PPT-Analysis of Algorithms
Author : min-jolicoeur | Published Date : 2015-09-15
CS 477677 Instructor Monica Nicolescu Lecture 2 CS 477677 Lecture 2 2 Algorithm Analysis The amount of resources used by the algorithm Space Computational time
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Analysis of Algorithms: Transcript
CS 477677 Instructor Monica Nicolescu Lecture 2 CS 477677 Lecture 2 2 Algorithm Analysis The amount of resources used by the algorithm Space Computational time Running time The number of primitive operations steps executed before termination. for Linear Algebra and Beyond. Jim . Demmel. EECS & Math Departments. UC Berkeley. 2. Why avoid communication? (1/3). Algorithms have two costs (measured in time or energy):. Arithmetic (FLOPS). Communication: moving data between . Hazem Ali, Borislav Nikoli. ć,. Kostiantyn Berezovskyi, Ricardo Garibay Martinez, Muhammad Ali Awan. Outline. Introduction. Non-Population Metaheuristics. Population Metaheuristics. Genetic Algorithims (GA). Some of the fastest known algorithms for certain tasks rely on chance. Stochastic/Randomized Algorithms. Two common variations. Monte Carlo. Las Vegas. We have already encountered some of both in this class. Siu. A. Chin. Texas A&M University. Castellon, Sept. 6, 2010. Forward. algorithms, with all positive time steps for solve time-irreversible equations with a diffusion kernel beyond the second-order. . Optimization problems, Greedy Algorithms, Optimal Substructure and Greedy choice. Learning & Development Team. http://academy.telerik.com. . Telerik Software Academy. Table of Contents. Optimization Problems. Lars . Arge. Spring . 2012. February . 27, 2012. Lars Arge. I/O-algorithms. 2. Random Access Machine Model. Standard theoretical model of computation:. Infinite memory. Uniform access cost. R . A. M. George Caragea, and Uzi Vishkin. University of Maryland. 1. Speaker. James Edwards. It has proven to be quite . difficult. to obtain significant performance improvements using current parallel computing platforms.. Annie . Yang and Martin Burtscher*. Department of Computer Science. Highlights. MPC compression algorithm. Brand-new . lossless . compression algorithm for single- and double-precision floating-point data. Amrinder Arora. Permalink: http://standardwisdom.com/softwarejournal/presentations/. Summary. Online algorithms show up in . many. practical problems.. Even if you are considering an offline problem, consider what would be the online version of that problem.. Aleksandar. R. . Mihajlovic. Technische. . Uni. versität München. mihajlovic@mytum.de. +49 176 673 41387. +381 63 183 0081. 1. Overview . Explain input data based imputation algorithm categorization scheme. Erin Carson, Jim Demmel, Laura . Grigori. , Nick Knight, . Penporn. . Koanantakool. , . Oded. Schwartz, . Harsha. . Simhadri. Slides based on. ASPIRE Retreat, June 2015. 1. Outline. Strassen. Instructor: Arun Sen. Office: BYENG . 530. Tel: 480-965-6153. E-mail: asen@asu.edu. Office Hours: . MW 3:30-4:30 or by appointment. TA: . TBA. Office. : TBA. Tel: . TBA. E-mail: . TBA. Office Hours. : . Problem - a well defined task.. Sort a list of numbers.. Find a particular item in a list.. Find a winning chess move.. Algorithms. A series of precise steps, known to stop eventually, that solve a problem.. 1. Brute Force. A straightforward approach, usually based . directly. on the problem’s . statement and . definitions. . of the concepts involved. Examples – based directly on definitions:. Computing .
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