'Problem size' presentation slideshows

Parallel Programming & Cluster Computing Shared Memory Multithreading

Parallel Programming & Cluster Computing Shared Memory Multithreading. Henry Neeman, Director OU Supercomputing Center for Education & Research University of Oklahoma Information Technology Oklahoma Supercomputing Symposium, Tue Oct 5 2010. Outline. Parallelism Shared Memory Parallelism

1.05k views • 86 slides

Grade School Revisited: How To Multiply Two Numbers

Grade School Revisited: How To Multiply Two Numbers. Time complexity of grade school addition. T(n) = amount of time grade school addition uses to add two n -bit numbers. * * * * * * * * * *. +. * * * * * * * * * *. * * * * * * * * * * *. T(n) is linear:. T(n ) = c 1 n. X.

950 views • 83 slides

Multiplicative Bounds for Metric Labeling

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Parallel Analysis of Algorithms: PRAM + CGM

Parallel Analysis of Algorithms: PRAM + CGM. Outline. Parallel Performance Parallel Models Shared Memory (PRAM, SMP) Distributed Memory (BSP, CGM). Parallel Analysis of Algorithms. Question?.

850 views • 70 slides

Asymptotic Analysis

Asymptotic Analysis. Outline. 2.3. In this topic, we will look at: Justification for analysis Quadratic and polynomial growth Counting machine instructions Landau symbols Big- Q as an Equivalence Relation Little- o as a Linear Ordering. Background. 2.3.

729 views • 52 slides

Parallel Scalability

Parallel Scalability . CS 420 Fall 2012 Osman Sarood. How faster can we run?. Suppose we have this serial problem with 12 tasks. How fast can we run given 3 processors?. Running in parallel. Execution time reduces from 12 secs to 4 secs !. Load imbalance .

751 views • 50 slides

CS38 Introduction to Algorithms

CS38 Introduction to Algorithms. Lecture 17 May 27, 2014. Outline. coping with intractibility NP-completeness special cases fixed parameter complexity approximation algorithms. Hardness and completeness. Reasonable that can efficiently transform one problem into another. Surprising:

615 views • 49 slides

Lecture 7

Lecture 7. CS203. Midterm Exam. The midterm exam will be next Wednesday at the regular class time and will be timed to fill the entire class period

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CMPT 225

Recursion. CMPT 225. Objectives. Identify recursive algorithms Write simple recursive algorithms Understand recursive function calling With reference to the call stack Compute the result of simple recursive algorithms Understand the drawbacks of recursion

645 views • 46 slides

Samuel Williams, Jonathan Carter, Leonid Oliker , John Shalf , Katherine Yelick

Resource-Efficient, Hierarchical Auto-tuning of a Hybrid Lattice Boltzmann Computation on the Cray XT4. Samuel Williams, Jonathan Carter, Leonid Oliker , John Shalf , Katherine Yelick Lawrence Berkeley National Laboratory (LBNL)

581 views • 33 slides

Meltem Peker 04.11.2013

Airline Schedule Planning: Accomplishments and Opportunities C. Barnhart and A. Cohn , 2004. Meltem Peker 04.11.2013. Introduction. Optimization in Airline Industry After " The Airline Deregulation Act " (1970s):

512 views • 33 slides

DYNAMIC PROGRAMMING ALGORITHMS

DYNAMIC PROGRAMMING ALGORITHMS. VINAY ABHISHEK MANCHIRAJU. SCOPE. Apply dynamic programming to gene finding and other bioinformatics problems . Power of DNA Sequence Comparison A revisit to the Change Problem The Manhattan Tourist Problem Edit Distance and Alignments

481 views • 33 slides

Sorting and Efficiency

Sorting and Efficiency. Eric Roberts CS 106B January 30, 2013. Sorting.

407 views • 25 slides

Finite Difference Time Domain (FDTD) (2 Sessions)

Finite Difference Time Domain (FDTD) (2 Sessions). History of FDTD Method. A Perspective on 40-Year History of FDTD Computational Electrodynamics. History of FDTD Method. Paper Number 1: Kane Yee IEEE AP-S Transactions, May 1966 . 2441 citations as of March 7, 2006 .

509 views • 25 slides

Chapter 6 Multiprocessor System

Chapter 6 Multiprocessor System. Introduction. Each processor in a multiprocessor system can be executing a different instruction at any time. The major advantages of MIMD system Reliability High performance The overhead involved with MIMD Communication between processors

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CSCI 171

401 views • 23 slides

2013.11.25 20126128 ???

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Multicore for Science

Multicore for Science. Multicore Panel at eScience 2008 December 11 2008 Geoffrey Fox Community Grids Laboratory , School of informatics Indiana University gcf@indiana.edu , http://www.infomall.org. 1. Lessons.

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P arallel Systems

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251 views • 8 slides