PPT-Scalable Many-Core Memory Systems Topic 1: DRAM Basics and

Author : tatyana-admore | Published Date : 2017-08-01

DRAM Scaling Prof Onur Mutlu httpwwwececmueduomutlu onurcmuedu HiPEAC ACACES Summer School 2013 July 1519 2013 The Main Memory System Main memory is a critical

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Scalable Many-Core Memory Systems Topic 1: DRAM Basics and: Transcript

DRAM Scaling Prof Onur Mutlu httpwwwececmueduomutlu onurcmuedu HiPEAC ACACES Summer School 2013 July 1519 2013 The Main Memory System Main memory is a critical component of all computing systems. by Parallelizing Refreshes. with Accesses. Donghyuk. Lee, . Zeshan. . Chishti. , . Alaa. . Alameldeen. , Chris Wilkerson, . Yoongu. Kim, . Onur. . Mutlu. Kevin Chang. Executive Summary. DRAM . refresh interferes with memory accesses. 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. Ph.D. Thesis Proposal. Kshitij Sudan. Thesis Statement. Improving DRAM access latency, power consumption, and capacity by leveraging intelligent data placement.. Overview. CPU. MC. DIMM. …. Prashant. Nair. Chia-Chen Chou . Moinuddin Qureshi. 1. Dynamic Random Access Memory (DRAM) used as main memory. DRAM stores data as charge on capacitor. Leakage. DRAM cells leak data!. DRAM Chip. 1. Jaewoong. . Sim. *, Gabriel H. Loh. +. , Vilas Sridharan. #. , Mike O’Connor. +. June . 2013 . *Georgia Tech. +. AMD Research. #. AMD RAS Architecture. Die-stacked Memory. Die-stacking is coming along, esp. DRAM. Kshitij. Sudan. , . Niladrish. . Chatterjee. , David . Nellans. , Manu . Awasthi. , Rajeev . Balasubramonian. , Al Davis. School of Computing, University of Utah. ASPLOS-2010. DRAM Memory Constraints. Low-Power High-Performance Computing. Jie. Meng, Daniel . Rossell. , and . Ayse. K. . Coskun. Performance and Energy Aware Computing Lab (PEAC-Lab). Electrical and Computer Engineering Department. Boston University. future of computing. Presentation to the Orlando chapter of INCOSE. August 16. th. , 2017. Ian Phillips, ESEP. Principal Systems Architect. Lockheed Martin EBS. Ian.phillips@lmco.com. Agenda. Motivation for Memory Driven Compute. and the Implications for Performance Optimization. Samuel Williams. 1,2. Jonathan Carter. 2. , Richard Vuduc. 3. , Leonid Oliker. 1,2. , John Shalf. 2. , . Katherine Yelick. 1,2. , James Demmel. 1,2. by Exploiting the Variation in Local . Bitlines. . Jeremie S. Kim. . Minesh. Patel . Hasan Hassan . Onur. . Mutlu. . Motivation. : DRAM latency is a . major performance bottleneck. Problem. Mar 3, 2016. COMPUTER ARCHITECTURE . CS 6354. Main Memory. The content and concept of this course are adapted from CMU ECE 740. AGENDA. Logistics. Review . from last . lecture. Main Memory. 2. ANONYMOUS FEEDBACK. Prof. Onur Mutlu. Carnegie Mellon University. Main Memory Lectures. These slides are . from the . Scalable . Memory Systems. course . taught at . ACACES . 2013 (July 15-19, 2013). Course Website:. http. Vivek Seshadri. Thomas Mullins, . Amirali. . Boroumand. , Onur Mutlu, . Phillip B. . Gibbons, Michael A. Kozuch, . Todd C. Mowry. Executive summary. Problem: Non-unit . strided. accesses. Present in many applications. Large scale computing systems. Scalability . issues. Low level and high level communication abstractions in scalable systems. Network interface . Common techniques for high performance communication.

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