'Shared memory model' presentation slideshows

Tools for High Performance Scientific Computing

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Tools for High Performance Scientific Computing

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Steve Wolfman , based on work by Dan Grossman

A Sophomoric Introduction to Shared-Memory Parallelism and Concurrency Lecture 1 Introduction to Multithreading & Fork-Join Parallelism. Steve Wolfman , based on work by Dan Grossman. LICENSE : This file is licensed under a Creative Commons Attribution 3.0 Unported License; see

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Chapter 4 Multiprocessor architecture

Chapter 4 Multiprocessor architecture. slides adapted from: http://www.cs.sunysb.edu/~cse502 David Patterson, UC-Berkeley cs252-s06 and Edelman, MIT. Currently popular models. Hardware Multicore chips (2009: mostly 2 cores and 4 cores, but doubling) (cores=processors)

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Computer Architecture

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SE363

SE363. Computer Architecture MIMD Parallel Processors John Morris. Iolanthe II racing in Waitemata Harbour. MIMD Systems. Recipe Buy a few high performance commercial PEs DEC Alpha MIPS R10000 UltraSPARC Pentium? Put them together with some memory and peripherals on a common bus

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SE363

SE363. Computer Architecture MIMD Parallel Processors John Morris. Iolanthe II racing in Waitemata Harbour. MIMD Systems. Recipe Buy a few high performance commercial PEs DEC Alpha MIPS R10000 UltraSPARC Pentium? Put them together with some memory and peripherals on a common bus

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Instructor: Justin Hsia

CS 61C: Great Ideas in Computer Architecture Synchronization, OpenMP. Instructor: Justin Hsia. Review of Last Lecture. Multiprocessor systems uses shared memory (single address space) Cache coherence implements shared memory even with multiple copies in multiple caches

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Parallel Computing

Parallel Computing. CS 6021/01 Advanced Computer Architecture Final Project. Spring 2019. Group 1 Hu Longhua Shweta Khandal Vannel Zeufack. Plan. Introduction Concepts Parallel Computing Memory Architectures Parallel Programming Models References. Introduction.

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Guang R. Gao ACM Fellow and IEEE Fellow Endowed Distinguished Professor

Topic 3 -- II: System Software Fundamentals: Multithreaded Execution Models, Virtual Machines and Memory Models. Guang R. Gao ACM Fellow and IEEE Fellow Endowed Distinguished Professor Electrical & Computer Engineering University of Delaware ggao@capsl.udel.edu. Outline.

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CPSC 668 DISTRIBUTED ALGORITHMS AND SYSTEMS

CPSC 668 DISTRIBUTED ALGORITHMS AND SYSTEMS. Fall 2011 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.

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Introduction to Parallel Architectures and Programming Models

Introduction to Parallel Architectures and Programming Models. A generic parallel architecture. P. P. P. P. M. M. M. M. Interconnection Network. Memory. Where is the memory physically located?. Classifying computer architecture.

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Dariusz Kowalski University of Connecticut & Warsaw University joint work with Alex Shvartsman

Dariusz Kowalski University of Connecticut & Warsaw University joint work with Alex Shvartsman University of Connecticut & MIT. Performing Tasks in Asynchronous Environments. Do-All problem ( [DHW] et al. ).

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Parallel Computation Models

Parallel Computation Models. Lecture 3 Lecture 4. Parallel Computation Models. PRAM (parallel RAM) Fixed Interconnection Network bus, ring, mesh, hypercube, shuffle-exchange Boolean Circuits Combinatorial Circuits BSP LOGP. PARALLEL AND DISTRIBUTED COMPUTATION.

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Parallelization Strategies

Parallelization Strategies. Laxmikant Kale. Overview. OpenMP Strategies Need for adaptive strategies Object migration based dynamic load balancing Minimal modification strategies Thread based techniques: ROCFLO, .. Some future plans. OpenMP. Motivation:

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Parallel Computing on Manycore GPUs

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ITEC452 Distributed Computing Lecture 2 Models in Distributed Systems

Hwajung Lee. ITEC452 Distributed Computing Lecture 2 Models in Distributed Systems. Why do we need models?.

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OpenMP Tutorial

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Process Synchronization

Process Synchronization. Cooperating Processes. Process Cooperation Purposes Information sharing (Share files) Computation speedup (create subtasks to run simultaneously) Modularity (system function divide into separate processes or threads)

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OPENCL OVERVIEW

OPENCL OVERVIEW. OpenCL Commercial Objectives. Grow the market for parallel computing For vendors of systems, silicon, middleware, tools and applications Open, royalty-free standard for heterogeneous parallel computing

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