'Shared variables' diaporamas de présentation

Parallel Programming and Timing Analysis on Embedded Multicores

Parallel Programming and Timing Analysis on Embedded Multicores. Eugene Yip The University of Auckland Supervisors: Advisor: Dr. Partha Roop Dr . Alain Girault Dr. Morteza Biglari-Abhari. Outline. Introduction ForeC language Timing analysis Results Conclusions. Introduction.

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Real-Time Systems Lecture 4

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GPUs and GPU Programming Bharadwaj Subramanian, Apollo Ellis

GPUs and GPU Programming Bharadwaj Subramanian, Apollo Ellis. Imagery taken from Nvidia Dawn Demo Slide on GPUs, CUDA and Programming Models by Apollo Ellis Slides on OpenCL by Bharadwaj Subramanian. A GPU is a Multi-core Architecture.

526 views • 41 slides

CPSC 668 DISTRIBUTED ALGORITHMS AND SYSTEMS

CPSC 668 DISTRIBUTED ALGORITHMS AND SYSTEMS. Spring 2014 Prof. Jennifer Welch. Shared Memory Model. Processors communicate via a set of shared variables, instead of passing messages. Each shared variable has a type , defining a set of operations that can be performed atomically.

501 views • 38 slides

CPSC 668 DISTRIBUTED ALGORITHMS AND SYSTEMS

CPSC 668 DISTRIBUTED ALGORITHMS AND SYSTEMS. Spring 2014 Prof. Jennifer Welch. Shared Memory Model. Processors communicate via a set of shared variables, instead of passing messages. Each shared variable has a type , defining a set of operations that can be performed atomically.

389 views • 38 slides

Module 2.2: Process Synchronization

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CPSC 668 Distributed Algorithms and Systems

CPSC 668 Distributed Algorithms and Systems. Fall 2006 Prof. Jennifer Welch. Shared Memory Model. Processors communicate via a set of shared variables, instead of passing messages. Each shared variable has a type , defining a set of operations that can be performed atomically.

467 views • 35 slides

Module 2.1: Process Synchronization

Module 2.1: Process Synchronization. Examples of Shared Variable Problem Mutual Exclusion Solutions to ME Semaphores Critical Regions Monitors Process synchronization means coordination among processes. Concurrent Processes.

539 views • 34 slides

TECHNIQUES FOR REDUCING CONSISTENCY-RELATED COMMUNICATION IN DISTRIBUTED SHARED-MEMORY SYSTEMS

TECHNIQUES FOR REDUCING CONSISTENCY-RELATED COMMUNICATION IN DISTRIBUTED SHARED-MEMORY SYSTEMS. J. B. Carter University of Utah J. K. Bennett and W. Zwaenepoel Rice University. INTRODUCTION.

392 views • 31 slides

Searching for Solutions

Searching for Solutions. Careful Analysis of Expansions The Bucket Algorithm. Solutions and Expansions. For every subgoal p(X,Y) of a query, each solution must have a subgoal (view) whose expansion allows a containment mapping to p(X,Y).

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Mutual Exclusion

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Unified Parallel C

Unified Parallel C. Kathy Yelick EECS, U.C. Berkeley and NERSC/LBNL NERSC Team: Dan Bonachea, Jason Duell, Paul Hargrove, Parry Husbands, Costin Iancu, Mike Welcome, Christian Bell. Outline. Global Address Space Languages in General Programming models Overview of Unified Parallel C (UPC)

365 views • 26 slides

CPAR-Cluster: A Runtime System for Heterogeneous Clusters with Mono and Multiprocessor Nodes

CPAR-Cluster: A Runtime System for Heterogeneous Clusters with Mono and Multiprocessor Nodes. Gisele S. Craveiro, PhD Profa. Liria M. Sato, PhD CCGrid 2004 - Chicago. Outline. Introduction CPAR Parallel Programming Language CPAR-Cluster Tests and Results Conclusions. Introduction.

336 views • 23 slides

Formal Methods of Systems Specification Logical Specification of Hard- and Software

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CS259: Security Analysis of Network Protocols Overview of Murphi

CS259: Security Analysis of Network Protocols Overview of Murphi. Arnab Roy. Running Murphi. Elaine Machines Murphi available at /usr/class/cs259/Murphi3.1/ HW1 code available at /usr/class/cs259/hw1/ Any issues so far?. Running Murphi. If you are using another linux machine or cygwin

254 views • 17 slides

The Critical-Section( ??? ) Problem

The Critical-Section( ??? ) Problem. n processes all competing to use some shared data. Each process has a code segment, called critical section , in which the shared data is accessed.

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HParC language

HParC language . Background. Shared memory level Multiple separated shared memory spaces Message passing level-1 Fast level of k separate message passing segments Message passing level-2 Slow level of message passing. Proposed solution.

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1.10 Model 3: Message-Passing Text

1.10 Model 3: Message-Passing Text. We saw Diagrams Shared-variables text Now Message-passing text (like CSP). In the communication statements, we name a channel, and not the communication partner directly. This naming convention Leads to better encapsulation of processes,

255 views • 13 slides

Spark

Spark. Cluster Computing with Working Sets. Matei Zaharia, Mosharaf Chowdhury, Michael Franklin, Scott Shenker, Ion Stoica. Background. MapReduce and Dryad raised level of abstraction in cluster programming by hiding scaling & faults

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Useful LabVIEW 8.20 Features

Useful LabVIEW 8.20 Features. CS Workshop 2007 February 2nd, 2007 Holger Brand, GSI. Project Explorer Libraries Shared Variables Custom DSC IO Server Periodic OnChange Classes Simple class hierarchy Online Tutorial: How to create and inherit from LVOOP classes

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