PPT-Linearly Compressed Pages: A Main Memory Compression Framework

with Low Complexity and Low Latency Gennady Pekhimenko Advisers Todd C Mowry and Onur Mutlu Carnegie Mellon University Executive Summary Main memory is a limited shared resource Observation. Join R X. R.A=S.B. S. :. :. Relation R. M Pages . N Pages . Relation S. Pr. records per page. Ps records per page. Simple Nested Loops Join. For each tuple r in R do. for each tuple s in S do. A Main Memory Compression Framework with . Low Complexity and Low Latency . Gennady Pekhimenko. , . Vivek. . Seshadri. . , . Yoongu. Kim, . Hongyi. . Xin. , . Onur. . Mutlu. , . Todd C. . Mowry. of Multi-Connection. Compressed Web Traffic. Yaron. Koral. 1. with: . Yehuda. Afek. 1. . , . Anat. Bremler-Barr. 1. *. 1. . Blavatnik. School of Computer Sciences Tel-Aviv University, Israel. 2 Computer Science Dept. Interdisciplinary Center, . Exploiting . Spatial Locality . for Energy-Optimized . Compressed Caching. Somayeh. . Sardashti. and . David . A. . Wood. University . of Wisconsin-Madison. 1. 2. 3. Where does energy go?. Communication vs. Computation. thatcansignicantlydegradeperformance.Tocounterthisprob-lem,priorwork[3,25,39]oncachecompressionproposedspecial-izedcompressionalgorithmsthatexploitregularpatternspresentinin-memorydata,andshowedthats A Main Memory . Compression Framework with . Low Complexity and Low Latency . Gennady Pekhimenko. , . Vivek. . Seshadri. . , . Yoongu. Kim, . Hongyi. . Xin. , . Onur. . Mutlu. , . Todd C. . Mowry. Exploiting . Spatial Locality . for Energy-Optimized . Compressed Caching. Somayeh. . Sardashti. and . David . A. . Wood. University . of Wisconsin-Madison. 1. 2. 3. Where does energy go?. Communication vs. Computation. Join R X. R.A=S.B. S. :. :. Relation R. M Pages . N Pages . Relation S. Pr. records per page. Ps records per page. Simple Nested Loops Join. For each tuple r in R do. for each tuple s in S do. A Main Memory Compression Framework with . Low Complexity and Low Latency . Gennady Pekhimenko. , . Vivek. . Seshadri. . , . Yoongu. Kim, . Hongyi. . Xin. , . Onur. . Mutlu. , . Todd C. . Mowry. Shreya. Current Query Methods. Data Scans: Loads file into memory and scans. Column oriented stores. Low memory, high latency. Index based scan: the file is preprocessed and stored in memory with indices.. David Hay . With . Anat Bremler-Barr, Daniel . Krauthgamer. , . Shimrit. . Tzur. David. This research was supported by ERC starting grant 259805. URL Matching. 2. Action . URL. . A1. work. .. com. Gennady Pekhimenko. ACM Student Research Competition. March, 2015. High . Performance Computing . I. s . E. verywhere. 2. Modern memory systems are . b. andwidth . c. onstrained. Energy . e. fficiency . Slobodan Vucetic * Vladimir Coric Zhuang Wang Department of Computer and Information Sciences Temple University Philadelphia, PA 19122, USA * t , y t ), t = 1…T}, where x t -dimensional inp Qiuping Wang. *. , . Jinhong. Li. *. , Wen Xia. #. Erik . Kruus. ^. , . Biplob. Debnath. ^. , Patrick P. C. Lee. *. *. The Chinese University of Hong Kong (CUHK). #. Harbin Institute of Technology, Shenzhen.