PPT-Caching and Virtual Memory

Main Points Cache concept Hardware vs software caches When caches work and when they dont Spatialtemporal locality vs Zipf workloads Cache Replacement Policies FIFO MIN LRU LFU Clock. Justin DeBrabant. Brown University . debrabant@cs.brown.edu. A bit of history…. 1974 – System R. query optimization . recovery . transaction serialization. lots of locks. Application. Primary Storage. Utilizing AppFabric Caching Services On-. Premise. and Beyond to Optimize Performance. About Me. Overview. of . Caching. Server . AppFabric. . Caching. Architecture. Demo. : Server . AppFabric. . Main Points. Cache concept. Hardware vs. software caches. When caches work and when they don’t. Spatial/temporal locality vs. . Zipf. workloads. Cache Replacement Policies. FIFO, MIN, LRU, LFU, Clock. Hakim Weatherspoon. CS 3410, Spring 2011. Computer Science. Cornell University. P & H . Chapter. 5.4-5. Announcements. PA3 . available. Due . Tuesday, April 19. th. Work with . pairs. Be responsible with new knowledge. Use main memory as a “cache” for secondary (disk) storage. Managed jointly by CPU hardware and the operating system (OS). Programs share main memory. Each gets a private virtual address space holding its frequently used code and data. Definitions. Cache. Copy of data that is faster to access than the original. Hit: if cache has copy. Miss: if cache does not have copy. Cache block. Unit of cache storage (multiple memory locations). 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. 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. Managed jointly by CPU hardware and the operating system (OS). Programs share main memory. Each gets a private virtual address space holding its frequently used code and data. Protected from other programs. 2017. Instructor:. . Ruth Anderson. Teaching Assistants:. Dylan Johnson. Kevin Bi. Linxing. Preston Jiang. Cody . Ohlsen. Yufang. Sun. Joshua Curtis. Administrivia. Midterms Graded. If you did not receive an email from . 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 CS 3410, Spring 2012. Computer Science. Cornell University. P & H Chapter 5.4 . Goals for Today. Virtual Memory. Address Translation. Pages, page tables, and memory . mgmt. unit. Paging. Role of Operating System. 15-213: Introduction to Computer Systems . 16. th. . Lecture, Oct. . 22. , 2013. Instructors:. . Randy Bryant, Dave . O’Hallaron. , and Greg . Kesden. Today . Address spaces. VM as a tool for caching. &. 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,...