2024-03-29T10:28:20Zhttps://upcommons.upc.edu/oai/requestoai:upcommons.upc.edu:2117/882632020-07-23T23:28:25Zcom_2117_80515com_2117_23714com_2117_28578com_2117_28577col_2117_80527openAccess
SHAPE Project Vortex Bladeless: Parallel multi-code coupling for Fluid-Structure Interaction in Wind Energy Generation
Cajas García, Juan Carlos
Houzeaux, Guillaume
Yáñez, David J.
Mier-Torrecilla, Mónica
Barcelona Supercomputing Center
Àrea temàtica UPC: Enginyeria electrònica
Vortex-Bladeless
Fluid-Structure Interaction (FSI)
Wwind turbine
Alya system
Energia eòlica
Simulació, Mètodes de
Fluid-structure interaction
Wind energy conversion systems
Parallel computer programs
Vortex-Bladeless is a Spanish SME whose objective is to develop a new concept of wind turbine without blades called Vortex or vorticity wind turbine. This design represents a new paradigm in wind energy and aims to eliminate or reduce many of the existing problems in conventional generators. Due to the significant difference in the project concept, its scope is different from conventional wind turbines. It is particularly suitable for offshore configuration and it could be exploited in wind farms and in environments usually closed to existing ones due to the presence of high intensity winds.
The device is composed of a single structural component, and given its morphological simplicity, its manufacturing, transport, storage and installation has clear advantages. The new wind turbine design has no bearings, gears, etcetera, so the maintenance requirements could be drastically reduced and their lifespan is expected to be higher than traditional wind turbines.
It is clear that the proposed device is of prime interest, and that scientific investigation of the response of this wind energy generator under different operation scenarios is highly desirable. Thus, the objective of this SHAPE project is to develop the needed tools to simulate Fluid-Structure Interaction (FSI) problems and to reproduce the experimental results for scaled models of the Vortex-Bladeless device. In order to do so the Alya code, developed at the Barcelona Supercomputing Center, is adapted to perform the Fluid-Structure Interaction (FSI) problem simulation. The obtained numerical results match satisfactorily with the experimental results reported.
2016-06-23T10:08:07Z
2016-06-23T10:08:07Z
2016
External research report
http://hdl.handle.net/2117/88263
Cajas, Juan C. [et al.]. "SHAPE Project Vortex Bladeless: Parallel multi-code coupling for Fluid-Structure Interaction in Wind Energy Generation". 2016.
eng
http://www.prace-ri.eu/IMG/pdf/WP216.pdf
info:eu-repo/grantAgreement/EC/H2020/653838/EU/PRACE 4th Implementation Phase Project/PRACE-4IP
Open Access
6 p.
https://upcommons.upc.edu/bitstream/2117/88263/5/SHAPE%20Project%20Vortex%20Bladeless.pdf.jpg
oai:upcommons.upc.edu:2117/1279692022-11-13T05:56:08Zcom_2117_80515com_2117_23714com_2117_28578com_2117_28577col_2117_80527openAccess
High-Integrity GPU Designs for Critical Real-Time Automotive Systems
Alcaide, Sergi
Kosmidis, Leonidas
Hernandez, Carles
Abella Ferrer, Jaume
Barcelona Supercomputing Center
Àrea temàtica UPC: Informàtica
GPU designs
Autonomous Driving (AD)
Unitats de processament gràfic
Graphics processing units
Autonomous Driving (AD) imposes the use of highperformance hardware, such as GPUs, to perform object recognition
and tracking in real-time. However, differently to the consumer electronics market, critical real-time AD functionalities
require a high degree of resilience against faults, in line with the automotive ISO26262 functional safety standard requirements.
ISO26262 imposes the use of some source of independent redundancy for the most critical functionalities so that a single fault cannot lead to a failure, being dual core lockstep (DCLS) with diversity the preferred choice for computing devices. Unfortunately, GPUs do not support diverse DCLS by construction, thus failing to meet ISO26262 requirements efficiently.
In this paper we propose lightweight modifications to GPUs to enable diverse DCLS for critical real-time applications without diminishing their performance for non-critical applications. In particular, we show how enabling specific mechanisms for software-controlled kernel scheduling in the GPU, allows guaranteeing that redundant kernels can be executed in different resources so that a single fault cannot lead to a failure, as imposed by ISO26262. Our results on a GPU simulator and an NVIDIA GPU prove the viability of the approach and its effectiveness on high-performance GPU designs needed for AD systems.
2019-01-31T10:11:33Z
2019-01-31T10:11:33Z
2019-04-16
Conference lecture
10.23919/DATE.2019.8715177
978-3-9819263-2-3
http://hdl.handle.net/2117/127969
Alcaide, S. [et al.]. High-Integrity GPU Designs for Critical Real-Time Automotive Systems. A: "". 2019, p. 1-6.
eng
https://ieeexplore.ieee.org/document/8715177
info:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/
info:eu-repo/grantAgreement/MINECO//RYC-2013-14717/ES/RYC-2013-14717/
info:eu-repo/grantAgreement/MINECO//TIN2014-60404-JIN/ES/PROBABILISTIC TIMING ANALYSIS OF HIGH-PERFORMANCE AND RELIABLE PROCESSORS/
Open Access
6 p.
IEEE
https://upcommons.upc.edu/bitstream/2117/127969/6/High-Integrity%20GPU%20Designs%20for%20critical.pdf.jpg
oai:upcommons.upc.edu:2117/857372022-05-17T10:08:45Zcom_2117_80515com_2117_23714com_2117_28578com_2117_28577col_2117_80527openAccess
Parallel Mesh Partitioning in Alya
Technical report 202, PRACE
Artigues, Antoni
Houzeaux, Guillaume
Barcelona Supercomputing Center
Àrea temàtica UPC: Enginyeria electrònica
Variational Multiscale Finite Element Method
Alya System
Navier-Stokes
Partial Differential Equations
Simulació, Mètodes de
Simulation methods
Multiscale modeling--Computer simulation
The Alya System is the BSC simulation code for multi-physics problems [1]. It is based on a Variational Multiscale Finite Element Method for unstructured meshes.
Work distribution is achieved by partitioning the original mesh into subdomains (submeshes). This pre-partition step has until now been done in serial by only one process, using the metis library [2]. This is a huge bottleneck when larger meshes with millions of elements have to be partitioned. This is due to the data not fitting in the memory of a single computing node and in the cases where the data does fit; Alya takes too long in the partitioning step.
In this document we explain the tasks done to design, implement and test a new parallel partitioning algorithm for Alya. In this algorithm a subset of the workers, is in charge of partition the mesh in parallel, using the parmetis library [3].
Partitioning workers, load consecutive parts of the main mesh, with a parallel space partitioning bin structure [4], capable of obtaining the adjacent boundary elements of their respective submeshes. With this local mesh, each of
the partitioning workers is able to create its local element adjacency graph and to partition the mesh. We have validated our new algorithm using a Navier-Stokes problem on a small cube mesh of 1000 elements. Then we performed a scalability test on a 30M element mesh to check if the time to partition the mesh is reduced proportionally with the number of partitioning workers.
We have also done a comparison between metis and parmetis, the balancing of the element distribution among the domains, to test how the use of many partitioning workers to partition the mesh affects the scalability of Alya. We have noticed in these tests that it’s better to use fewer partitioning workers to partition the mesh.
Finally we have two sections explaining the results and the future work that has to be done in order to finalise and improve the parallel partition algorithm.
2016-04-15T10:42:42Z
2016-04-15T10:42:42Z
2015
External research report
http://hdl.handle.net/2117/85737
Artigues, Antoni; Houzeaux, Guillaume. "Parallel Mesh Partitioning in Alya". 2015.
eng
info:eu-repo/grantAgreement/EC/FP7/312763/EU/PRACE/PRACE-3IP
Open Access
11 p.
https://upcommons.upc.edu/bitstream/2117/85737/5/Parallel%20Mesh%20Partitioning%20in%20Alya.pdf.jpg
oai:upcommons.upc.edu:2117/3775112023-12-24T08:27:54Zcom_2117_15797com_2117_28577com_2117_6164com_2117_28579com_2117_80515com_2117_23714com_2117_28578com_2117_3911com_2117_80516col_2117_3055col_2117_6166col_2117_80527col_2117_3913col_2117_80534openAccess
ETP4HPC’s SRA 5 strategic research agenda for High-Performance Computing in Europe 2022: European HPC research priorities 2023-2027
Carpenter, Paul Matthew
Casas, Marc
Unsal, Osman Sabri
Radojkovic, Petar
Martorell Bofill, Xavier
Miranda, Alberto
Guitart Fernández, Jordi
Corbalán González, Julita
Peña Monferrer, Antonio José
Bautista Gomez, Leonardo Arturo
Vázquez García, Miguel
Beltran Querol, Vicenç
Queralt Calafat, Anna
Nou Castell, Ramon
Borrell Pol, Ricard
Houzeaux, Guillaume
Serradell Maronda, Kim
Carrera Pérez, David
García Sáez, Artur
Puchol García, Carlos
Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació
Barcelona Supercomputing Center
Universitat Politècnica de Catalunya. CROMAI - Computing Resources Orchestration and Management for AI
Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Services, Information and Data Engineering
Àrea temàtica UPC: Informàtica: Arquitectura de computadors
Supercomputadors
Europa
Càlcul intensiu (Informàtica)
Supercomputers
Europe
High performance computing
This document feeds research and development priorities devel-oped by the European HPC ecosystem into EuroHPC’s Research and Innovation Advisory Group with an aim to define the HPC Technology research Work Programme and the calls for proposals included in it and to be launched from 2023 to 2026.
This SRA also describes the major trends in the deployment of HPC and HPDA methods and systems, driven by economic and societal needs in Europe, taking into account the changes ex-pected in the technologies and architectures of the expanding underlying IT infrastructure. The goal is to draw a complete picture of the state of the art and the challenges for the next three to four years rather than to focus on specific technologies, implementations or solutions.
2022-12-01T08:31:13Z
2022-12-01T08:31:13Z
2022-09
External research report
https://www.etp4hpc.eu/news/300-the-etp4hpcs-sra-is-here.html
10.5281/zenodo.7347008
http://hdl.handle.net/2117/377511
Carpenter, P. [et al.]. ETP4HPC’s SRA 5 strategic research agenda for High-Performance Computing in Europe 2022: European HPC research priorities 2023-2027. 2022. DOI 10.5281/zenodo.7347008.
eng
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
Open Access
166 p.
https://upcommons.upc.edu/bitstream/2117/377511/3/ETP4HPC-SRA5_2022_web.pdf.jpg