<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-05-05T18:44:25Z</responseDate><request verb="GetRecord" identifier="oai:uvadoc.uva.es:10324/58510" metadataPrefix="etdms">https://uvadoc.uva.es/oai/request</request><GetRecord><record><header><identifier>oai:uvadoc.uva.es:10324/58510</identifier><datestamp>2023-02-06T20:00:38Z</datestamp><setSpec>com_10324_1165</setSpec><setSpec>com_10324_931</setSpec><setSpec>com_10324_894</setSpec><setSpec>col_10324_1335</setSpec></header><metadata><thesis xmlns="http://www.ndltd.org/standards/metadata/etdms/1.0/" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.ndltd.org/standards/metadata/etdms/1.0/ http://www.ndltd.org/standards/metadata/etdms/1.0/etdms.xsd">
<title>UVaFTLE: Lagrangian finite time Lyapunov exponent extraction for fluid dynamic applications</title>
<creator>Carratalá Sáez, Rocío</creator>
<creator>Torres de la Sierra, Yuri</creator>
<creator>Sierra Pallarés, José Benito</creator>
<creator>López Huguet, Sergio</creator>
<creator>Llanos Ferraris, Diego Rafael</creator>
<description>Producción Científica</description>
<description>The determination of Lagrangian Coherent Structures (LCS) is becoming very&#xd;
important in several disciplines, including cardiovascular engineering, aerodynam-&#xd;
ics, and geophysical fluid dynamics. From the computational point of view, the&#xd;
extraction of LCS consists of two main steps: The flowmap computation and the&#xd;
resolution of Finite Time Lyapunov Exponents (FTLE). In this work, we focus on&#xd;
the design, implementation, and parallelization of the FTLE resolution. We offer&#xd;
an in-depth analysis of this procedure, as well as an open source C implementation&#xd;
(UVaFTLE) parallelized using OpenMP directives to attain a fair parallel efficiency&#xd;
in shared-memory environments. We have also implemented CUDA kernels that&#xd;
allow UVaFTLE to leverage as many NVIDIA GPU devices as desired in order to&#xd;
reach the best parallel efficiency. For the sake of reproducibility and in order to con-&#xd;
tribute to open science, our code is publicly available through GitHub. Moreover, we&#xd;
also provide Docker containers to ease its usage.</description>
<date>2023-02-06</date>
<date>2023-02-06</date>
<date>2023</date>
<type>info:eu-repo/semantics/article</type>
<identifier>The Journal of Supercomputing, 2023.</identifier>
<identifier>0920-8542</identifier>
<identifier>https://uvadoc.uva.es/handle/10324/58510</identifier>
<identifier>10.1007/s11227-022-05017-x</identifier>
<identifier>The Journal of Supercomputing</identifier>
<identifier>1573-0484</identifier>
<language>eng</language>
<relation>https://link.springer.com/article/10.1007/s11227-022-05017-x</relation>
<rights>info:eu-repo/semantics/openAccess</rights>
<rights>http://creativecommons.org/licenses/by/4.0/</rights>
<rights>© 2023 The Author(s)</rights>
<rights>Atribución 4.0 Internacional</rights>
<publisher>Springer</publisher>
</thesis></metadata></record></GetRecord></OAI-PMH>