{"id":56610,"date":"2018-03-09T22:44:25","date_gmt":"2018-03-09T22:44:25","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/optimizacion-de-la-transformada-wavelet-explotacion-de-paralelismo-de-grano-fino\/"},"modified":"2018-03-09T22:44:25","modified_gmt":"2018-03-09T22:44:25","slug":"optimizacion-de-la-transformada-wavelet-explotacion-de-paralelismo-de-grano-fino","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/optimizacion-de-la-transformada-wavelet-explotacion-de-paralelismo-de-grano-fino\/","title":{"rendered":"Optimizaci\u00f3n de la transformada wavelet. explotaci\u00f3n de paralelismo de grano fino"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Christian Tenllado Van Der Reijden <\/strong><\/h2>\n<p>Esta tesis aborda la explotaci\u00f3n eficiente de paralelismo de datos en la transformada wavelet discreta en dos dimensiones (2d-dwt). Concretamente se centra en el uso de extensiones multimedia para la vectorizaci\u00f3n de sus dos algoritmos principales, el piramidal de mallat y el esquema lifting de sweldens, y en la explotaci\u00f3n del paralelismo de datos mediante procesamiento de flujos en unidades gr\u00e1ficas programables (gpus).     inicialmente se realiza un minucioso an\u00e1lisis del comportamiento de la memoria para reducir la presi\u00f3n de los procesados verticales sobre la jerarqu\u00eda de memoria delos procesadores superscalares de la familia intel. Esto permite desarrollar algunas estrategias novedosas para la optimizaci\u00f3n dela localidad de los dos algorimtos, que adem\u00e1s resultan indispensable para la explotaci\u00f3n eficiente del paralelismo simd mediante extensiones multimedia.     las estrategias de sectorizaci\u00f3n propuestas utilizan una t\u00e9cnica de transposici\u00f3n local para habilitar la explotaci\u00f3n del paralelismo simd en los dos procesados, horizontal y vertical. Adem\u00e1s, se desarrolla una nueva t\u00e9cnica de complicaci\u00f3n, basada en el compilador de slp, que permite automatizar este proceso. El rendimiento alcanzado supera significativamente al proporcionado por los copiladores de intel.     finalmente, se proponen modelos de procesamiento de flujos para la 2d-dwt, que permite la explotaci\u00f3n de paralelismo de datos en unidades gr\u00e1ficas programables. Se realiza un minucioso estudio sobre su rendimiento y los par\u00e1metros de los modelos, llegando a la conclusi\u00f3n de que el algoritmo piramidal de mallat es m\u00e1s eficiente que el esquema lifting en este tipo de plataformas, que son adem\u00e1s m\u00e1s eficientes para este tipo del algoritmo que los procesadores superescalares. Los resultados parecen adem\u00e1s indicar que estas diferencias de rendimiento tienden a acentuarse con el desarrollo de la tecnolog\u00eda de hardware gr\u00e1fico.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Optimizaci\u00f3n de la transformada wavelet. explotaci\u00f3n de paralelismo de grano fino<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Optimizaci\u00f3n de la transformada wavelet. explotaci\u00f3n de paralelismo de grano fino <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Christian Tenllado Van Der Reijden <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Complutense de Madrid<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 16\/01\/2007<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Manuel Prieto Matias<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: roman Hermida correa <\/li>\n<li>inmaculada Garcia fernandez (vocal)<\/li>\n<li>ramon Doallo biempica (vocal)<\/li>\n<li>Emilio Lopez zapata (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Christian Tenllado Van Der Reijden Esta tesis aborda la explotaci\u00f3n eficiente de paralelismo de datos en la [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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