the ASV and its multi-parametric probe to take measurements in the 3D locations of the water body where the HACB is likely to occur. This paper presents a new self-driven system for that purpose, consistent on 1) an offline trajectory planner for the ASV that exploits the information provided by a commercial HACBs simulator to optimize, in turn, the ASV horizontal and probe vertical displacements; and 2) a guidance and control system specially designed for making the ASV follow the planned trajectories. The paper also presents a comprehensive set of simulations to evaluate our proposal's performance and adjust its parameters.

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A Lake Cyanobacteria Colony Dynamics Simulation Supported by SPH

A Lake Cyanobacteria Colony Dynamics Simulation Supported by...

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Simulation Winter Conference

作者： Samuel Ferrero-Losada José L. Risco-Martín José A. López-Orozco Eva Besada-Portas Dept. of Computer Architecture and Automation Universidad Complutense de Madrid Madrid Spain

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

Addressing the prediction of Harmful Cyanobacterial Blooms (CyanoHABs) is critical due to the increasing strain on global water resources from climate change and overexploitation. This paper introduces a combined physical and biological modeling approach for simulating the 3D migration, growth, and decay of cyanobacteria colonies in water bodies. Utilizing the Smoothed Particle Hydrodynamics (SPH) method, our model accommodates complex geometries with high accuracy. This adaptable open-source framework significantly enhances the simulation of cyanobacteria migration in three dimensions, a capability often lacking in existing environmental lake simulators. Moreover, it is being integrated into an advanced early warning system, representing a digital twin of the water body. This integration aims to improve the prediction and management of CyanoHABs, contributing to safeguard water quality and ecosystem health.

关键词： Geometry Adaptation models Solid modeling Three-dimensional displays Cyanobacteria Water quality Lakes Hydrodynamics Water resources Strain

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Development of an Interface for Digital Neuromorphic Hardware Based on an FPGA

Development of an Interface for Digital Neuromorphic Hardwar...

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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, International Conference on Maintenance Engineering, IncoME-V 2023, International conference on the Efficiency and Performance Engineering Network, TEPEN 2023

作者： Harmann, René Sohlbach, Lukas Perez-Peña, Fernando Schmidt, Karsten Department of Computer Science and Engineering Frankfurt University of Applied Sciences Nibelungenplatz 1 Frankfurt60318 Germany Department of Automation Electronics and Computer Architecture and Networks School of Engineering University of Cadiz Avda. de la Universidad 10 Puerto Real11519 Spain

ISBN: (纸本)9783031494208

Exploring and understanding the functioning of the human brain is one of the greatest challenges for current research. Neuromorphic engineering tries to address this challenge by abstracting biological mechanisms and translating them into technology. Via the abstraction process and experiments with the resulting technical system, an attempt is made to obtain information about the biological counterpart. One subsection of Neuromorphic Engineering (NE) is Spiking Neural Networks (SNN), which describe the structures of the human brain more and more closely than Artificial Neural Networks (ANN). Together with their dedicated hardware, SNNs provide a good platform for developing new algorithms for information processing. In the context of these neuromorphic hardware platforms, this paper aims to develop an interface for a digital hardware platform (SPINN-3 Development Board) to enable the use of industrial or conventional sensors and thus create new approaches for experimental research. The basis for this endeavor is a Field Programmable Gate Array (FPGA), which is placed as a gateway between the sensors and the neuromorphic hardware. Overall, the developed system provides a robust solution for a wide variety of investigations related to neuromorphic hardware and SNNs. Furthermore, the solution also offers suitable possibilities to monitor all processes within the system in order to obtain suitable measurements, which can be examined in search of meaningful results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Neural networks

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Control of Microgrid Cluster Using Raspberry Pi

Control of Microgrid Cluster Using Raspberry Pi

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2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

作者： Carrasco-González, David Sarrias-Mena, Raúl Horrillo-Quintero, Pablo Llorens-Iborra, Francisco Fernández-Ramírez, Luis M. Suret Research Group Department of Electrical Engineering Algeciras Spain Uca Suret Reseach Group Dept. of Engineering in Automation Electronics and Computer Architecture and Networks Algeciras Spain

ISBN: (纸本)9781665471640

Currently, microgrid clusters (MGC) are being increasingly used owing to their benefits and human needs. MGs can be composed of power generation, consumption, and storage elements. They permit the combination of DC and AC technologies, even for a single microgrid (MG). In this paper, a new control system of a MGC consisting of two MGs connected to the main grid is developed. One of them is a DC MG that is composed of a wind turbine (WT), electrolyzer (EZ), ultracapacitor (UC), fuel cell (FC) and DC loads. The other MG is an AC MG, which is made up of a PV generator, a battery bank and AC loads. The MGC is tested under different working conditions in an experimental setup composed of a Raspberry Pi microcontroller, an OPAL-RT 4510 unit and a PC host. The experimental setup allows the system to run in real time and validate the results obtained. Finally, the control system implemented in the MGC exhibits a correct behaviour under different conditions, according to the results obtained. © 2023 IEEE.

关键词： energy management system Microgrid cluster Raspberry Pi real-time simulation

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A Suite of Division Algorithms for Posit Arithmetic

A Suite of Division Algorithms for Posit Arithmetic

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International Conference on Application Specific Systems (ASAP), architectures and Processors

作者： Raul Murillo Alberto A. Del Barrio Guillermo Botella Dept. of Computer Architecture and Automation Faculty of Physics University of Madrid Madrid Spain Dept. of Computer Architecture and Automation Faculty of Computer Science Complutense University of Madrid Madrid Spain

Posit ™ arithmetic is a promising alternative to IEEE 754 floating-point arithmetic due to its higher accuracy, larger dynamic range, and bitwise compatibility. While posit arithmetic has been well studied for basic arithmetic operations, division has received little attention. This paper proposes multiple divider designs for posit arithmetic based on digit recurrence and iterative approximation, and evaluates their performance. ASIC synthesis results show that the proposed designs significantly reduce hardware requirements for 32-bit division units compared to previous works by 1.14 × in area, 1.11× in power, and 1.04×in datapath delay. Moreover, the paper introduces an approximate logarithmic posit division that achieves an 8.8×reduction in area and 29×reduction in energy consumption with negligible degradation of the final results, making it suitable for error-tolerant applications.

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A NOVEL REAL-TIME DEVS SIMULATION architecture WITH HARDWARE-IN-THE-LOOP CAPABILITIES

A NOVEL REAL-TIME DEVS SIMULATION ARCHITECTURE WITH HARDWARE...

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2024 Annual Modeling and Simulation Conference, ANNSIM 2024

作者： Fernández-Sebastián, Óscar Cárdenas, Román Arroba, Patricia Risco-Martín, José L. Department of Computer Architecture and Automation Universidad Complutense de Madrid Spain Department of Electronic Engineering Universidad Politécnica de Madrid Spain Center for Computational Simulation Universidad Politécnica de Madrid Spain

ISBN: (纸本)9781713899310

Advanced Modelling and Simulation (M&S) techniques, including Digital Twins (DTs) and Hardware-In-the-Loop (HIL) simulation, are essential for the design and operation of today’s complex systems. Despite these advances, there remains a gap between the simulation methods used in design and those used in implementation. This paper introduces a Real-Time (RT) simulation framework that connects models using the Discrete-Event System Specification (DEVS) with external systems, improving implementation and operation. The Python xDEVS tool has been enhanced to introduce a new suite of real-time simulation components and a DEVS-based communication interface, facilitating adaptable communication protocols. The framework demonstrates its capability to integrate both DEVS and non-DEVS systems and establish effective communication through various experiments, ranging from RT simulation of DEVS models to complex multi-component systems. This tool has significant potential in supporting real and incremental system implementations through HIL techniques, making a valuable contribution to complex system design and operation. © 2024 Society for Modeling & Simulation International (SCS).

关键词： Hardware-in-the-loop simulation

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Towards the Munich Quantum Software Stack: Enabling Efficient Access and Tool Support for Quantum computers 4

Towards the Munich Quantum Software Stack: Enabling Efficien...

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4th IEEE International Conference on Quantum Computing and Engineering, QCE 2023

作者： Schulz, Martin Schulz, Laura Ruefenacht, Martin Wille, Robert Technical University of Munich Computer Architecture and Parallel Systems Munich Germany Leibniz Supercomputing Centre Qct Department Garching Germany Technical University of Munich Design Automation Munich Germany

ISBN: (纸本)9798350343236

As quantum computing systems mature and move from laboratories to production computing environments, corresponding software stacks are becoming key for their successful utilization. In particular, the expected use of quantum systems as HPC accelerators requires a deep integration with the existing and widely deployed HPC software stacks. Additionally, new requirements such as dynamic compilation and new challenges for tools and programming models must be considered. We tackle these challenges by developing the Munich Quantum Software Stack - a comprehensive initiative by the Munich Quantum Valley to offer a flexible, efficient, and user-oriented software environment. In this poster, we describe the core components and workflows, and how they will enable this transformation from quantum experiments to quantum accelerators. © 2023 IEEE.

关键词： Quantum optics

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Intelligence-Based Recommendation System for Critical Stroke Management in Intensive Care Units

Intelligence-Based Recommendation System for Critical Stroke...

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16th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2023

作者： Garcıa Terriza, Luis Risco-Martın, Jose L. Ayala, Jose L. Reig Rosello, Gemma Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid28040 Spain Stroke Care Unit Hospital Universitario de La Princesa Spain

This work presents an integrated recommendation system capable of providing support in healthcare critical environments such as Intensive Care Units or Stroke Care Units using Machine Learning techniques. The system can manage several patients by reading monitoring hemodynamic data in real-time, presenting current death risk probability, and showing recommendations that would reduce such probability and, in some cases, avoid death. This system introduces a novel method to produce recommendations based on genetic models and supervised machine learning. The interface is built upon a web application where clinicians can evaluate recommendations and straightforwardly provide feedback. © 2023 by SCITEPRESS – Science and Technology Publications, Lda

关键词： Adversarial machine learning

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Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics 24

Methodology for Online Estimation of Rheological Parameters ...

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Proceedings of the Winter Simulation Conference

作者： Juan Sandubete-López José L. Risco-Martín Alexander H. McMillan Eva Besada-Portas Dept. of Computer Architecture and Automation Universidad Complutense de Madrid Madrid SPAIN and Microfluidics Innovation Center Paris FRANCE Dept. of Computer Architecture and Automation Universidad Complutense de Madrid Madrid SPAIN Microfluidics Innovation Center Paris FRANCE

ISBN: (纸本)9798331534202

Microfluidic devices are increasingly used in biological and chemical experiments due to their cost-effectiveness for rheological estimation in fluids. However, these devices often face challenges in terms of accuracy, size, and cost. This study presents a methodology, integrating deep learning, modeling and simulation to enhance the design of microfluidic systems, used to develop an innovative approach for viscosity measurement of polymer melts. We use synthetic data generated from the simulations to train a deep learning model, which then identifies rheological parameters of polymer melts from pressure drop and flow rate measurements in a microfluidic circuit, enabling online estimation of fluid properties. By improving the accuracy and flexibility of microfluidic rheological estimation, our methodology accelerates the design and testing of microfluidic devices, reducing reliance on physical prototypes, and offering significant contributions to the field.

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Acceleration and energy consumption optimization in cascading classifiers for face detection on low-cost ARM *** asymmetric architectures

arXiv

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arXiv 2024年

作者： Corpas, Alberto Costero, Luis Botella, Guillermo Igual, Francisco D. García, Carlos Rodríguez, Manuel Dept. of Architecture and Computer Technology ETSIIT University of Granada Granada18071 Spain Dept. Computer Architecture and Automation Complutense University of Madrid Madrid28040 Spain

This paper proposes a mechanism to accelerate and optimize the energy consumption of a face detection software based on Haar-like cascading classifiers, taking advantage of the features of low-cost Asymmetric Multicore Processors (AMPs) with limited power budget. A modelling and task scheduling/allocation is proposed in order to efficiently make use of the existing features on *** ARM processors, including: (I) source-code adaptation for parallel computing, which enables code acceleration by applying the OmpSs programming model, a task-based programming model that handles data-dependencies between tasks in a transparent fashion;(II) different OmpSs task allocation policies which take into account the processor asymmetry and can dynamically set processing resources in a more efficient way based on their particular features. The proposed mechanism can be efficiently applied to take advantage of the processing elements existing on low-cost and low-energy multi-core embedded devices executing object detection algorithms based on cascading classifiers. Although these classifiers yield the best results for detection algorithms in the field of computer vision, their high computational requirements prevent them from being used on these devices under real-time requirements. Finally, we compare the energy efficiency of a heterogeneous architecture based on asymmetric multicore processors with a suitable task scheduling, with that of a homogeneous symmetric architecture. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy efficiency

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