PPT-Micro-Pages: Increasing DRAM Efficiency with Locality-Aware

Author : kittie-lecroy | Published Date : 2016-12-13

Kshitij Sudan Niladrish Chatterjee David Nellans Manu Awasthi Rajeev Balasubramonian Al Davis School of Computing University of Utah ASPLOS2010 DRAM Memory

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Micro-Pages: Increasing DRAM Efficiency with Locality-Aware: Transcript

Kshitij Sudan Niladrish Chatterjee David Nellans Manu Awasthi Rajeev Balasubramonian Al Davis School of Computing University of Utah ASPLOS2010 DRAM Memory Constraints. Niladrish. . Chatterjee. Manjunath. . Shevgoor. Rajeev . Balasubramonian. Al Davis. Zhen Fang. ‡†. Ramesh . Illikkal. *. Ravi . Iyer. *. University of Utah , NVidia. ‡. and Intel Labs*. †. Optimization. Techniques. . Presented by . Preethi Rajaram. CSS 548 Introduction to Compilers . Professor Carol Zander. Fall 2012 . Why?. Processor Speed . -. increasing at a faster rate than the memory speed. 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. …. Zhenhua . Guo. , Geoffrey Fox, Mo Zhou. Outline. Introduction. Data Locality and Fairness. Experiments. Conclusions. MapReduce Execution Overview. 3. Google File System. Read input data. Data locality. Bank Privatization for Predictability and Temporal Isolation. Sungjun. . Kim . Columbia . University. Edward A. Lee . UC . Berkeley . Isaac . Liu . UC Berkeley. Hiren. D. Patel University of Waterloo. 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. DRAM Scaling. Prof. Onur Mutlu. http://www.ece.cmu.edu/~omutlu. onur@cmu.edu. HiPEAC. ACACES Summer School 2013. July 15-19, . 2013. The Main Memory System. Main memory is a critical component of all computing systems. Zhenhua . Guo. , Geoffrey Fox, Mo Zhou. Outline. Introduction. Data Locality and Fairness. Experiments. Conclusions. MapReduce Execution Overview. 3. Google File System. Read input data. Data locality. UCI Annual Meeting. City of Hampton. May 25, 2017. David . S. Jarman. , P.E.. Transportation Project Management Supervisor. City of Virginia . Beach. Project Delivery Options Available. UCI . Member. Access Locality. Hasan Hassan,. Gennady . Pekhimenko. , . Nandita Vijaykumar, . Vivek. . Seshadri. , Donghyuk Lee, Oguz Ergin, . Onur. . Mutlu. Executive Summary. Goal. : . Reduce average DRAM access latency with no modification to the existing DRAM chips. 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. Vinson Young. Prashant Nair. Moinuddin Qureshi. 1. MOORE’s LAW HITS BANDWIDTH WALL. 2. Moore’s scaling encounters Bandwidth Wall. 3D-DRAM MITIGATES BANDWIDTH WALL. 3. 3D-DRAM. Hybrid Memory Cube (HMC) from Micron, . Daniel Burk. What is a Predictive Model?. A GIS based model attempting to determine fossil locality potential. 1. Start with known fossil localities. 2. Compare their characteristics to other places.

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