PPT-DICE: Compressing DRAM Caches for Bandwidth and Capacity

Author : briana-ranney | Published Date : 2020-04-06

Vinson Young Prashant Nair Moinuddin Qureshi 1 MOOREs LAW HITS BANDWIDTH WALL 2 Moores scaling encounters Bandwidth Wall 3DDRAM MITIGATES BANDWIDTH WALL 3 3DDRAM

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DICE: Compressing DRAM Caches for Bandwidth and Capacity: Transcript

Vinson Young Prashant Nair Moinuddin Qureshi 1 MOOREs LAW HITS BANDWIDTH WALL 2 Moores scaling encounters Bandwidth Wall 3DDRAM MITIGATES BANDWIDTH WALL 3 3DDRAM Hybrid Memory Cube HMC from Micron . Gigascale. DRAM caches. Chiachen Chou, Georgia Tech. Aamer. . Jaleel. , NVIDIA*. Moinuddin. K. . Qureshi. , Georgia Tech. ISCA 2015. Portland, OR. June 15 , 2015. 3D DRAM Helps Mitigate Bandwidth WALL. 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. …. K. . Qureshi. ECE, Georgia Tech. Gabriel H. Loh, AMD. Fundamental Latency Trade-offs. in Architecting DRAM Caches. MICRO 2012. 3-D Memory Stacking. 3-D Stacked memory can provide large caches at high . 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. Off-Chip Power-Area-Timing Models. Norman P. . Jouppi. ¥. , Andrew B. Kahng. †‡. ,. Naveen Muralimanohar. ¥. , . Vaishnav Srinivas. †. November 6. th. , 2012. ECE. †. and CSE. ‡. Departments. Cody Williams. Overall Bandwidth Growth in Asia. Overall Bandwidth Growth in . Oceania. Comparing Growth by Region. Annual Growth in International Used Bandwidth, 2006-2015. How Asia Bandwidth is Connected. High-Bandwidth, Energy-efficient DRAM Architectures for GPU systems. GPUs Demand High DRAM Bandwidth. GPUs Demand High DRAM Bandwidth. 2008: NVIDIA Tesla GT200. 512-bits @ 2.2 . Gbps. GPUs Demand High DRAM Bandwidth. Sep 17, 2017. 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. LOGISTICS. 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. Improving 3D-Stacked Memory Bandwidth at Low Cost. Donghyuk Lee, . Saugata Ghose. ,. Gennady . Pekhimenko. , Samira Khan, . Onur. . Mutlu. Carnegie Mellon University. HiPEAC. 2016. cell array. peripheral logic. Haonan. Wang, Fan Luo, . Mohamed Ibrahim. . (College of William and Mary), . Onur. . Kayiran. (AMD), . Adwait Jog (College of William and Mary). Single-Application Execution on GPUs. 2. GPU. Kernel-1 (K1). Xiangyao. Yu. 1. , Christopher Hughes. 2. , . Nadathur. Satish. 2. , . Onur. Mutlu. 3. , Srinivas . Devadas. 1. 1. MIT . 2 . Intel Labs . 3. ETH Zürich. Motivation. In-package DRAM has . Lecture 7: Emerging Memory Technologies. Prof. . Onur. . Mutlu. Carnegie Mellon University. 9/21/2012. Reminder: Review Assignments. Due: Friday, September 21, 11:59pm.. Smith, “. Architecture and applications of the HEP multiprocessor computer system.

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