'Parallel code' diaporamas de présentation

Parallel and Concurrent Programming

Parallel and Concurrent Programming. Motivation (General): Multicore Architectures Systems that require High Performance Computing (HPC) services Systems that provide HPC services Science and Engineering moving towards simulation ( requiring HPC)

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Universal Parallel Computing Research Center at Illinois

Universal Parallel Computing Research Center at Illinois. Making parallel programming synonymous with programming. Wen-mei Hwu Co-Director UPCRC Illinois. The UPCRC@ Illinois Team . UPCRC Illinois. background . CUDA Center of Excellence. Illiac. Extreme Scale Computing.

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Code Optimization of Parallel Programs

Code Optimization of Parallel Programs. Vivek Sarkar Rice University vsarkar@rice.edu. Parallel Software Challenges & Focus Area for this Talk. Domain-specific implicitly parallel programming models e.g., Matlab, stream processing, map-reduce (Sawzall),. Domain-specific Programming Models.

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High Performance Computing Research at Berkeley

High Performance Computing Research at Berkeley. Katherine Yelick U. C. Berkeley, EECS Dept. and Lawrence Berkeley National Laboratory November 2004. Major Research Areas in HPC at Berkeley. Programming Languages & Compilers Performance Analysis, Modeling, Tuning Algorithms & Libraries

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Pattern Programming Introduction to Seeds Framework

Pattern Programming Introduction to Seeds Framework. ITCS 4/5145 Parallel Programming Spring 2013 PatterrnProgIntro.ppt Modification date: April 15, 2013. 1. Problem Addressed. To make parallel programming more useable and scalable.

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greg astfalk woon yung chung woon-yung_chung@hp

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Ocelot: supported devices

Ocelot: supported devices. Overview. Ocelot PTX Emulator Multicore-Backend NVIDIA GPU Backend AMD GPU Backend. Multicore CPU Backend: Introduction. Target: Efficient execution of PTX kernels on CPUs ISA Translation from PTX to LLVM

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UC Berkeley Par Lab Overview

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Lab 2 Ideas

Lab 2 Ideas. Various forms of non-optimized FIR code. Demonstrate progress on Lab.1. 1.5% of term mark is associated with demonstrating progress on developing C++ code (FIR) and associated tests. Demonstrate at the start of the Lab. Lab. notes.

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STDP and Network Architectures

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High Performance Computing Code for Pyroclastic Flows Simulations

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STDP and Network Architectures

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Parallel Computing Explained Parallel Performance Analysis

Parallel Computing Explained Parallel Performance Analysis. Slides Prepared from the CI-Tutor Courses at NCSA http://ci-tutor.ncsa.uiuc.edu/ By S. Masoud Sadjadi School of Computing and Information Sciences Florida International University March 2009. Agenda.

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Parallel Algorithms

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Using the Argo Cluster

Using the Argo Cluster. Paul Sexton CS 566 February 6, 2006. Logging in. The address is argo-new.cc.uic.edu Use ssh to log in, using your ACCC username Ex: ssh psexto2@argo-new.cc.uic.edu Pay attention to the login message, this is how the admins will communicate information to you.

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Point-to-Point Communication

Point-to-Point Communication. Self Test with solution. Self Test. MPI_SEND is used to send an array of 10 4-byte integers. At the time MPI_SEND is called, MPI has over 50 Kbytes of internal message buffer free on the sending process. Choose the best answer.

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cc Compiler Parallelization Options

cc Compiler Parallelization Options. CSE 260 Mini-project Fall 2001 John Kerwin. Background. The Sun Workshop 6.1 cc compiler does not support OpenMP, but it does contain Multi Processing options similar to those in OpenMP. FOR MORE INFO. Chapter 4 of the C User's Guide at

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Assignment 1

Assignment 1. CMSC 714 September 11, 2003. Data Collection. For this assignment, you will be asked to provide the following: Effort spent on various activities (self-tracked) Information when you compile your program (automatically collected)

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