'Parallel programming' diaporamas de présentation

Uzi Vishkin Electrical and Computer Engineering Dept

ENEE699/ENEE459P: Parallel Algorithms Home page: http://www.umiacs.umd.edu/users/vishkin/TEACHING/enee459p-f10.html. Uzi Vishkin Electrical and Computer Engineering Dept. Topics covered. Parallel algorithms Parallel programing languages

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Partitioning, Divide and Conquer

Partitioning, Divide and Conquer. Partitioning Dividing the problem into parts Most strategies require coordination between the parts Embarrassingly parallel is an exception Partitioning can typically be done in two ways Dividing the data Data partitioning or domain decomposition

1.02k views • 66 slides

Understanding PRAM as Fault Line: Too Easy? or Too difficult?

Understanding PRAM as Fault Line: Too Easy? or Too difficult?. Using Simple Abstraction to Reinvent Computing for Parallelism, CACM, January 2011, pp. 75-85 http://www.umiacs.umd.edu/users/vishkin/XMT/. Uzi Vishkin. Commodity computer systems.

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ME964 High Performance Computing for Engineering Applications

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PARLab Parallel Boot Camp Cloud Computing with MapReduce and Hadoop

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Introduction to MapReduce and Hadoop

Introduction to MapReduce and Hadoop. Matei Zaharia UC Berkeley RAD Lab matei@eecs.berkeley.edu. What is MapReduce?. Data-parallel programming model for clusters of commodity machines Pioneered by Google Processes 20 PB of data per day Popularized by open-source Hadoop project

1.08k views • 52 slides

ME964 High Performance Computing for Engineering Applications

1.07k views • 49 slides

MapReduce for Machine Learning on Multicore

MapReduce for Machine Learning on Multicore. Cheng-Tao Chu and Sang Kyun Kim et al. Stanford University, Stanford CA Presented by Inna Rytsareva. Outline. What is MapReduce? Problem Description and Formalization Statistical Query Model and Summation Form

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Parallel and High Performance Computing

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A Pattern Language for Parallel Programming

A Pattern Language for Parallel Programming. Beverly Sanders University of Florida. Overview of talk. History of pattern languages Motivation for a pattern language for parallel programming Pattern example: Reengineering for Parallelism

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Map-reduce programming paradigm

Map-reduce programming paradigm. Some slides are from lecture of Matei Zaharia, and distributed computing seminar by Christophe Bisciglia, Aaron Kimball, & Sierra Michels-Slettvet. Data. The New York Stock Exchange generates about one terabyte of new trade data per day.

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NewsFlash!!

629 views • 33 slides

Introduction, background, jargon

Introduction, background, jargon. Jakub Yaghob. Literature. T.G.Mattson , B.A.Sanders , B.L.Massingill : Patterns for Parallel Programming , Addison-Wesley, 2005, ISBN 978-0-321-22811-6

589 views • 30 slides

Parallel Computing

Parallel Computing. Guoliang Chen E-mail : glchen@ustc.edu.cn. Parallel Computing. Parallel Architectures Parallel Algorithms Parallel Programming. Abstract.

490 views • 22 slides

Research on Reconfigurable Computing Using Impulse C

Research on Reconfigurable Computing Using Impulse C. Carmen Li Shen Mentor: Dr. Russell Duren February 1, 2008. Presentation Overview. Background Information Introduction Impulse C Current Work Conclusion & Future Research Questions. Background Information. Reconfigurable computing

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Human Media Multicore Computing Lecture 1 : Course Overview

Human Media Multicore Computing Lecture 1 : Course Overview. Bong-Soo Sohn Associate Professor School of Computer Science and Engineering Chung-Ang University. Course Description. Almost all recent PCs and smart phones/tablets are equipped with multicore CPUs

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The 50B Transistor Challenge Mikko Lipasti Department of Electrical and Computer Engineering University of Wisconsin - M

The 50B Transistor Challenge Mikko Lipasti Department of Electrical and Computer Engineering University of Wisconsin - Madison. IBM T.J. Watson Research Center July 22 and 23, 2008. 50B Transistors on a Chip?. History 1997 IEEE Computer Special Issue, 1B T/chip by 2007

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Microsoft Research Faculty Summit 2007

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Narsingh Deo , Faraz Hussain , Sumit Kumar Jha , *Mahadevan Vasudevan

Introducing parallel programming across the undergraduate curriculum through an interdisciplinary course on computational modeling Building Big Systems for Biting into Big Data. Narsingh Deo , Faraz Hussain , Sumit Kumar Jha , *Mahadevan Vasudevan

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Lecture 2: Parallel Computing Fundamentals

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