PPT-CSE 421 Greedy Algorithms / Caching Problem

Yin Tat Lee 1 2 Optimal CachingPaging Memory systems Many levels of storage with different access times Smaller storage has shorter access time To access an item it must be brought to the lowest level of the memory system. Carmine . Cerrone. , . Raffaele. . Cerulli. , Bruce Golden. GO IX. Sirmione. , Italy. July 2014. 1. Outline. Motivation. The Minimum Label Spanning Tree (MLST) problem. Experimental justification. Introduction to Carousel . How It Works and When You Should Use It . Shy Cohen. Principal, . Shy Cohen Consulting. AAP314. What Gurus Need to Know. What’s a cache and what it does. Core and advanced concepts. Caching on premises and in Windows Azure. Utilizing AppFabric Caching Services On-. Premise. and Beyond to Optimize Performance. About Me. Overview. of . Caching. Server . AppFabric. . Caching. Architecture. Demo. : Server . AppFabric. . Optimization problems, Greedy Algorithms, Optimal Substructure and Greedy choice. Learning & Development Team. http://academy.telerik.com. . Telerik Software Academy. Table of Contents. Optimization Problems. CIS 606. Spring 2010. Greedy Algorithms. Similar to dynamic programming.. Used for optimization problems.. Idea. When we have a choice to make, make the one that looks best . right now. . Make . a locally . Yuli. Ye . Joint work with Allan Borodin, University of Toronto. Why do we study greedy algorithms? . don’t. A quote from Jeff Erickson’s algorithms book. . Everyone should tattoo the following sentence on the back of their hands, right under all the rules about logarithms and big-Oh notation. Ilija Vukotic. ADC TIM - Chicago. October 28, 2014. Caching – why and where?. Straight Tier3 . Most of the disk space is devoted to input data. The input data is almost always from downloaded from the grid. Telerik Software Academy. http://academy.telerik.com. . ASP.NET MVC. Table of Contents. Why do we need caching?. ASP.NET Output Caching. OutputCache. page directive. Cache profiles. Post-cache substitution. The two key components. Optimal Sub-structure. You solve the problem by solving a sub-problem optimally. Greedy Property. Using the choice that seems best at the moment leads to the optimal result. This is tougher to show!. and When You Should Use It . Jon Flanders. Senior Consultant. MCW Technologies. MID302. Agenda. Why Caching?. What is AppFabric Cache?. On-Premise and in Azure. Demo, demo, demo. Typical Web Architecture. Caching Problem. Yin Tat Lee. 1. 2. Last Lecture. Greedy . Analysis Strategies. Greedy algorithm stays ahead: Induction. Structural: Come up with a lower bound. Exchange argument: transform OPT to . greedy. CS-3013 . Operating Systems. Hugh C. Lauer. (Slides include materials from. Slides include materials from . Modern Operating Systems. , . 3. rd. ed. ., by Andrew . Tanenbaum. and from . Operating System Concepts. Caching at the Web Scale Victor Zakhary, Divyakant Agrawal, Amr El Abbadi Full slide deck: https://goo.gl/1VYGW3 1 The old problem of Caching Disk RAM L 2 L 1 Larger Slower Cheaper Smaller Faster Fall 20151 Week . 7. CSCI-141. Scott C. Johnson. Say we go to the bank to cash our paycheck. We ask the teller for the fewest bills and coins as possible. Moments later the teller gives us our money and we leave.