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CBurst Let Hard Disks Sleep Well and Work Energetically Feng Chen and Xiaodong Zhang Dept of Computer Science and Engineering The Ohio State University Power Management in Hard Disk . Alexander . Kotov. , . ChengXiang. . Zhai. , Richard . Sproat. University of Illinois at Urbana-Champaign. Roadmap. Problem definition. Previous work. Approach. Experiments. Summary. Motivation. Web data is generated by a large number of textual streams (news, blogs, tweets, etc. in Kentico CMS. Boris . Pocatko. Solution Architect. Kentico Software. borisp@kentico.com. Agenda. Problem. Describing different caching mechanisms. Demo for cache dependencies. API caching and additional info. 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. 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. Victor Zakhary, . Divyakant. Agrawal, Amr El . Abbadi. 1. The old problem of Caching. Disk. RAM. L. 2. L. 1. Larger. Slower. Cheaper. Smaller. Faster. Expensive. 2. The old problem of Caching. Smaller. ): Let Hard Disks Sleep Well and Work Energetically. Feng. Chen and . Xiaodong. Zhang. Dept. of Computer Science and Engineering. The Ohio State University. Power Management . in . Hard Disk . Power management . Edwin Kite (U. Chicago), John Armstrong (Weber State), . Robin Wordsworth (Harvard), Francois Forget (LMD) . c. an climate . models. h. elp distinguish. these scenarios?. h. abitable surface. s. terile surface. Name. Title. Microsoft Corporation. Presentation Summary. Version: Jul 2010. Feedback: . ryandunn@microsoft.com. . Technical Level: 300/400. Intended Audience: Developers, Architects. Intended Time: 60 minutes. A Framework for Evaluating Caching Policies in a Hierarchical Network of Caches Eman Ramadan, Pariya Babaie , Zhi -Li Zhang Presented By: Arvind Narayanan University of Minnesota, USA 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 Caching 50.5* COS 518: Advanced Computer Systems Lecture 9 Michael Freedman * Half of 101 Tradeoff Fast: Costly, small, close Slow: Cheap, large, far Based on two assumptions Temporal location: Will be accessed again soon catch a burst and notify other observatoriesboth in space and on the ground of its approx-imate locationWithin minutes HETE-2 mayobtain a precise locationCurrent telescopestake much longer to notify o &. Caching. Noah Mendelsohn. Tufts University. Email: . noah@cs.tufts.edu. Web: http://www.cs.tufts.edu/~noah. COMP 150-IDS: Internet Scale Distributed Systems . (Spring 2015). 2. Goals. Explore some general principles of performance,...