{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"id":[{"id":"https:\/\/ror.org\/03mb6wj31","id-type":"ROR","asserted-by":"publisher"},{"id":"https:\/\/www.isni.org\/000000041937028X","id-type":"ISNI","asserted-by":"publisher"},{"id":"https:\/\/www.wikidata.org\/entity\/Q1640731","id-type":"wikidata","asserted-by":"publisher"}],"name":"Universitat Polit\u00e8cnica de Catalunya","acronym":["UPC"]}],"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T20:15:35Z","timestamp":1768853735204,"version":"3.49.0"},"reference-count":0,"publisher":"Universitat Polit\u00e8cnica de Catalunya","license":[{"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Classical geostatistical methods are based on the hypothesis of stationarity, which allows to apply repetitive sampling in different locations of the spatial domain, in order to obtain enough information to infer cumulative distributions. In case of non stationarity, anisotropy is observed in the underlying physical phenomena. This feature manifest itself as preferential directions of continuity in the phenomena, i.e. properties are more continuous in one orientation than in another. In the case of local anisotropy, each location of the domain in study presents different preferential directions of continuity. The locally varying anisotropy (LVA) approach in geostatistics allows to incorporate a field of local anisotropy parameters defined for each domain point. With this additional input, more realistic spatial simulations can be generated, including geological features to the computational model such as folds, veins, faults, among others. Since the seminal article published by Boisvert and Deutsch (2011), to the best of the author's knowledge, no further analysis or public code improvements were developed. This is in part because acceleration and parallelization techniques must be applied to the inner kernels of the baseline LVA codes. Large execution time is needed to generate small-scale domain simulations, making large-scale domain simulations a prohibitive task.\r\n\r\nThe contributions of this thesis are accelerating and parallelizing classical and LVA-based geostatistical simulation methods, particularly sequential simulation, which is one of the most common and computationally intensive methods in the field. This fact was recently remarked by some of the main authors in the field, G\u00f3mez-Hern\u00e1ndez and Srivastava (2021), which shows the relevance of this work today. Two main parallel algorithms and an optimized version of a kd-tree search implementation are presented, all of them applied to both classical and LVA-based sequential simulation implementations. The first parallel algorithm is related to the parallel simulation of different domain points, after rearranging the order of simulation but preserving the exact results of a single-thread execution. The second parallel algorithm is related to the parallel search of neighbour points in the domain, which will be used to build data dependencies for the parallel simulation of points. The optimized kd-tree search was used in each test case in order to reduce the computational complexity of neighbour search tasks. Its modified implementation reduces the number of branching instructions and introduces specialized code sections to accelerate the execution. The main focus is on multi-core architectures using OpenMP and optimization techniques applied to Fortran and C++ codes.\r\n\r\nAdditionally, acceleration and parallelization techniques were also applied to auxiliary applications, such as shortest path and variogram calculation on hybrid CPU\/GPU architectures using Fortran, C++ and CUDA codes. In the last application, an analytical and heuristic model was developed to estimate the optimal workload distribution between CPU and GPU in the hybrid context.\r\n\r\nThe overall results of this work are a set of applications that will allow researchers and practitioners to accelerate dramatically the execution of their experiments and simulations, being sgsim, sisim, sgs-lva and sisim-lva the accelerated codes presented. Final speedup results of 11x and 50x are obtained for non-LVA codes using 16 threads, and 56x and 1822x are obtained for LVA codes using 20 threads. These tools can be combined with other geostatistical tools, in order to improve the existing landscape of open source codes that can be used in practical scenarios.<\/jats:p>\n                <jats:p>Los m\u00e9todos geoestad\u00edsticos cl\u00e1sicos se basan en la hip\u00f3tesis de la estacionariedad, que permite aplicar muestreos repetitivos en diferentes lugares del dominio espacial, con el fin de obtener informaci\u00f3n suficiente para inferir distribuciones acumuladas. En caso de no estacionariedad, se observa anisotrop\u00eda en los fen\u00f3menos f\u00edsicos subyacentes. Esta caracter\u00edstica se manifiesta como direcciones preferenciales de continuidad en los fen\u00f3menos, es decir, las propiedades son m\u00e1s continuas en una orientaci\u00f3n que en otra. En el caso de la anisotrop\u00eda local, cada ubicaci\u00f3n del dominio en estudio puede presentar diferentes direcciones preferenciales de continuidad. El enfoque de anisotrop\u00eda localmente variable (LVA) en geoestad\u00edstica permite incorporar un campo de par\u00e1metros de anisotrop\u00eda locales definidos para cada punto de dominio. Con esta entrada adicional, se pueden generar simulaciones espaciales m\u00e1s realistas, incluyendo caracter\u00edsticas geol\u00f3gicas al modelo computacional como pliegues, vetas, fallas, entre otras. Desde el art\u00edculo seminal publicado por Boisvert y Deutsch (2011), seg\u00fan el conocimiento del autor, no se han desarrollado m\u00e1s an\u00e1lisis ni mejoras en el c\u00f3digo p\u00fablico. Esto se debe en parte a que se deben aplicar t\u00e9cnicas de aceleraci\u00f3n y paralelizaci\u00f3n a los n\u00facleos internos de los c\u00f3digos LVA de referencia. Se necesita mucho tiempo de ejecuci\u00f3n para generar simulaciones de dominio a peque\u00f1a escala, lo que hace que las simulaciones de dominio a gran escala sean una tarea prohibitiva. Las contribuciones de esta tesis consisten en acelerar y paralelizar m\u00e9todos de simulaci\u00f3n geoestad\u00edstica cl\u00e1sicos y basados en LVA, particularmente la simulaci\u00f3n secuencial, que es uno de los m\u00e9todos m\u00e1s comunes e intensivos en computaci\u00f3n en el campo. Este hecho fue se\u00f1alado recientemente por algunos de los principales autores en el campo, G\u00f3mez-Hern\u00e1ndez y Srivastava (2021), lo que demuestra la relevancia de este trabajo en la actualidad. Se presentan dos algoritmos paralelos principales y una versi\u00f3n optimizada de una implementaci\u00f3n de b\u00fasqueda de \u00e1rbol kd, todos ellos aplicados a implementaciones de simulaci\u00f3n secuencial cl\u00e1sicas y basadas en LVA. El primer algoritmo paralelo est\u00e1 relacionado con la simulaci\u00f3n paralela de diferentes puntos del dominio, despu\u00e9s de reorganizar el orden de simulaci\u00f3n pero conservando los resultados exactos de una ejecuci\u00f3n de un solo hilo. El segundo algoritmo paralelo est\u00e1 relacionado con la b\u00fasqueda paralela de puntos vecinos en el dominio, que se utilizar\u00e1 para resolver dependencias de datos para la simulaci\u00f3n paralela de puntos. La b\u00fasqueda optimizada de kd-tree se utiliz\u00f3 en cada caso de prueba para reducir la complejidad computacional de las tareas de b\u00fasqueda de vecinos. Su implementaci\u00f3n modificada reduce el n\u00famero de instrucciones branching e introduce c\u00f3digo especializado para acelerar la ejecuci\u00f3n. El foco principal est\u00e1 en arquitecturas multi-n\u00facleo usando OpenMP y t\u00e9cnicas de optimizaci\u00f3n aplicadas a c\u00f3digos Fortran y C++. Adem\u00e1s, tambi\u00e9n se aplicaron t\u00e9cnicas de aceleraci\u00f3n y paralelizaci\u00f3n a aplicaciones auxiliares, como el c\u00e1lculo de la ruta m\u00e1s corta en un grafo y el c\u00e1lculo de variogramas en arquitecturas h\u00edbridas CPU\/GPU utilizando c\u00f3digos Fortran, C++ y CUDA. En la \u00faltima aplicaci\u00f3n, se desarroll\u00f3 un modelo anal\u00edtico y heur\u00edstico para estimar la distribuci\u00f3n \u00f3ptima de la carga de trabajo entre CPU y GPU en el contexto h\u00edbrido. Los resultados generales de este trabajo son un conjunto de aplicaciones que permitir\u00e1n a los investigadores y profesionales acelerar la ejecuci\u00f3n de sus experimentos, siendo sgsim, sisim, sgs-lva y sisim-lva los c\u00f3digos acelerados. Se obtienen resultados finales de aceleraci\u00f3n de 11x y 50x para c\u00f3digos que no son LVA usando 16 hilos, y se obtienen 56x y 1822x para c\u00f3digos LVA usando 20 hilos. Estas herramientas se pueden combinar con otras herramientas geoestad\u00edcas<\/jats:p>","DOI":"10.5821\/dissertation-2117-369087","type":"dissertation","created":{"date-parts":[[2023,7,19]],"date-time":"2023-07-19T02:25:48Z","timestamp":1689733548000},"approved":{"date-parts":[[2022,6,9]]},"source":"Crossref","is-referenced-by-count":0,"title":["Large scale geostatistics with locally varying anisotropy"],"prefix":"10.5821","author":[{"sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oscar Francisco","family":"Peredo Andrade","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"3865","container-title":[],"original-title":[],"deposited":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T06:38:33Z","timestamp":1768804713000},"score":1,"resource":{"primary":{"URL":"https:\/\/hdl.handle.net\/2117\/369087"}},"subtitle":[],"editor":[{"given":"Jos\u00e9 Ram\u00f3n","family":"Herrero Zaragoza","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[null]]},"references-count":0,"URL":"https:\/\/doi.org\/10.5821\/dissertation-2117-369087","relation":{},"subject":[]}}