November 30, 2020

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High Performance Computing

High Performance Computing
Author : Gary Sabot
Publisher : Addison-Wesley
Release Date : 1995
Category : Computers
Total pages :246
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This book shows by example how to solve complex scientific problems with programs that run on high-performance computers. Combining case studies from a variety of problem domains, written by experts in those domains, it shows how to map or transform an abstract problem into concrete solutions that execute rapidly and efficiently on available high-performance hardware. Each chapter describes some technical or engineering problem to which computers are commonly applied, then leads readers through the choice and development of appropriate algorithms and through an evaluation of resulting implementations. Although each chapter centers on a single application area, they all focus on general techniques useful for any area rather than on application-specific details. Students should have some programming experience in a language like FORTRAN or C, and some familiarity with computing issues involved in scientific problems; but no expertise in parallel computing is required. 0201598302B04062001

Problem-solving in High Performance Computing

Problem-solving in High Performance Computing
Author : Igor Ljubuncic
Publisher : Morgan Kaufmann
Release Date : 2015-09-01
Category : Computers
Total pages :320
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Problem-Solving in High Performance Computing: A Situational Awareness Approach with Linux focuses on understanding giant computing grids as cohesive systems. Unlike other titles on general problem-solving or system administration, this book offers a cohesive approach to complex, layered environments, highlighting the difference between standalone system troubleshooting and complex problem-solving in large, mission critical environments, and addressing the pitfalls of information overload, micro, and macro symptoms, also including methods for managing problems in large computing ecosystems. The authors offer perspective gained from years of developing Intel-based systems that lead the industry in the number of hosts, software tools, and licenses used in chip design. The book offers unique, real-life examples that emphasize the magnitude and operational complexity of high performance computer systems. Provides insider perspectives on challenges in high performance environments with thousands of servers, millions of cores, distributed data centers, and petabytes of shared data Covers analysis, troubleshooting, and system optimization, from initial diagnostics to deep dives into kernel crash dumps Presents macro principles that appeal to a wide range of users and various real-life, complex problems Includes examples from 24/7 mission-critical environments with specific HPC operational constraints

High-Performance Computing in Finance

High-Performance Computing in Finance
Author : M. A. H. Dempster,Juho Kanniainen,John Keane,Erik Vynckier
Publisher : CRC Press
Release Date : 2018-02-21
Category : Computers
Total pages :614
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High-Performance Computing (HPC) delivers higher computational performance to solve problems in science, engineering and finance. There are various HPC resources available for different needs, ranging from cloud computing– that can be used without much expertise and expense – to more tailored hardware, such as Field-Programmable Gate Arrays (FPGAs) or D-Wave’s quantum computer systems. High-Performance Computing in Finance is the first book that provides a state-of-the-art introduction to HPC for finance, capturing both academically and practically relevant problems.

High performance computing for solving large sparse systems. Optical diffraction tomography as a case of study

High performance computing for solving large sparse systems. Optical diffraction tomography as a case of study
Author : Gloria Ortega López
Publisher : Universidad Almería
Release Date : 2015-04-14
Category :
Total pages :182
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This thesis, entitled €High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study€ investigates the computational issues related to the resolution of linear systems of equations which come from the discretization of physical models described by means of Partial Differential Equations (PDEs). These physical models are conceived for the description of the space-temporary behavior of some physical phenomena f(x, y, z, t) in terms of their variations (partial derivative) with respect to the dependent variables of the phenomena. There is a wide variety of discretization methods for PDEs. Two of the most well-known methods are the Finite Difference Method (FDM) and the Finite Element Method (FEM). Both methods result in an algebraic description of the model that can be translated into the approach of a linear system of equations of type (Ax = b), where A is a sparse matrix (a high percentage of zero elements) whose size depends on the required accuracy of the modeled phenomena. This thesis begins with the algebraic description of the model associated with the physical phenomena, and the work herein has been focused on the design of techniques and computational models that allow the resolution of these linear systems of equations. The main interest of this study is specially focused on models which require a high level of discretization and usually generate sparse matrices, A, which have a highly sparse structure and large size. Literature characterizes these types of problems by their high demanding computational requirements (because of their fine degree of discretization) and the sparsity of the matrices involved, suggesting that these kinds of problems can only be solved using High Performance Computing techniques and architectures. One of the main goals of this thesis is the research of the possible alternatives which allow the implementation of routines to solve large and sparse linear systems of equations using High Performance Computing (HPC). The use of massively parallel platforms (GPUs) allows the acceleration of these routines, because they have several advantages for vectorial computation schemes. On the other hand, the use of distributed memory platforms allows the resolution of problems defined by matrices of enormous size. Finally, the combination of both techniques, distributed computation and multi-GPUs, will allow faster resolution of interesting problems in which large and sparse matrices are involved. In this line, one of the goals of this thesis is to supply the scientific community with implementations based on multi-GPU clusters to solve sparse linear systems of equations, which are the key in many scientific computations. The second part of this thesis is focused on a real physical problem of Optical Diffractional Tomography (ODT) based on holographic information. ODT is a non-damaging technique which allows the extraction of the shapes of objects with high accuracy. Therefore, this technique is very suitable to the in vivo study of real specimens, microorganisms, etc., and it also makes the investigation of their dynamics possible. A preliminary physical model based on a bidimensional reconstruction of the seeding particle distribution in fluids was proposed by J. Lobera and J.M. Coupland. However, its high computational cost (in both memory requirements and runtime) made compulsory the use of HPC techniques to extend the implementation to a three dimensional model. In the second part of this thesis, the implementation and validation of this physical model for the case of three dimensional reconstructions is carried out. In such implementation, the resolution of large and sparse linear systems of equations is required. Thus, some of the algebraic routines developed in the first part of the thesis have been used to implement computational strategies capable of solving the problem of 3D reconstruction based on ODT.

Solving competitive location problems via memetic algorithms. High performance computing approaches.

Solving competitive location problems via memetic algorithms. High performance computing approaches.
Author : Juana López Redondo
Publisher : Universidad Almería
Release Date : 2009-02-19
Category : Technology & Engineering
Total pages :129
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La localización de servicios (“Facility location” en inglés) pretende encontrar el emplazamiento de uno o más centros (servicios) de modo que se optimice una determinada función objetivo. Dicha función objetivo puede, por ejemplo, tratar de minimizar el coste de transporte, proporcionar a los clientes un servicio de forma equitativa, capturar la mayor cuota de mercado posible, etc. La localización de servicios abarca muchos campos, como la investigación operativa, la ingeniería industrial, la geografía, la economía, las matemáticas, el marketing, el planning urbanístico, además de otros muchos campos relacionados. Existen muchos problemas de localización en la vida real, como por ejemplo, la localización de hospitales, de colegios o vertederos, por nombrar algunos. Para ser capaces de obtener soluciones a los problemas de localización, es necesario desarrollar/diseñar un modelo que represente la realidad lo más fielmente posible. Dichos modelos pueden llegar a ser realmente difíciles de tratar. Muchos algoritmos de optimización global, exactos y heurísticos han sido propuestos para resolver problemas de localización. Los algoritmos exactos se caracterizan por ser capaces de obtener el óptimo global con una cierta precisión. Sin embargo, suelen ser altamente costosos desde el punto de vista computacional, lo que implica que, en determinados casos, sea imposible aplicarlos para resolver un problema. Los algoritmos heurísticos se alzan entonces como una buena alternativa. No obstante, en determinadas circunstancias, los requerimientos computacionales son tan elevados, que el uso de algoritmos heurísticos ejecutándose en procesadores estándares no es suficiente. En tales situaciones, la computación de altas prestaciones es necesaria. Esta tesis, “Solving competitive location problems via memetic algorithms. High performance computing approaches” (Algoritmos meméticos para problemas de localización competitiva. Computación de altas prestaciones), proporciona, por un lado, algoritmos heurísticos capaces de resolver problemas de localización, tanto en el dominio continuo como en el discreto y, por otro lado, técnicas paralelas que permiten reducir el tiempo de ejecución, resolver problemas más grandes, e incluso en ocasiones mejorar la calidad de las soluciones. Esta tesis incluye tres partes bien diferenciadas, cada una de las cuales se divide en varios capítulos. La primera parte Preliminaries (Preliminares), está compuesta por tres capítulos que revisan el estado actual de la optimización global, de la computación de altas prestaciones y de la ciencia de la localización, respectivamente. El Capítulo 1 comienza con la definición de los problemas de optimización, y continúa con la introducción de diferentes métodos heurísticos para tratar con ellos. El Capítulo 2 describe brevemente algunas de las arquitecturas paralelas y de los modelos de programación paralelos. Finalmente, en el Capítulo 3, se describen y analizan los principales ingredientes de la localización de servicios, y se presenta una revisión sobre problemas de localización continuos y discretos. La segunda parte de la tesis, Solving continuous location problems (Resolviendo problemas de localización continua), comienza en el Capítulo 4, donde se presenta un problema de localización competitiva en el plano y se revisan dos técnicas previamente propuestas en la literatura para resolverlo. Posteriormente, se describe una nuevo algoritmo evolutivo para resolver óptimamente el problema, llamado UEGO, y se comparan todas las alternativas. Finalmente, varias estrategias paralelas basadas en el algoritmo UEGO son analizadas y evaluadas. En el Capítulo 5, el problema de localizar un solo centro en el plano, se extiende al caso en el que la cadena o empresa quiere emplazar más de un servicio. Para abordar este problema, se adapta el algoritmo UEGO presentado en el Capítulo 4, además de otras técnicas descritas en la literatura. A través de un extenso estudio computational, todas los algoritmos son comparados y se concluye que UEGO es el mejor de todos ellos, tanto por su eficiencia como por su efectividad. UEGO es usado para realizar un estudio de sensibilidad con el fin de chequear los cambios de diseño/localización óptima cuando los parámetros del modelo cambian. Finalmente, se presentan y evalúan varias técnicas paralelas para tratar el problema de localización de varios centros. El Capítulo 6 está dedicado al problema de líder-seguidor. En dicho problema, tras la localización del líder, el competidor reacciona localizando otro nuevo centro en el lugar que maximice su propio beneficio. El objetivo del líder es encontrar la solución que maximice su beneficio, sabiendo que posteriormente, la competencia localizará un nuevo centro. Por tanto, hay que resolver dos problemas simultáneamente: el problema del seguidor, también denominado medianoide, y el problema del líder o centroide. El modelo del problema del líder-seguidor se describe al principio del capítulo. Posteriormente, se proponen y evalúan varios algoritmos para resolver tanto el problema del medianoide como el del centroide. El capítulo finaliza con la paralelización de uno de los algoritmos propuestos. La tercera parte de la tesis, Solving discrete location problems (Resolviendo problemas de localización discreta), comienza en el Capítulo 7 con una introducción sobre algunos problemas de localización discreta. Este capítulo analiza aquellos casos en los que dichos problemas podrían presentar varias soluciones óptimas. Además, se muestra cómo un usuario experimentado podría obtenerlas, y se establecen algunos criterios para seleccionar una solución óptima entre diferentes alternativas. El capítulo finaliza con la descripción del algoritmo MSH, un heurístico ampliamente usado en la literatura para la resolución de problemas de localización discreta. El Capítulo 8 describe un algoritmo genético multimodal, GASUB, capaz de resolver varios problemas de localización discreta. El algoritmo tiene diferentes parámetros de entrada que pueden ser ajustados para alcanzar diferentes metas. En este capítulo, el objetivo es obtener al menos una solución óptima, pero invirtiendo el menor esfuerzo (tiempo) computacional posible. Para tal fin, se lleva a cabo un estudio previo y se determina el conjunto de parámetros adecuado. GASUB, con este conjunto de parámetros, es comparado con el optimizador Xpress-MP y con la heurística MSH, los cuales son capaces de obtener un único óptimo global (de manera directa). Sin embargo, teniendo en cuenta que los problemas de localización discreta considerados en esta tesis pueden tener más de una solución óptima, en el Capítulo 9 se analiza la posibilidad de explotar las propiedades multimodales de GASUB. Con este fin, se propone un nuevo conjunto de parámetros, con el que GASUB es nuevamente evaluado. Finalmente, se da una paralelización de GASUB y se estudian algunas de las soluciones globales encontradas por los algoritmos. La tesis finaliza con un resumen sobre los principales resultados obtenidos y sobre la líneas de investigación futura.

Frontiers of High Performance Computing and Networking - ISPA 2007 Workshops

Frontiers of High Performance Computing and Networking - ISPA 2007 Workshops
Author : Parimala Thulasiraman,Xubin He,Tony Li Xu,Mieso Denko,Ruppa K. Thulasiram,Laurence T. Yang
Publisher : Springer
Release Date : 2007-08-18
Category : Computers
Total pages :538
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This book constitutes the refereed joint proceedings of seven international workshops held in conjunction with the 5th International Symposium on Parallel and Distributed Processing and Applications, ISPA 2007, held in Niagara Falls, Canada in August 2007. The 53 revised full papers presented were carefully selected from many high quality submissions. The workshops contribute to enlarging the spectrum of the more general topics treated in the ISPA 2007 main conference.

High Performance Computing for Geospatial Applications

High Performance Computing for Geospatial Applications
Author : Wenwu Tang,Shaowen Wang
Publisher : Springer Nature
Release Date : 2020-08-21
Category : Technology & Engineering
Total pages :296
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This volume fills a research gap between the rapid development of High Performance Computing (HPC) approaches and their geospatial applications. With a focus on geospatial applications, the book discusses in detail how researchers apply HPC to tackle their geospatial problems. Based on this focus, the book identifies the opportunities and challenges revolving around geospatial applications of HPC. Readers are introduced to the fundamentals of HPC, and will learn how HPC methods are applied in various specific areas of geospatial study. The book begins by discussing theoretical aspects and methodological uses of HPC within a geospatial context, including parallel algorithms, geospatial data handling, spatial analysis and modeling, and cartography and geovisualization. Then, specific domain applications of HPC are addressed in the contexts of earth science, land use and land cover change, urban studies, transportation studies, and social science. The book will be of interest to scientists and engineers who are interested in applying cutting-edge HPC technologies in their respective fields, as well as students and faculty engaged in geography, environmental science, social science, and computer science.

High Performance Computing Demystified

High Performance Computing Demystified
Author : David Loshin
Publisher : Academic Press
Release Date : 2014-05-10
Category : Mathematics
Total pages :278
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High Performance Computing Demystified provides an overview of high performance resources and their applications across many disciplines. This book is organized into five parts encompassing 16 chapters that cover the principles, mode of operation, and practical aspects of supercomputers. The first and second parts provide a brief history of high performance computing and describe the “basic parts needed to build high performance computers, including high performance microprocessors and network topologies. The third part examines the features of multiprocessor architectures of high performance, such as the large number crunchers, massively parallel processing machines, and networks of workstations. The fourth part deals with the software paradigms for high performance, while the fifth part looks into the high performance computing resources that are available to the public, with some guide to accessing those resources. This book is intended primarily for engineers and business managers who have a basic understanding of computers and would like to learn about high performance computing.

High-Performance Computing and Networking

High-Performance Computing and Networking
Author : Marian Bubak,Bob Hertzberger,Hamideh Afsarmanesh,Roy Williams
Publisher : Springer Science & Business Media
Release Date : 2000-04-28
Category : Computers
Total pages :719
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This book constitutes the refereed proceedings of the 8th International Conference on High-Performance Computing and Networking, HPCN Europe 2000, held in Amsterdam, The Netherlands, in May 2000. The 52 revised full papers presented together with 34 revised posters were carefully reviewed for inclusion in the book. The papers are organized in sections on problem solving environments, metacomputing, load balancing, numerical parallel algorithms, virtual enterprises and virtual laboratories, cooperation coordination, Web-based tools for tele-working, monitoring and performance, low-level algorithms, Java in HPCN, cluster computing, data analysis, and applications in a variety of fields.

Parallel I/O for High Performance Computing

Parallel I/O for High Performance Computing
Author : John M. May
Publisher : Morgan Kaufmann
Release Date : 2001
Category : Computers
Total pages :366
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"I enjoyed reading this book immensely. The author was uncommonly careful in his explanations. I'd recommend this book to anyone writing scientific application codes." -Peter S. Pacheco, University of San Francisco "This text provides a useful overview of an area that is currently not addressed in any book. The presentation of parallel I/O issues across all levels of abstraction is this book's greatest strength." -Alan Sussman, University of Maryland Scientific and technical programmers can no longer afford to treat I/O as an afterthought. The speed, memory size, and disk capacity of parallel computers continue to grow rapidly, but the rate at which disk drives can read and write data is improving far less quickly. As a result, the performance of carefully tuned parallel programs can slow dramatically when they read or write files-and the problem is likely to get far worse. Parallel input and output techniques can help solve this problem by creating multiple data paths between memory and disks. However, simply adding disk drives to an I/O system without considering the overall software design will not significantly improve performance. To reap the full benefits of a parallel I/O system, application programmers must understand how parallel I/O systems work and where the performance pitfalls lie. Parallel I/O for High Performance Computing directly addresses this critical need by examining parallel I/O from the bottom up. This important new book is recommended to anyone writing scientific application codes as the best single source on I/O techniques and to computer scientists as a solid up-to-date introduction to parallel I/O research. Features: An overview of key I/O issues at all levels of abstraction-including hardware, through the OS and file systems, up to very high-level scientific libraries. Describes the important features of MPI-IO, netCDF, and HDF-5 and presents numerous examples illustrating how to use each of these I/O interfaces. Addresses the basic question of how to read and write data efficiently in HPC applications. An explanation of various layers of storage - and techniques for using disks (and sometimes tapes) effectively in HPC applications.

High Performance Computing - HiPC 2006

High Performance Computing - HiPC 2006
Author : Yves L. Robert,Manish Parashar,Ramamurthy Badrinath,Viktor K. Prasanna
Publisher : Springer Science & Business Media
Release Date : 2006-11-27
Category : Computers
Total pages :642
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This book constitutes the refereed proceedings of the 13th International Conference on High-Performance Computing, HiPC 2006, held in Bangalore, India in December 2006. The 52 revised full papers presented together with the abstracts of 7 invited talks were carefully reviewed and selected from 335 submissions. The papers are organized in topical sections on scheduling and load balancing, architectures, network and distributed algorithms, application software, network services, applications, ad-hoc networks, systems software, sensor networks and performance evaluation, as well as routing and data management algorithms.

High-Performance Computing and Networking

High-Performance Computing and Networking
Author : Peter Sloot,Marian Bubak,Alfons Hoekstra,Bob Hertzberger
Publisher : Springer Science & Business Media
Release Date : 1999-03-30
Category : Computers
Total pages :1320
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This book constitutes the refereed proceedings of the 7th International Conference on High-Performance Computing and Networking, HPCN Europe 1999, held in Amsterdam, The Netherlands in April 1999. The 115 revised full papers presented were carefully selected from a total of close to 200 conference submissions as well as from submissions for various topical workshops. Also included are 40 selected poster presentations. The conference papers are organized in three tracks: end-user applications of HPCN, computational science, and computer science; additionally there are six sections corresponding to topical workshops.

High-Performance Computing Infrastructure for South East Europe's Research Communities

High-Performance Computing Infrastructure for South East Europe's Research Communities
Author : Mihnea Dulea,Aneta Karaivanova,Anastasis Oulas,Ioannis Liabotis,Danica Stojiljkovic,Ognjen Prnjat
Publisher : Springer Science & Business Media
Release Date : 2013-08-13
Category : Technology & Engineering
Total pages :171
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This book is a collection of carefully reviewed papers presented during the HP-SEE User Forum, the meeting of the High-Performance Computing Infrastructure for South East Europe’s (HP-SEE) Research Communities, held in October 17-19, 2012, in Belgrade, Serbia. HP-SEE aims at supporting and integrating regional HPC infrastructures; implementing solutions for HPC in the region; and making HPC resources available to research communities in SEE, region, which are working in a number of scientific fields with specific needs for massively parallel execution on powerful computing resources. HP-SEE brings together research communities and HPC operators from 14 different countries and enables them to share HPC facilities, software, tools, data and research results, thus fostering collaboration and strengthening the regional and national human network; the project specifically supports research groups in the areas of computational physics, computational chemistry and the life sciences. The contributions presented in this book are organized in four main sections: computational physics; computational chemistry; the life sciences; and scientific computing and HPC operations.

High Performance Computing and the Art of Parallel Programming

High Performance Computing and the Art of Parallel Programming
Author : Stan Openshaw,Ian Turton
Publisher : Routledge
Release Date : 2005-09-19
Category : Computers
Total pages :304
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This book provides a non-technical introduction to High Performance Computing applications together with advice about how beginners can start to write parallel programs. The authors show what HPC can offer geographers and social scientists and how it can be used in GIS. They provide examples of where it has already been used and suggestions for other areas of application in geography and the social sciences. Case studies drawn from geography explain the key principles and help to understand the logic and thought processes that lie behind the parallel programming.

High Performance Computing and Applications

High Performance Computing and Applications
Author : Wu Zhang,Zhangxin Chen,Craig C. Douglas,Weiqin Tong
Publisher : Springer Science & Business Media
Release Date : 2010-02-19
Category : Computers
Total pages :589
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This book constitutes the thoroughly refereed post-conference proceedings of the Second International Conference on High Performance Computing and Applications, HPCA 2009, held in Shangahi, China, in August 2009. The 71 revised papers presented together with 10 invited presentations were carefully selected from 324 submissions. The papers cover topics such as numerical algorithms and solutions; high performance and grid computing; novel approaches to high performance computing; massive data storage and processsing; and hardware acceleration.