'Input size' diaporamas de présentation

On Time Versus Input Size

On Time Versus Input Size. t ime. # of bits. How to add 2 n-bit numbers. * *. * *. * *. * *. * *. * *. * *. * *. * *. * *. * *. +. How to add 2 n-bit numbers. * *. * *. * *. * *. * *. * *. * *. * *. * *. * * *. * * * . +. How to add 2 n-bit numbers. * *. * *. * *.

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David E. Keyes Center for Computational Science Old Dominion University Institute for Computer Applications in Science &

Algorithms and Software for Scalable Fusion Energy Simulations. David E. Keyes Center for Computational Science Old Dominion University Institute for Computer Applications in Science & Engineering NASA Langley Research Center Institute for Scientific Computing Research

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Class exam #1

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Limitation of Algorithm Power

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2.1 Computational Tractability

2.1 Computational Tractability. "For me, great algorithms are the poetry of computation. Just like verse, they can be terse, allusive, dense, and even mysterious. But once unlocked, they cast a brilliant new light on some aspect of computing." - Francis Sullivan. Computational Tractability.

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Chayant Tantipathananandh with Tanya Berger-Wolf

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Asymptotics

Asymptotics. Section 3.2 of Rosen Fall 2008 CSCE 235 Introduction to Discrete Structures Course web-page: cse.unl.edu/~cse235 Questions : cse235@cse.unl.edu. Outline. Introduction Asymptotic Definitions (Big O, Omega, Theta), properties Proof techniques

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Algorithmic Issues in Non-cooperative (i.e., strategic) Distributed Systems

Algorithmic Issues in Non-cooperative (i.e., strategic) Distributed Systems Two Research Traditions Theory of Algorithms: computational issues What can be feasibly computed? How much does it take to compute a solution? Which is the quality of a computed solution?

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CS5302 Data Structures and Algorithms

CS5302 Data Structures and Algorithms . Lecturer: Lusheng Wang Office: Y6416 Phone: 2788 9820 E-mail lwang@cs.cityu.edu.hk Welcome to ask questions at ANY time. Java Source code: http://net3.datastructures.net/download.html The course Website:

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Analysis of Algorithms

Analysis of Algorithms. The Non-recursive Case. Except as otherwise noted, the content of this presentation is licensed under the Creative Commons Attribution 2.5 License. . Key Topics:. Introduction Generalizing Running Time Doing a Timing Analysis Big-Oh Notation Big-Oh Operations

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Computational Intractability As A Law of Physics

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Analysis of Algorithms

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CS216: Program and Data Representation University of Virginia Computer Science Spring 2006 David Evans

CS216: Program and Data Representation University of Virginia Computer Science Spring 2006 David Evans. Lecture 2: Orders of Growth. http://www.cs.virginia.edu/cs216. Menu. Predicting program properties Orders of Growth: O , ? Course Survey Results.

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Lecture 2: Divide and Conquer I: Merge-Sort and Master Theorem

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Online Performance Auditing Using Hot Optimizations Without Getting Burned

Online Performance Auditing Using Hot Optimizations Without Getting Burned. Jeremy Lau (UCSD, IBM) Matthew Arnold (IBM) Michael Hind (IBM) Brad Calder (UCSD). Problem. Trend: Increasing complexity of computer systems Hardware: more speculation and parallelism

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Whole Program Paths

Whole Program Paths. James R. Larus. Outline. Find acyclic path fragments Convert into whole-program path Determine hot subpaths. Acyclic Paths. As per Ball&Larus paper we implemented. Calculating Acyclic Paths. Instrument chords Sum along paths is unique Postprocess for functions

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A Gentle Introduction to Bilateral Filtering and its Applications

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Vertex and Edge Covers with Clustering Properties: Complexity and Algorithms

Vertex and Edge Covers with Clustering Properties: Complexity and Algorithms. Henning Fernau Department of Computer Science University of Trier David Manlove Department of Computing Science University of Glasgow.

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Parallel Algorithms

Parallel Algorithms. several operations can be executed at the same time many problems are most naturally modeled with parallelism A Simple Model for Parallel Processing Approaches to the design of parallel algorithms Speedup and Efficiency of parallel algorithms A class of problems NC

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