PPT-TLC: A Tag-less Cache for reducing dynamic first level Cache Energy

Author : marina-yarberry | Published Date : 2019-12-11

TLC A Tagless Cache for reducing dynamic first level Cache Energy Presented by Rohit Reddy Takkala Introduction First level caches are performance critical and are

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TLC: A Tag-less Cache for reducing dynamic first level Cache Energy: Transcript

TLC A Tagless Cache for reducing dynamic first level Cache Energy Presented by Rohit Reddy Takkala Introduction First level caches are performance critical and are therefore optimized for speed Modern processors reduce the miss ratio by using setassociative caches and optimize latency by reading all ways in parallel with the TLBTranslation Lookaside Buffer and tag lookup. Message Passing Sharedmemory single copy of shared data in memory threads communicate by readingwriting to a shared location Messagepassing each thread has a copy of data in its own private memory that other threads cannot access threads communicate for 3D memory systems. CAMEO. 12/15/2014 MICRO. Cambridge, UK. Chiachen Chou, Georgia Tech. Aamer. . Jaleel. , Intel. Moinuddin. K. . Qureshi. , Georgia Tech. Executive Summary. How to use . S. tacked DRAM: Cache or Memory. 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. Cache. Some material adapted from Mohamed Younis, UMBC CMSC 611 Spr 2003 course slides. Some material adapted from Hennessy & Patterson / © 2003 Elsevier Science. Control. Datapath. Secondary. Storage. + . Also Affiliated with NSF Center for High-Performance Reconfigurable Computing . This work was supported by National Science Foundation (NSF) grant CNS-0953447 . Tosiron Adegbija. 1. , Ann Gordon-Ross. Memory and Performance. Many . of the following slides are taken with permission from . Complete . Powerpoint. Lecture Notes for. Computer Systems: A Programmer's Perspective (CS:APP). Randal E. Bryant. Characterizing Roles of Front-end Servers in . End. -to-. End. . Performance of Dynamic Content Distribution . 46842197. Li . ZHANG. 78884704 . . Dakuo WANG. 30165502 . . Xuejie. SUN. and . its usage . in . the real . world. Ivan . Chepurnyi. Owner. EcomDev. BV. About me. Meet Magento. Technical Consultant, Owner at EcomDev B.V.. Started as one of the first five developers in original Magento core team. + . Also Affiliated with NSF Center for High-Performance Reconfigurable Computing . Tosiron Adegbija. 1. , Ann Gordon-Ross. 1+. ,. . and . Arslan. Munir. 2. 1. Department . of Electrical and Computer . + . Also Affiliated with NSF Center for High-Performance Reconfigurable Computing . This work was supported by National Science Foundation (NSF) grant CNS-0953447 . Tosiron Adegbija and Ann Gordon-Ross. document contains proprietary information of Conversant and may not be reproduced in any form or disclosed to any third party without the expressed written permission of a duly authorized representative from Conversant . Direct-mapped caches. Set-associative caches. Impact of caches on performance. CS 105. Tour of the Black Holes of Computing. Cache Memories. C. ache memories . are small, fast SRAM-based memories managed automatically in hardware. Internet . has many user. Issues with access latency (lag). Server crashing. How to solve?. One solution, Web Cache. Web Cache. What is web cache?. Cache “. a place of . storage”. Web cache – “a . with Idle GPU Core Resources. Sina. . Darabi. , Mohammad . Sadrosadati. , . Joël . Lindegger. ,. Negar . Akbarzadeh. , . Mohammad Hosseini, . Jisung. Park, . Juan Gómez-Luna, Hamid . Sarbazi. -Azad, .

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