'Load balance' diaporamas de présentation

Map Reduce Basics Chapter 2

Map Reduce Basics Chapter 2. Basics. Divide and conquer Partition large problem into smaller subproblems Worker work on subproblems in parallel Threads in a core, cores in multi-core processor, multiple processor in a machine, machines in a cluster

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Hardware/Software Performance Tradeoffs (plus Msg Passing Finish)

Hardware/Software Performance Tradeoffs (plus Msg Passing Finish). CS 258, Spring 99 David E. Culler Computer Science Division U.C. Berkeley. SAS Recap. Partitioning = Decomposition + Assignment Orchestration = coordination and communication SPMD, Static Assignment Implicit communication

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Dynamic Computations in Ever-Changing Networks

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DONAR Decentralized Server Selection for Cloud Services

DONAR Decentralized Server Selection for Cloud Services. Patrick Wendell , Princeton University Joint work with Joe Wenjie Jiang, Michael J. Freedman, and Jennifer Rexford. Outline. Server selection background Constraint-based policy interface Scalable optimization algorithm

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CS 267: Applications of Parallel Computers Load Balancing

CS 267: Applications of Parallel Computers Load Balancing. James Demmel www.cs.berkeley.edu/~demmel/cs267_Spr06. Outline. Motivation for Load Balancing Recall graph partitioning as load balancing technique Overview of load balancing problems, as determined by Task costs Task dependencies

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CS 267: Applications of Parallel Computers Load Balancing

CS 267: Applications of Parallel Computers Load Balancing. James Demmel www.cs.berkeley.edu/~demmel/cs267_Spr10. Outline. Motivation for Load Balancing Recall graph partitioning as load balancing technique Overview of load balancing problems, as determined by Task costs Task dependencies

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James Harding - Database Manager Sabre Sherri Trojan - Database Architect HP October 2, 2009

Maximizing Oracle Real Application Clusters 11g: Sharing the Load with Services. James Harding - Database Manager Sabre Sherri Trojan - Database Architect HP October 2, 2009. Today. Tomorrow. Objective. Improve: Capacity & Scalability Operation Support

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Scalable High Performance Dimension Reduction

Scalable High Performance Dimension Reduction. Seung-Hee Bae. Outline. Motivation Background and Related Work Research Issues Experimental Analysis Contributions References. Motivation. Data deluge era Biological sequence, Chemical Compound data Data intensive computing

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CMPE 511 H IGH PERFORMANCE COMPUTING CLUSTERS

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WSS 3.0 & SharePoint 2007 Updates: The Tour Starts Here

WSS 3.0 & SharePoint 2007 Updates: The Tour Starts Here. Presented by: JD Wade SharePoint Engineer, MCTS, MCSE Mail: jd.wade@hrizns.com Blog: http://wadingthrough.wordpress.com Twitter: JDWade FriendFeed: http://friendfeed.com/jdwade. Agenda. Overview of Updates

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Problem Solving with NetSolve

Problem Solving with NetSolve. Michelle Miller, Keith Moore, Susan Blackford, NetSolve group, Innovative Computing Lab, University of Tennessee. miller@cs.utk.edu moore@cs.utk.edu susan@cs.utk.edu. www.cs.utk.edu/netsolve netsolve@cs.utk.edu. NetSolve. Problem Statement

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HPC USER FORUM ISV PANEL April 2010 Dearborn, MI

HPC USER FORUM ISV PANEL April 2010 Dearborn, MI. Panel Members. Moderators Alex Akkerman, Ford Motor Company Sharan Kalwani, KAUST Participants Steve Feldman, CD-adapco Matt Dunbar, Simulia Uwe Schramm, Altair Engineering Li Zhang, Livermore Software Technology Corporation

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GSM Continued

GSM Continued. GSM Burst Format. Each time slot is 577us. They are (in this order) Trailing bits (3 bits) Data (57 bits) Flag (1 bit) Training sequence (26 bits) Data (57 bits) Flag (1 bit) Trailing bits (3 bits) Guard Period (8.25bit). GSM Bursts . In addition,

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Compressive Data Gathering for Large-Scale Wireless Sensor Networks

Compressive Data Gathering for Large-Scale Wireless Sensor Networks. Chong Luo Feng Wu Shanghai Jiao Tong University Microsoft Research Asia Jun Sun Chang Wen Chen

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Oracle Global IT Data Center Operations and Management Best Practices Bill Weils, Global IT Senior Director November 20

Oracle Global IT Data Center Operations and Management Best Practices Bill Weils, Global IT Senior Director November 2007. Our Goal Accomplishments Corporate Business Challenge Our Strategy - Oracle Grid Architecture Standardization and Consolidation Austin Data Center Overview

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An Ant Colony Optimization Algorithm for Multi-objective Clustering in Mobile Ad Hoc Networks

An Ant Colony Optimization Algorithm for Multi-objective Clustering in Mobile Ad Hoc Networks. Chung-Wei Wu, Tsung-Che Chiang, and Li-Chen Fu IEEE C ongress on Evolutionary C omputation (CEC ) Beijing, July 11, 2014, . Outline. Introduction Proposed algorithm Experimental results

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Proxy Servers

Proxy Servers. CS-480b Dick Steflik. Proxy Servers. Part of an overall Firewall strategy Sits between the local network and the external network Originally used primarily as a caching strategy to minimize outgoing URL requests and increase perceived browser performance

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Composite Link (CL ): status update and Framework

Composite Link (CL ): status update and Framework. Ning So, Curtis Villamizar, Dave McDysan, Andy Malis, Lucy Yong, Eric Osbourne. Status Update of CL drafts . draft-ietf-rtgwg-cl-requirement-07 Minor changes since last IETF. WG doc awaiting advancement of other two CL docs

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