PPT-Graph-Based Parallel Computing

William Cohen 1 Announcements Next Tuesday 128 Presentations for 10805 projects 15 minutes per project Final written reports due Tues 12 15 For exam S pectral clustering will not be cov. Uni processor computing can be called centralized computing brPage 3br mainframe computer workstation network host network link terminal centralized computing distributed computing A distributed system is a collection of independent computers interc Performance Theory - 1. Parallel Computing. CIS . 410/. 510. Department of Computer and Information Science. Outline. Performance scalability. Analytical performance measures. Amdahl. ’. s. law and Gustafson-. Parallel Computing. CIS . 410/. 510. Department of Computer and Information Science. Outline. What is the fork-join concept?. What is the fork-join pattern?. Programming Model Support for Fork-Join. Recursive Implementation of Map. Copyright © 2014 by ScaleOut Software, Inc.. Portland Big Data Users Group. October 23, 2014. Bill . Bain, CEO . (. wbain@scaleoutsoftware.com). What Is Operational Intelligence?. Example: Tracking Cable Viewers. George Caragea, and Uzi Vishkin. University of Maryland. 1. Speaker. James Edwards. It has proven to be quite . difficult. to obtain significant performance improvements using current parallel computing platforms.. Improving Computer Performance. What performance translates into:. Time taken to do computation. Improving performance . → reducing time taken. What key benefits improving performance can bring:. Can solve “now-computationally-attainable” problems in . Efficient and scalable architectures to perform pleasingly parallel, MapReduce and iterative data intensive computations on cloud environments. Thilina. . Gunarathne. (tgunarat@indiana.edu). Advisor : . Applications and. Types of Parallelism. Henry Neeman, Director. OU Supercomputing Center for Education & Research. University of Oklahoma Information Technology. Oklahoma Supercomputing Symposium, Tue Oct . : . Structure . and . Algorithms*. Presented By:. Saleh. A. . Almugrin. salmugri@kent.edu. * Based . and influenced by . many works of . Hans L. . Bodlaender. , . Institute of Information and Computing Sciences, Utrecht . Luke Winslow. OWI a-la-carte. Overview. What is Parallel Computing. Example Uses. Intro to Condor. Demo. Parallel Computing. Cluster. Why would I need this?. Dealing with Large Datasets. Lake Shape Characteristics. Dr Susan Cartwright. Dept of Physics and Astronomy. University of Sheffield. Parallel Universes. Are you unique?. Could there be another “you” differing only in what you had for breakfast this morning?. William Cohen. 1. Announcements. Next Tuesday 12/8:. Presentations for 10-805 projects.. 15 minutes per. project.. Final written reports due Tues 12/15. 2. Graph-Based Parallel Computing. William Cohen. Early Adopter: ASU - Intel Collaboration in Parallel and Distributed Computing Yinong Chen , Eric Kostelich , Yann -Hang Lee, Alex Mahalov , Gil Speyer, and Violet R. Syrotiuk 1 st NSF /TCPP Workshop on Parallel and Distributed Computing Education ( CS 6260. Professor: Elise De . Doncker. By: . Lina. Hussein. 1. Topics Covered :. Introduction. What is cluster computing?. Classification of Cluster Computing. Technologies:. Beowulf cluster. Construction of Beowulf Cluster.