4 resultados para Graphic ProcessingUnits, GPUs
em Universidad Politécnica de Madrid
Resumo:
Nowadays, computer simulators are becoming basic tools for education and training in many engineering fields. In the nuclear industry, the role of simulation for training of operators of nuclear power plants is also recognized of the utmost relevance. As an example, the International Atomic Energy Agency sponsors the development of nuclear reactor simulators for education, and arranges the supply of such simulation programs. Aware of this, in 2008 Gas Natural Fenosa, a Spanish gas and electric utility that owns and operate nuclear power plants and promotes university education in the nuclear technology field, provided the Department of Nuclear Engineering of Universidad Politécnica de Madrid with the Interactive Graphic Simulator (IGS) of “José Cabrera” (Zorita) nuclear power plant, an industrial facility whose commercial operation ceased definitively in April 2006. It is a state-of-the-art full-scope real-time simulator that was used for training and qualification of the operators of the plant control room, as well as to understand and analyses the plant dynamics, and to develop, qualify and validate its emergency operating procedures.
Resumo:
En el presente documento se hablará acerca del desarrollo de un proyecto para la mejora de un programa de análisis de señales; con ese fin, se hará uso de técnicas de optimización del software y de tecnologías de aceleración, mediante el aprovechamiento del paralelismo del programa. Además se hará un análisis de acerca del uso de dos tecnologías basadas en diferentes paradigmas de programación paralela; una mediante múltiples hilos con memoria compartida y la otra mediante el uso de GPUs como dispositivos de coprocesamiento. This paper will talk about the development of a Project to improve a program that does signals analysis; to that end, it will make use of software optimization techniques and acceleration technologies by exploiting parallelism in the program. In Addition will be done an analysis on the use of two technologies based on two different paradigms; one using multiple threads with shared memory and the other using GPU as co-processing devices.
Resumo:
This approach aims at aligning, unifying and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. A sentiment lexicon is a critical and essential resource for tagging subjective corpora on the web or elsewhere. In many situations, the multilingual property of the sentiment lexicon is important because the writer is using two languages alternately in the same text, message or post. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and -1, where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and -1 means they are perfectly inversely correlated and the UnifiedMetrics procedure for CPU and GPU, respectively.
Resumo:
El objetivo de este proyecto es evaluar la mejora de rendimiento que aporta la paralelización de algoritmos de procesamiento de imágenes, para su ejecución en una tarjeta gráfica. Para ello, una vez seleccionados los algoritmos a estudio, fueron desarrollados en lenguaje C++ bajo el paradigma secuencial. A continuación, tomando como base estas implementaciones, se paralelizaron siguiendo las directivas de la tecnología CUDA (Compute Unified Device Architecture) desarrollada por NVIDIA. Posteriormente, se desarrolló un interfaz gráfico de usuario en Visual C#, para una utilización más sencilla de la herramienta. Por último, se midió el rendimiento de cada uno de los algoritmos, en términos de tiempo de ejecución paralela y speedup, mediante el procesamiento de una serie de imágenes de distintos tamaños.---ABSTRACT---The aim of this Project is to evaluate the performance improvement provided by the parallelization of image processing algorithms, which will be executed on a graphics processing unit. In order to do this, once the algorithms to study were selected, each of them was developed in C++ under sequential paradigm. Then, based on these implementations, these algorithms were implemented using the compute unified device architecture (CUDA) programming model provided by NVIDIA. After that, a graphical user interface (GUI) was developed to increase application’s usability. Finally, performance of each algorithm was measured in terms of parallel execution time and speedup by processing a set of images of different sizes.