'Fast memory' diaporamas de présentation

Physical Infrastructure

Physical Infrastructure. Week 1 INFM 603. Agenda. The Computer The Internet The Web T he C ourse. Source: Wikipedia. Source: Wikipedia. Source: Wikipedia. Source: Wikipedia. Source: Wikipedia. The Big Picture. Memory. Processor. Network. Hardware Processing Cycle.

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James Demmel cs.berkeley/~demmel/cs267_Spr15/

CS267 Lecture 2 Single Processor Machines: Memory Hierarchies and Processor Features Case Study: Tuning Matrix Multiply. James Demmel http://www.cs.berkeley.edu/~demmel/cs267_Spr15/. Rough List of Topics. Basics of computer architecture, memory hierarchies, performance

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Single Processor Machines: Memory Hierarchies and Processor Features

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Jim Demmel EECS & Math Departments, UC Berkeley demmel@cs.berkeley

Minimizing Communication in Numerical Linear Algebra www.cs.berkeley.edu/~demmel Case Study: Matrix Multiply. Jim Demmel EECS & Math Departments, UC Berkeley demmel@cs.berkeley.edu. Why Matrix Multiplication?. An important kernel in many problems Appears in many linear algebra algorithms

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James Demmel demmel@cs.berkeley cs.berkeley/~demmel/cs267_Spr06

High Performance Programming on a Single Processor: Memory Hierarchies Matrix Multiplication Automatic Performance Tuning. James Demmel demmel@cs.berkeley.edu www.cs.berkeley.edu/~demmel/cs267_Spr06. Outline. Idealized and actual costs in modern processors Memory hierarchies

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Jim Demmel EECS & Math Departments UC Berkeley

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Single Processor Optimizations Matrix Multiplication Case Study

Single Processor Optimizations Matrix Multiplication Case Study. Kathy Yelick yelick@cs.berkeley.edu www.cs.berkeley.edu/~yelick/cs267_spr07. Outline. Recap from Lecture 2 Memory hierarchy is important to performance Use of simple performance models to understand performance

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CSC D70: Compiler Optimization Memory Optimizations

CSC D70: Compiler Optimization Memory Optimizations. Prof. Gennady Pekhimenko University of Toronto Winter 2019. The content of this lecture is adapted from the lectures of Todd Mowry, Greg Steffan , and Phillip Gibbons. Pointer Analysis (Summary).

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Lecture #1

Lecture #1. Computer System Overview. ?? ??. ????? ??? ???? ????? ???? ????? ????? ??? ? ?? ??? ???? ????? ?? ??? ??? ???? ??? ????. ??? ???? ??. ??? ???? ??? ?? ????( Hardware) ?????( Software) ??? ?????( System Software) ????( Operating System) ????( Utility)

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Lecture 5

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15-853: Algorithms in the Real World

15-853: Algorithms in the Real World. Locality I: Cache-aware algorithms Introduction Sorting List ranking B-trees Buffer trees. RAM Model. Standard theoretical model for analyzing algorithms: Infinite memory size Uniform access cost

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Memory Hierarchies & Optimizations Case Study: Tuning Matrix Multiply

Memory Hierarchies & Optimizations Case Study: Tuning Matrix Multiply. Based on slides by: Kathy Yelick www.cs.berkeley.edu/~yelick/cs194f07 & James Demmel and Horst Simon http://www.cs.berkeley.edu/~demmel/cs267_Spr10/. Motivation.

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14:332:331 Computer Architecture and Assembly Language Spring 2005 Lecture 1

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Bob Lucas nersc/~dhbailey/cs267

CS 267 Applications of Parallel Computers Lecture 2: Memory Hierarchies and Optimizing Matrix Multiplication. Bob Lucas http://www.nersc.gov/~dhbailey/cs267. Millennium Accounts. To get Millenium accounts, students need to get EECS Instructional Accounts

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Computer System Overview

Computer System Overview. Chapter 1. An Operating System makes the computing power available to users by controlling the hardware Let us review the aspects of computer hardware which are important for the OS. Basic Components. Processor (CPU) Main Memory (aka real memory, aka primary memory)

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Microprogramming and Exceptions 14 October 2013

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ROD DAQ Workshop February 6-7, 2003

ROD DAQ Workshop February 6-7, 2003. DSP Software Update. Isr and Data Handling. MDSP initialization, Rev B & Rev C RODs. Histogramming code. Douglas Ferguson UW-Madison & LBL. ISR and Data Handling. Event Based Data:. Event based data allows the DMA ISR to complete

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Nicolas Nicolaou Voting Technology Research ( VoTeR ) Center

24th Annual ACM Symposium on Applied Computing SAC 2009, Honolulu, Hawaii. Taking Total Control of Voting Systems: Firmware Manipulations on an Optical Scan Voting Terminal. Joint work with: Seda Davtyan, Sotiris Kentros, Aggelos Kiayias, Laurent Michel,

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CS61C Midterm #2 Review Session

CS61C Midterm #2 Review Session. A little Cache goes a long way. The Ideal Memory System. Fast Cheap (Large). Actual Memory Systems. Fast, Expensive (Small). Slow, Cheap (Large). Idea: Multilevel Memory (cache). +. =. The Cache. CPU. Store recently used data in fast memory Cache Hit

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Problem 3.2 Paging Algorithms-Time & Space Requirements

Problem 3.2 Paging Algorithms-Time & Space Requirements. Problem:What are the space and time requirements of LIFO, LFU, and LED? LRU: (least-recently-used): when eviction is necessary, replace the page whose most recent request was earliest.

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