'Matrix vector multiplication' diaporamas de présentation

Overview

Overview. Goal: scalable algorithms to find patterns and anomalies on graphs Mining Large Graphs: Algorithms, Inference, and Discoveries Spectral Analysis of Billion-Scale Graphs : Discoveries and Implementation Patterns on the Connected Components of Terabyte-Scale Graphs

744 views • 63 slides

Overview

Overview. Goal: scalable algorithms to find patterns and anomalies on graphs Mining Large Graphs: Algorithms, Inference, and Discoveries Spectral Analysis of Billion-Scale Graphs : Discoveries and Implementation Patterns on the Connected Components of Terabyte-Scale Graphs

745 views • 63 slides

Barriers and Condition Variables

Barriers and Condition Variables. Barriers. Synchronizing the threads to make sure that they all are at the same point in a program is called a barrier. No thread can cross the barrier until all the threads have reached it. Using barriers to time the slowest thread.

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Improving Gate-Level Simulation of Quantum Circuits

DARPA. DARPA. Improving Gate-Level Simulation of Quantum Circuits. George F. Viamontes, Igor L. Markov, and John P. Hayes {gviamont,imarkov,jhayes}@umich.edu Advanced Computer Architecture Laboratory University of Michigan, EECS. Problem.

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REVIEW: Separation of Variables

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Bob Lucas nersc/~dhbailey/cs267

CS 267 Applications of Parallel Computers Lecture 2: Memory Hierarchies and Optimizing Matrix Multiplication. Bob Lucas http://www.nersc.gov/~dhbailey/cs267. Millennium Accounts. To get Millenium accounts, students need to get EECS Instructional Accounts

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Computer Graphics

Computer Graphics. http:/ /viscomp.ucsd.edu/classes/cse167/ wi19. CSE 167 [Win 19] , Lecture 2: Review of Basic Math Ravi Ramamoorthi. To Do. Complete Assignment 0 (due Jan 16) Get help if issues with compiling, programming Any problems with edX edge?

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James Demmel cs.berkeley/~demmel/cs267_Spr99

CS 267 Applications of Parallel Computers Lecture 2: Memory Hierarchies and Optimizing Matrix Multiplication. James Demmel http://www.cs.berkeley.edu/~demmel/cs267_Spr99. Outline. Understanding Caches Optimizing Matrix Multiplication. Idealized Uniprocessor Model.

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A Flipped Classroom Approach to Teaching Concurrency and Parallelism

A Flipped Classroom Approach to Teaching Concurrency and Parallelism. Shirley Moore University of Texas at El Paso svmoore@utep.edu Steven Dunlop Purdue University dunlop@purdue.edu EduPar-16 May 23, 2016. Motivation and Goals.

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Economics 2301

Matrices Lecture 12. Economics 2301 . Inner Product. Let a ' be a row vector and b a column vector, both being n -tuples, that is vectors having n elements:.

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Matrix Solvers Direct Methods

Matrix Solvers Direct Methods. Phil Bording Memorial University. What makes the matrix structure?. The mathematical formulation!! Finite Elements Finite Differences Boundary Element Methods. I, j+1 i-1,j-1 I,j i+1,j I,j-1.

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