User Visible Registers. CPU Structure and Function Ch 11. General CPU Organization (4) Control and Status Registers (5) Register Organisation (4)

Size: px
Start display at page:

Download "User Visible Registers. CPU Structure and Function Ch 11. General CPU Organization (4) Control and Status Registers (5) Register Organisation (4)"

Transcription

1 PU Stuctue and Function h Geneal Oganisation Registes Instuction ycle Pipelining anch Pediction Inteupts Use Visible Registes Vaies fom one achitectue to anothe Geneal pupose egiste (GPR) ata, addess, index, P, condition,. ata egiste Int, FP, ouble, Index Addess egiste Segment and stac pointes only pivileged instuction can wite? ondition codes esult of some pevious ALU opeation 4 Geneal PU Oganization (4) ALU does all eal wo Registes data stoed hee Intenal PU us ontol Moe in haptes 4-5 detemines who does what when diven by cloc uses contol signals (wies) to contol what evey cicuit is doing at any given cloc cycle Fig.. Fig..2 2 ontol and Status Registes (5) P next instuction (not cuent!) pat of pocess state IR, Instuction (ecoding) Registe cuent instuction MAR, Memoy Addess Registe cuent memoy addess MR, Memoy uffe Registe cuent data to/fom memoy PSW, Pogam Status Wod what is allowed? What is going on? pat of pocess state Fig..7 5 Registe Oganisation (4) Registes mae up PU wo space Use visible egistes accessible diectly via instuctions ontol and status egistes may be accessible indiectly via instuctions may be accessible only intenally Intenal latches fo tempoay stoage duing instuction execution E.g., ALU opeand eithe fom constant in instuction o fom machine egiste A R,R2,R3 Neq Loop HW exception 3 PSW - Pogam Status Wod (6) State info fom latest ALU-op Sign, zeo? ay (fo multiwod ALU ops)? Oveflow? Inteupts that ae enabled/disabled? Pending inteupts? PU execution mode (supeviso, use)? Stac pointe, page table pointe? I/O egistes? 6 hapte, PU Stuctue and Function

2 Instuction ycle (4) asic cycle with inteupt handling Indiect cycle Figs.5-6 ata Flow Figs.7-9 PU, us, Memoy ata Path PU s intenal data bus o data mesh All computation is data tansfomations occuing on the data path ontol signals detemine data flow & action fo each cloc cycle Fig..4 Fig a s O d e Pipelined Laundy () A 6 PM fo one load Latency 90 minutes pe load.5 loads pe hou houghput Aveage speed Max speed?.5 load pe hou Pipelined laundy taes 3.5 hous fo 4 loads At best case, laundy is completed evey 40 minutes 0 Pipeline Example Laundy Example (avid A. Patteson) Ann, ian, athy, ave each have one load of clothes A to wash, dy, and fold Washe taes 30 minutes ye taes 40 minutes Folde taes 20 minutes (liuuhihna) Pipelining Lessons (4) Pipelining doesn t help latency of single tas, but it helps thoughput of the entie woload A Pipeline ate limited by slowest pipeline stage Multiple tass opeating simultaneously Potential speedup = maximum possible speedup = Numbe pipe stages 6 PM (nopeutus) 8 a s O d e A Sequential Laundy (6) 6 PM fo one load (viive?) Latency.5 hous pe load Sequential laundy taes 6 hous fo 4 loads If they leaned pipelining, how long would laundy tae? houghput Midnight 0.67 loads pe hou 9 Pipelining Lessons (3) Unbalanced lengths of pipe stages educes speedup May need moe esouces Enough electical cuent to un both washe and dye simultaneously? Need to have at least 2 people pesent all the time? to fill pipeline and time to dain it educes speedup 6 PM A fill dain 2 hapte, PU Stuctue and Function 2

3 2-stage Instuction Execution Pipeline (4) Fig..0 Good: instuction pe-fetch at the same time as execution of pevious instuction ad: execution phase is longe, I.e., fetch stage is sometimes idle ad: Sometimes (jump, banch) wong instuction is fetched evey 6 th instuction? Not enough paallelism moe stages? Pipeline Execution (3) to execute one instuction (latency, seconds) may be longe than fo non-pipelined machine exta latches to stoe intemediate esults to execute 000 instuctions (seconds) is shote (bette) than that fo non-pipelined machine, I.e., houghput (instuctions pe second) fo pipelined machine is bette (bigge) than that fo non-pipelined machine Is this good o bad? Why? 3 6 Anothe Possible Instuction Execution Pipeline FE -Fetch instuction I -ecode instuction O -alculate opeand effective addesses FO -Fetch opeands fom memoy EI -Execute Instuction WO -Wite opeand (esult) to memoy Fig.. Pipeline Speedup Poblems Some stages ae shote than the othes ependencies between instuctions contol dependency E.g., conditional banch decision now only afte EI stage Fig..2 Fig Pipeline Speedup (3) No pipeline, 9 instuctions Not evey instuction uses evey stage seial execution actually even faste speedup even smalle will not affect pipeline speed unused stage PU idle (execution bubble ) 54 time units Fig.. 6 stage pipeline, 9 instuctions 4 time units Speedup = 9 * 6 old new = 54/4 = 3.86 < 6! (nopeutus) 5 Pipeline Speedup Poblems ependencies between instuctions data dependency One instuction depends on data poduced by some ealie instuction stuctual dependency Many instuctions need the same esouce at the same time memoy bus, ALU, Fig..2 Known afte EI stage MUL R,R2,R3 LOA R6,A(R) Needed in O stage WO SORE R,VaX A R2,R3,VaY MUL R3,R4,R5 FI FO 8 hapte, PU Stuctue and Function 3

4 ycle [ ] + d = + d d τ = max τ τ ovehead? i m >> max gate delay in stage (min) cycle time delay in latches between stages (= cloc pulse, o cloc cycle time) gate delay in stage i ycle time is the same fo all stages time (in cloc pulses) to execute the cycle Each stage executed in one cycle time Longest stage detemines min cycle time max MHz ate fo system cloc anch Poblem Solutions (5) elayed anch compile places some useful instuctions ( o moe!) afte banch (o jump) instuctions these instuctions ae almost completely executed when banch decision is nown less actual wo lost Fig. 2.7 can be difficult to do 9 22 Pipeline Speedup n instuctions, stages not pipelined: = nτ = [ + ( n ) ]τ pipelined: cycles until st instuction completes n instuctions, stages τ = stage delay = cycle time (pessimistic because of assuming that each stage would still have τ cycle time) cycle fo each of the est (n-) instuctions anch Pobl. Solutions (contd) (6) Multiple instuction steams execute speculatively in both diections Poblem: we do not now the banch taget addess ealy! if one diection splits, continue each way again lots of hadwae speculative esults (egistes!), contol speculative instuctions may delay eal wo bus & egiste contention? need to be able to cancel not-taen instuction steams in pipeline Pipeline Speedup () n instuctions, stages not pipelined: = nτ = [ + ( n ) ]τ pipelined: Speedup with stages: S Fig..4 = = n instuctions, stages τ = stage delay = cycle time (pessimistic because of assuming that each stage would still have τ cycle time) nτ = n [ + ( n ) ] τ [ + ( n ) ] anch Pobl. Solutions (contd) (2) Pefetch anch aget IM 360/9 (967) pefetch just banch taget instuction do not execute it, I.e., do only FI stage if banch tae, no need to wait fo memoy Loop uffe eep n most ecently fetched instuctions in high speed buffe inside PU wos fo small loops (at most n instuctions) 2 24 hapte, PU Stuctue and Function 4

5 anch Pobl. Solutions (contd) (5) anch Pediction guess (intelligently) which way banch will go static pediction: all taen o all not taen static pediction based on opcode E.g., because LE instuction is usually at the end of loop, guess taen dynamic pediction taen/not taen based on pevious time this instuction was executed need space ( bit) in PU fo each (?) banch end of loop always wong twice! extension based on two pevious time execution need moe space (2 bits) Fig PU Example: PoweP Use Visible Registes 32 geneal pupose egs, each 64 bits Exception eg (XER), 32 bits 32 FP egs, each 64 bits FP status & contol (FPSR), 32 bits banch pocessing unit egistes ondition, 32 bits 8 fields, each 4 bits identity given in instuctions Lin eg, 64 bits E.g., etun addess ount egs, 64 bits E.g., loop counte Fig..22 Fig..23a able.3 Fig..23b able.4 28 anch Addess Pediction (3) It is not enough to now whethe banch is taen o not Must now also banch addess to fetch taget instuction anch Histoy able state infomation to guess whethe banch will be taen o not pevious banch taget addess stoed in PU fo each (?) banch PU Example: PoweP Inteupts cause system condition o event instuction able anch Histoy able ached PoweP 620 enties only fo most ecent banches anch instuction addess, o tag bits fo it anch taen pediction bits (2?) aget addess (fom pevious time) o complete taget instuction? Why cached expensive hadwae, not enough space fo all possible banches at looup time chec fist whethe enty fo coect banch instuction PU Example: PoweP Machine State Registe, 64 bits able.6 bit 48: extenal (I/O) inteupts enabled? bit 49: pivileged state o not bits 52&55: which FP inteupts enabled? bit 59: data addess tanslation on/off bit 63: big/little endian mode Save/Restoe Regs SRR0 and SRR tempoay data needed fo inteupt handling hapte, PU Stuctue and Function 5

6 Powe P Inteupt Invocation Save etun P to SRR0 able.6 cuent o next instuction at the time of inteupt opy elevant aeas of MSR to SRR opy additional inteupt info to SRR opy fixed new value into MSR diffeent fo each inteupt addess tanslation off, disable inteupts opy inteupt handle enty point to P two possible handles, selection based on bit 57 of oiginal MSR 3 Powe P Inteupt Retun Retun Fom Inteupt (fi) instuction able.6 pivileged Rebuild oiginal MSR fom SRR opy etun addess fom SRR0 to P End of hapte : PU Stuctue -- 5 stage pipelined vesion of datapath (Fig. 6.2) (Patteson-Hennessy, ompute Og & esign, 2nd Ed, 998) 33 hapte, PU Stuctue and Function 6

Lecture 8 Introduction to Pipelines Adapated from slides by David Patterson

Lecture 8 Introduction to Pipelines Adapated from slides by David Patterson Lectue 8 Intoduction to Pipelines Adapated fom slides by David Patteson http://www-inst.eecs.bekeley.edu/~cs61c/ * 1 Review (1/3) Datapath is the hadwae that pefoms opeations necessay to execute pogams.

More information

Introduction To Pipelining. Chapter Pipelining1 1

Introduction To Pipelining. Chapter Pipelining1 1 Intoduction To Pipelining Chapte 6.1 - Pipelining1 1 Mooe s Law Mooe s Law says that the numbe of pocessos on a chip doubles about evey 18 months. Given the data on the following two slides, is this tue?

More information

Lecture Topics ECE 341. Lecture # 12. Control Signals. Control Signals for Datapath. Basic Processing Unit. Pipelining

Lecture Topics ECE 341. Lecture # 12. Control Signals. Control Signals for Datapath. Basic Processing Unit. Pipelining EE 341 Lectue # 12 Instucto: Zeshan hishti zeshan@ece.pdx.edu Novembe 10, 2014 Potland State Univesity asic Pocessing Unit ontol Signals Hadwied ontol Datapath contol signals Dealing with memoy delay Pipelining

More information

UCB CS61C : Machine Structures

UCB CS61C : Machine Structures inst.eecs.bekeley.edu/~cs61c UCB CS61C : Machine Stuctues Lectue SOE Dan Gacia Lectue 28 CPU Design : Pipelining to Impove Pefomance 2010-04-05 Stanfod Reseaches have invented a monitoing technique called

More information

ECE331: Hardware Organization and Design

ECE331: Hardware Organization and Design ECE331: Hadwae Oganization and Design Lectue 16: Pipelining Adapted fom Compute Oganization and Design, Patteson & Hennessy, UCB Last time: single cycle data path op System clock affects pimaily the Pogam

More information

Computer Science 141 Computing Hardware

Computer Science 141 Computing Hardware Compute Science 141 Computing Hadwae Fall 2006 Havad Univesity Instucto: Pof. David Books dbooks@eecs.havad.edu [MIPS Pipeline Slides adapted fom Dave Patteson s UCB CS152 slides and May Jane Iwin s CSE331/431

More information

COSC 6385 Computer Architecture. - Pipelining

COSC 6385 Computer Architecture. - Pipelining COSC 6385 Compute Achitectue - Pipelining Sping 2012 Some of the slides ae based on a lectue by David Culle, Pipelining Pipelining is an implementation technique wheeby multiple instuctions ae ovelapped

More information

COEN-4730 Computer Architecture Lecture 2 Review of Instruction Sets and Pipelines

COEN-4730 Computer Architecture Lecture 2 Review of Instruction Sets and Pipelines 1 COEN-4730 Compute Achitectue Lectue 2 Review of nstuction Sets and Pipelines Cistinel Ababei Dept. of Electical and Compute Engineeing Maquette Univesity Cedits: Slides adapted fom pesentations of Sudeep

More information

CMCS Mohamed Younis CMCS 611, Advanced Computer Architecture 1

CMCS Mohamed Younis CMCS 611, Advanced Computer Architecture 1 CMCS 611-101 Advanced Compute Achitectue Lectue 6 Intoduction to Pipelining Septembe 23, 2009 www.csee.umbc.edu/~younis/cmsc611/cmsc611.htm Mohamed Younis CMCS 611, Advanced Compute Achitectue 1 Pevious

More information

Computer Architecture. Pipelining and Instruction Level Parallelism An Introduction. Outline of This Lecture

Computer Architecture. Pipelining and Instruction Level Parallelism An Introduction. Outline of This Lecture Compute Achitectue Pipelining and nstuction Level Paallelism An ntoduction Adapted fom COD2e by Hennessy & Patteson Slide 1 Outline of This Lectue ntoduction to the Concept of Pipelined Pocesso Pipelined

More information

The Processor: Improving Performance Data Hazards

The Processor: Improving Performance Data Hazards The Pocesso: Impoving Pefomance Data Hazads Monday 12 Octobe 15 Many slides adapted fom: and Design, Patteson & Hennessy 5th Edition, 2014, MK and fom Pof. May Jane Iwin, PSU Summay Pevious Class Pipeline

More information

CISC 662 Graduate Computer Architecture Lecture 6 - Hazards

CISC 662 Graduate Computer Architecture Lecture 6 - Hazards CISC 662 Gaduate Compute Achitectue Lectue 6 - Hazads Michela Taufe http://www.cis.udel.edu/~taufe/teaching/cis662f07 Powepoint Lectue Notes fom John Hennessy and David Patteson s: Compute Achitectue,

More information

Chapter 4 (Part III) The Processor: Datapath and Control (Pipeline Hazards)

Chapter 4 (Part III) The Processor: Datapath and Control (Pipeline Hazards) Chapte 4 (Pat III) The Pocesso: Datapath and Contol (Pipeline Hazads) 陳瑞奇 (J.C. Chen) 亞洲大學資訊工程學系 Adapted fom class notes by Pof. M.J. Iwin, PSU and Pof. D. Patteson, UCB 1 吃感冒藥副作用怎麼辦? http://big5.sznews.com/health/images/attachement/jpg/site3/20120319/001558d90b3310d0c1683e.jpg

More information

Lecture #22 Pipelining II, Cache I

Lecture #22 Pipelining II, Cache I inst.eecs.bekeley.edu/~cs61c CS61C : Machine Stuctues Lectue #22 Pipelining II, Cache I Wiewold cicuits 2008-7-29 http://www.maa.og/editoial/mathgames/mathgames_05_24_04.html http://www.quinapalus.com/wi-index.html

More information

CS 61C: Great Ideas in Computer Architecture. Pipelining Hazards. Instructor: Senior Lecturer SOE Dan Garcia

CS 61C: Great Ideas in Computer Architecture. Pipelining Hazards. Instructor: Senior Lecturer SOE Dan Garcia CS 61C: Geat Ideas in Compute Achitectue Pipelining Hazads Instucto: Senio Lectue SOE Dan Gacia 1 Geat Idea #4: Paallelism So9wae Paallel Requests Assigned to compute e.g. seach Gacia Paallel Theads Assigned

More information

CENG 3420 Computer Organization and Design. Lecture 07: MIPS Processor - II. Bei Yu

CENG 3420 Computer Organization and Design. Lecture 07: MIPS Processor - II. Bei Yu CENG 3420 Compute Oganization and Design Lectue 07: MIPS Pocesso - II Bei Yu CEG3420 L07.1 Sping 2016 Review: Instuction Citical Paths q Calculate cycle time assuming negligible delays (fo muxes, contol

More information

You Are Here! Review: Hazards. Agenda. Agenda. Review: Load / Branch Delay Slots 7/28/2011

You Are Here! Review: Hazards. Agenda. Agenda. Review: Load / Branch Delay Slots 7/28/2011 CS 61C: Geat Ideas in Compute Achitectue (Machine Stuctues) Instuction Level Paallelism: Multiple Instuction Issue Guest Lectue: Justin Hsia Softwae Paallel Requests Assigned to compute e.g., Seach Katz

More information

Administrivia. CMSC 411 Computer Systems Architecture Lecture 5. Data Hazard Even with Forwarding Figure A.9, Page A-20

Administrivia. CMSC 411 Computer Systems Architecture Lecture 5. Data Hazard Even with Forwarding Figure A.9, Page A-20 Administivia CMSC 411 Compute Systems Achitectue Lectue 5 Basic Pipelining (cont.) Alan Sussman als@cs.umd.edu as@csu dedu Homewok poblems fo Unit 1 due today Homewok poblems fo Unit 3 posted soon CMSC

More information

CS 2461: Computer Architecture 1 Program performance and High Performance Processors

CS 2461: Computer Architecture 1 Program performance and High Performance Processors Couse Objectives: Whee ae we. CS 2461: Pogam pefomance and High Pefomance Pocessos Instucto: Pof. Bhagi Naahai Bits&bytes: Logic devices HW building blocks Pocesso: ISA, datapath Using building blocks

More information

CS 61C: Great Ideas in Computer Architecture (Machine Structures) Instruc>on Level Parallelism

CS 61C: Great Ideas in Computer Architecture (Machine Structures) Instruc>on Level Parallelism Agenda CS 61C: Geat Ideas in Compute Achitectue (Machine Stuctues) Instuc>on Level Paallelism Instuctos: Randy H. Katz David A. PaJeson hjp://inst.eecs.bekeley.edu/~cs61c/fa10 Review Instuc>on Set Design

More information

CENG 3420 Lecture 07: Pipeline

CENG 3420 Lecture 07: Pipeline CENG 3420 Lectue 07: Pipeline Bei Yu byu@cse.cuhk.edu.hk CENG3420 L07.1 Sping 2017 Outline q Review: Flip-Flop Contol Signals q Pipeline Motivations q Pipeline Hazads q Exceptions CENG3420 L07.2 Sping

More information

CSE4201. Computer Architecture

CSE4201. Computer Architecture CSE 4201 Compute Achitectue Pof. Mokhta Aboelaze Pats of these slides ae taken fom Notes by Pof. David Patteson at UCB Outline MIPS and instuction set Simple pipeline in MIPS Stuctual and data hazads Fowading

More information

CS 61C: Great Ideas in Computer Architecture Instruc(on Level Parallelism: Mul(ple Instruc(on Issue

CS 61C: Great Ideas in Computer Architecture Instruc(on Level Parallelism: Mul(ple Instruc(on Issue CS 61C: Geat Ideas in Compute Achitectue Instuc(on Level Paallelism: Mul(ple Instuc(on Issue Instuctos: Kste Asanovic, Randy H. Katz hbp://inst.eecs.bekeley.edu/~cs61c/fa12 1 Paallel Requests Assigned

More information

Review from last lecture

Review from last lecture CSE820 Gaduate Compute Achitectue Week 3 Pefomance + Pipeline Review Based on slides by David Patteson Review fom last lectue Tacking and extapolating technology pat of achitect s esponsibility Expect

More information

Any modern computer system will incorporate (at least) two levels of storage:

Any modern computer system will incorporate (at least) two levels of storage: 1 Any moden compute system will incopoate (at least) two levels of stoage: pimay stoage: andom access memoy (RAM) typical capacity 32MB to 1GB cost pe MB $3. typical access time 5ns to 6ns bust tansfe

More information

THE THETA BLOCKCHAIN

THE THETA BLOCKCHAIN THE THETA BLOCKCHAIN Theta is a decentalized video steaming netwok, poweed by a new blockchain and token. By Theta Labs, Inc. Last Updated: Nov 21, 2017 esion 1.0 1 OUTLINE Motivation Reputation Dependent

More information

Accelerating Storage with RDMA Max Gurtovoy Mellanox Technologies

Accelerating Storage with RDMA Max Gurtovoy Mellanox Technologies Acceleating Stoage with RDMA Max Gutovoy Mellanox Technologies 2018 Stoage Develope Confeence EMEA. Mellanox Technologies. All Rights Reseved. 1 What is RDMA? Remote Diect Memoy Access - povides the ability

More information

The Java Virtual Machine. Compiler construction The structure of a frame. JVM stacks. Lecture 2

The Java Virtual Machine. Compiler construction The structure of a frame. JVM stacks. Lecture 2 Compile constuction 2009 Lectue 2 Code geneation 1: Geneating code The Java Vitual Machine Data types Pimitive types, including intege and floating-point types of vaious sizes and the boolean type. The

More information

GCC-AVR Inline Assembler Cookbook Version 1.2

GCC-AVR Inline Assembler Cookbook Version 1.2 GCC-AVR Inline Assemble Cookbook Vesion 1.2 About this Document The GNU C compile fo Atmel AVR isk pocessos offes, to embed assembly language code into C pogams. This cool featue may be used fo manually

More information

A Memory Efficient Array Architecture for Real-Time Motion Estimation

A Memory Efficient Array Architecture for Real-Time Motion Estimation A Memoy Efficient Aay Achitectue fo Real-Time Motion Estimation Vasily G. Moshnyaga and Keikichi Tamau Depatment of Electonics & Communication, Kyoto Univesity Sakyo-ku, Yoshida-Honmachi, Kyoto 66-1, JAPAN

More information

Overview of Control. CS 152 Computer Architecture and Engineering Lecture 11. Multicycle Controller Design

Overview of Control. CS 152 Computer Architecture and Engineering Lecture 11. Multicycle Controller Design S 152 ompute chitectue and Engineeing Lectue 11 Multicycle ontolle Design Oveview of ontol ontol may be designed using one of seveal initial epesentations. The choice of sequence contol, and how logic

More information

Review: Moore s Law. EECS 252 Graduate Computer Architecture Lecture 2. Review: Joy s Law in ManyCore world. Bell s Law new class per decade

Review: Moore s Law. EECS 252 Graduate Computer Architecture Lecture 2. Review: Joy s Law in ManyCore world. Bell s Law new class per decade EECS 252 Gaduate Compute Achitectue Lectue 2 ℵ 0 Review of Instuction Sets, Pipelines, and Caches Januay 26 th, 2009 Review Mooe s Law John Kubiatowicz Electical Engineeing and Compute Sciences Univesity

More information

a Not yet implemented in current version SPARK: Research Kit Pointer Analysis Parameters Soot Pointer analysis. Objectives

a Not yet implemented in current version SPARK: Research Kit Pointer Analysis Parameters Soot Pointer analysis. Objectives SPARK: Soot Reseach Kit Ondřej Lhoták Objectives Spak is a modula toolkit fo flow-insensitive may points-to analyses fo Java, which enables expeimentation with: vaious paametes of pointe analyses which

More information

High performance CUDA based CNN image processor

High performance CUDA based CNN image processor High pefomance UDA based NN image pocesso GEORGE VALENTIN STOIA, RADU DOGARU, ELENA RISTINA STOIA Depatment of Applied Electonics and Infomation Engineeing Univesity Politehnica of Buchaest -3, Iuliu Maniu

More information

All lengths in meters. E = = 7800 kg/m 3

All lengths in meters. E = = 7800 kg/m 3 Poblem desciption In this poblem, we apply the component mode synthesis (CMS) technique to a simple beam model. 2 0.02 0.02 All lengths in metes. E = 2.07 10 11 N/m 2 = 7800 kg/m 3 The beam is a fee-fee

More information

Getting Started PMW-EX1/PMW-EX3. 1 Rotate the grip with the RELEASE button pressed. Overview. Connecting the Computer and PMW-EX1/EX3

Getting Started PMW-EX1/PMW-EX3. 1 Rotate the grip with the RELEASE button pressed. Overview. Connecting the Computer and PMW-EX1/EX3 A PMW-EX1/PMW-EX3 Getting Stated Oveview This document descibes how to use the XDCAM EX Vesion Up Tool (heeafte Vesion Up Tool ) to upgade the PMW-EX1 and PMW-EX3 to vesion 1.20 (PMW-EX1) o vesion 1.10

More information

dc - Linux Command Dc may be invoked with the following command-line options: -V --version Print out the version of dc

dc - Linux Command Dc may be invoked with the following command-line options: -V --version Print out the version of dc - CentOS 5.2 - Linux Uses Guide - Linux Command SYNOPSIS [-V] [--vesion] [-h] [--help] [-e sciptexpession] [--expession=sciptexpession] [-f sciptfile] [--file=sciptfile] [file...] DESCRIPTION is a evese-polish

More information

Chapter 8. Pipelining

Chapter 8. Pipelining Chapter 8. Pipelining Overview Pipelining is widely used in modern processors. Pipelining improves system performance in terms of throughput. Pipelined organization requires sophisticated compilation techniques.

More information

GARBAGE COLLECTION METHODS. Hanan Samet

GARBAGE COLLECTION METHODS. Hanan Samet gc0 GARBAGE COLLECTION METHODS Hanan Samet Compute Science Depatment and Cente fo Automation Reseach and Institute fo Advanced Compute Studies Univesity of Mayland College Pak, Mayland 07 e-mail: hjs@umiacs.umd.edu

More information

Pre-requisites. This is a textbook-based course. Chapter 1. Pipelines, Performance, Caches, and Virtual Memory. January 2009 Paul H J Kelly

Pre-requisites. This is a textbook-based course. Chapter 1. Pipelines, Performance, Caches, and Virtual Memory. January 2009 Paul H J Kelly 332 Advanced Compute Achitectue Chapte 1 Intoduction and eview of Pipelines, Pefomance, Caches, and Vitual Januay 2009 Paul H J Kelly These lectue notes ae patly based on the couse text, Hennessy and Patteson

More information

Multidimensional Testing

Multidimensional Testing Multidimensional Testing QA appoach fo Stoage netwoking Yohay Lasi Visuality Systems 1 Intoduction Who I am Yohay Lasi, QA Manage at Visuality Systems Visuality Systems the leading commecial povide of

More information

MapReduce Optimizations and Algorithms 2015 Professor Sasu Tarkoma

MapReduce Optimizations and Algorithms 2015 Professor Sasu Tarkoma apreduce Optimizations and Algoithms 2015 Pofesso Sasu Takoma www.cs.helsinki.fi Optimizations Reduce tasks cannot stat befoe the whole map phase is complete Thus single slow machine can slow down the

More information

Query Language #1/3: Relational Algebra Pure, Procedural, and Set-oriented

Query Language #1/3: Relational Algebra Pure, Procedural, and Set-oriented Quey Language #1/3: Relational Algeba Pue, Pocedual, and Set-oiented To expess a quey, we use a set of opeations. Each opeation takes one o moe elations as input paamete (set-oiented). Since each opeation

More information

XFVHDL: A Tool for the Synthesis of Fuzzy Logic Controllers

XFVHDL: A Tool for the Synthesis of Fuzzy Logic Controllers XFVHDL: A Tool fo the Synthesis of Fuzzy Logic Contolles E. Lago, C. J. Jiménez, D. R. López, S. Sánchez-Solano and A. Baiga Instituto de Micoelectónica de Sevilla. Cento Nacional de Micoelectónica, Edificio

More information

CPS104 Computer Organization and Programming Lecture 19: Pipelining. Robert Wagner

CPS104 Computer Organization and Programming Lecture 19: Pipelining. Robert Wagner CPS104 Computer Organization and Programming Lecture 19: Pipelining Robert Wagner cps 104 Pipelining..1 RW Fall 2000 Lecture Overview A Pipelined Processor : Introduction to the concept of pipelined processor.

More information

1.3 Multiplexing, Time-Switching, Point-to-Point versus Buses

1.3 Multiplexing, Time-Switching, Point-to-Point versus Buses http://achvlsi.ics.foth.g/~kateveni/534 1.3 Multiplexing, Time-Switching, Point-to-Point vesus Buses n R m Aggegation (multiplexing) Distibution (demultiplexing) Simplest Netwoking, like simplest pogamming:

More information

EE 6900: Interconnection Networks for HPC Systems Fall 2016

EE 6900: Interconnection Networks for HPC Systems Fall 2016 EE 6900: Inteconnection Netwoks fo HPC Systems Fall 2016 Avinash Kaanth Kodi School of Electical Engineeing and Compute Science Ohio Univesity Athens, OH 45701 Email: kodi@ohio.edu 1 Acknowledgement: Inteconnection

More information

Automatically Testing Interacting Software Components

Automatically Testing Interacting Software Components Automatically Testing Inteacting Softwae Components Leonad Gallaghe Infomation Technology Laboatoy National Institute of Standads and Technology Gaithesbug, MD 20899, USA lgallaghe@nist.gov Jeff Offutt

More information

Communication module System Manual Part 9

Communication module System Manual Part 9 Communication module 70.4040 System Manual Pat 9 Contents 1 Intoduction 3 1.1 Peface... 3 1.2 Type designation... 4 2 Indications and contols 5 3 Integated functions 7 3.1 Oveview... 7 3.2 Outputs...

More information

Slotted Random Access Protocol with Dynamic Transmission Probability Control in CDMA System

Slotted Random Access Protocol with Dynamic Transmission Probability Control in CDMA System Slotted Random Access Potocol with Dynamic Tansmission Pobability Contol in CDMA System Intaek Lim 1 1 Depatment of Embedded Softwae, Busan Univesity of Foeign Studies, itlim@bufs.ac.k Abstact In packet

More information

Conversion Functions for Symmetric Key Ciphers

Conversion Functions for Symmetric Key Ciphers Jounal of Infomation Assuance and Secuity 2 (2006) 41 50 Convesion Functions fo Symmetic Key Ciphes Deba L. Cook and Angelos D. Keomytis Depatment of Compute Science Columbia Univesity, mail code 0401

More information

An Optimised Density Based Clustering Algorithm

An Optimised Density Based Clustering Algorithm Intenational Jounal of Compute Applications (0975 8887) Volume 6 No.9, Septembe 010 An Optimised Density Based Clusteing Algoithm J. Hencil Pete Depatment of Compute Science St. Xavie s College, Palayamkottai,

More information

SIMOCODE pro. Motor Management and Control Devices. SIMOCODE pro for Modbus RTU. Answers for industry. Edition 04/2015

SIMOCODE pro. Motor Management and Control Devices. SIMOCODE pro for Modbus RTU. Answers for industry. Edition 04/2015 SIMOCODE po Moto Management and Contol Devices SIMOCODE po fo Modbus RTU Geätehandbuch Configuation Manual Edition 04/2015 Answes fo industy. Intoduction 1 System configuation and commissioning with RTU

More information

A modal estimation based multitype sensor placement method

A modal estimation based multitype sensor placement method A modal estimation based multitype senso placement method *Xue-Yang Pei 1), Ting-Hua Yi 2) and Hong-Nan Li 3) 1),)2),3) School of Civil Engineeing, Dalian Univesity of Technology, Dalian 116023, China;

More information

DYNAMIC STORAGE ALLOCATION. Hanan Samet

DYNAMIC STORAGE ALLOCATION. Hanan Samet ds0 DYNAMIC STORAGE ALLOCATION Hanan Samet Compute Science Depatment and Cente fo Automation Reseach and Institute fo Advanced Compute Studies Univesity of Mayland College Pak, Mayland 07 e-mail: hjs@umiacs.umd.edu

More information

GAS IA-32 Assembly Language Programming Tony Richardson April 19, 2007

GAS IA-32 Assembly Language Programming Tony Richardson April 19, 2007 GAS IA-32 Assembly Language Pogamming Tony Richadson Apil 19, 2007 The following table contains a patial list of IA-32 assembly mnemonics. An S in the mnemonic epesents a size specification lette of eithe

More information

Chapter 5 (a) Overview

Chapter 5 (a) Overview Chapter 5 (a) Overview (a) The principles of pipelining (a) A pipelined design of SRC (b) Pipeline hazards (b) Instruction-level parallelism (ILP) Superscalar processors Very Long Instruction Word (VLIW)

More information

Pipelining. Maurizio Palesi

Pipelining. Maurizio Palesi * Pipelining * Adapted from David A. Patterson s CS252 lecture slides, http://www.cs.berkeley/~pattrsn/252s98/index.html Copyright 1998 UCB 1 References John L. Hennessy and David A. Patterson, Computer

More information

Information Retrieval. CS630 Representing and Accessing Digital Information. IR Basics. User Task. Basic IR Processes

Information Retrieval. CS630 Representing and Accessing Digital Information. IR Basics. User Task. Basic IR Processes CS630 Repesenting and Accessing Digital Infomation Infomation Retieval: Basics Thosten Joachims Conell Univesity Infomation Retieval Basics Retieval Models Indexing and Pepocessing Data Stuctues ~ 4 lectues

More information

Spiral Recognition Methodology and Its Application for Recognition of Chinese Bank Checks

Spiral Recognition Methodology and Its Application for Recognition of Chinese Bank Checks Spial Recognition Methodology and Its Application fo Recognition of Chinese Bank Checks Hanshen Tang 1, Emmanuel Augustin 2, Ching Y. Suen 1, Olivie Baet 2, Mohamed Cheiet 3 1 Cente fo Patten Recognition

More information

Physical simulation for animation

Physical simulation for animation Physical simulation fo animation Case study: The jello cube The Jello Cube Mass-Sping System Collision Detection Integatos Septembe 17 2002 1 Announcements Pogamming assignment 3 is out. It is due Tuesday,

More information

RANDOM IRREGULAR BLOCK-HIERARCHICAL NETWORKS: ALGORITHMS FOR COMPUTATION OF MAIN PROPERTIES

RANDOM IRREGULAR BLOCK-HIERARCHICAL NETWORKS: ALGORITHMS FOR COMPUTATION OF MAIN PROPERTIES RANDOM IRREGULAR BLOCK-HIERARCHICAL NETWORKS: ALGORITHMS FOR COMPUTATION OF MAIN PROPERTIES Svetlana Avetisyan Mikayel Samvelyan* Matun Kaapetyan Yeevan State Univesity Abstact In this pape, the class

More information

Realistic Memories and. 2-level Data Cache Interface (0,n)

Realistic Memories and. 2-level Data Cache Interface (0,n) Realistic Meoies and Caches Pat III Li-Shiuan Peh Copute Science & Atificial Intelligence Lab. Massachusetts Institute of Technology Apil 4, 2012 http://csg.csail.it.edu/6.s078 L15-1 2-level Data Cache

More information

A Non-blocking Directory Protocol for Large-Scale Multiprocessors. Technical Report

A Non-blocking Directory Protocol for Large-Scale Multiprocessors. Technical Report A Non-blocking Diectoy Potocol fo Lage-Scale Multipocessos Technical Repot Depatment of Compute Science and Engineeing Univesity of Minnesota 4-192 EECS Building 200 Union Steet SE Minneapolis, MN 55455-0159

More information

arxiv: v1 [cs.lo] 3 Dec 2018

arxiv: v1 [cs.lo] 3 Dec 2018 A high-level opeational semantics fo hadwae weak memoy models axiv:1812.00996v1 [cs.lo] 3 Dec 2018 Abstact Robet J. Colvin School of Electical Engineeing and Infomation Technology The Univesity of Queensland

More information

Topic -3 Image Enhancement

Topic -3 Image Enhancement Topic -3 Image Enhancement (Pat 1) DIP: Details Digital Image Pocessing Digital Image Chaacteistics Spatial Spectal Gay-level Histogam DFT DCT Pe-Pocessing Enhancement Restoation Point Pocessing Masking

More information

DEADLOCK AVOIDANCE IN BATCH PROCESSES. M. Tittus K. Åkesson

DEADLOCK AVOIDANCE IN BATCH PROCESSES. M. Tittus K. Åkesson DEADLOCK AVOIDANCE IN BATCH PROCESSES M. Tittus K. Åkesson Univesity College Boås, Sweden, e-mail: Michael.Tittus@hb.se Chalmes Univesity of Technology, Gothenbug, Sweden, e-mail: ka@s2.chalmes.se Abstact:

More information

Journal of World s Electrical Engineering and Technology J. World. Elect. Eng. Tech. 1(1): 12-16, 2012

Journal of World s Electrical Engineering and Technology J. World. Elect. Eng. Tech. 1(1): 12-16, 2012 2011, Scienceline Publication www.science-line.com Jounal of Wold s Electical Engineeing and Technology J. Wold. Elect. Eng. Tech. 1(1): 12-16, 2012 JWEET An Efficient Algoithm fo Lip Segmentation in Colo

More information

Chapter 12. CPU Structure and Function. Yonsei University

Chapter 12. CPU Structure and Function. Yonsei University Chapter 12 CPU Structure and Function Contents Processor organization Register organization Instruction cycle Instruction pipelining The Pentium processor The PowerPC processor 12-2 CPU Structures Processor

More information

The Internet Ecosystem and Evolution

The Internet Ecosystem and Evolution The Intenet Ecosystem and Evolution Contents Netwok outing: basics distibuted/centalized, static/dynamic, linkstate/path-vecto inta-domain/inte-domain outing Mapping the sevice model to AS-AS paths valley-fee

More information

Module 6 STILL IMAGE COMPRESSION STANDARDS

Module 6 STILL IMAGE COMPRESSION STANDARDS Module 6 STILL IMAE COMPRESSION STANDARDS Lesson 17 JPE-2000 Achitectue and Featues Instuctional Objectives At the end of this lesson, the students should be able to: 1. State the shotcomings of JPE standad.

More information

Persistent Memory what developers need to know Mark Carlson Co-chair SNIA Technical Council Toshiba

Persistent Memory what developers need to know Mark Carlson Co-chair SNIA Technical Council Toshiba Pesistent Memoy what developes need to know Mak Calson Co-chai SNIA Technical Council Toshiba 2018 Stoage Develope Confeence EMEA. All Rights Reseved. 1 Contents Welcome Pesistent Memoy Oveview Non-Volatile

More information

Method of controlling access to intellectual switching nodes of telecommunication networks and systems

Method of controlling access to intellectual switching nodes of telecommunication networks and systems ISSN (e): 2250 3005 Volume 05 Issue 05 ay 2015 Intenational Jounal of Computational Engineeing eseach (IJCE) ethod of contolling access to intellectual switching nodes of telecommunication netwoks and

More information

RBAC Tutorial. Brad Spengler Open Source Security, Inc. Locaweb

RBAC Tutorial. Brad Spengler Open Source Security, Inc. Locaweb RBAC Tutoial Bad Spengle Open Souce Secuity, Inc. Locaweb - 2012 Oveview Why Access Contol? Goals Achitectue Implementation Lookup example Subject example Questions/Requests Why Access Contol? Access Contol

More information

NODAL AND LOOP ANALYSIS TECHNIQUES

NODAL AND LOOP ANALYSIS TECHNIQUES NODAL AND LOOP ANALYSIS TECHNIQUES LEANING GOALS NODAL ANALYSIS LOOP ANALYSIS Deelop systematic techniques to determine all the oltages and currents in a circuit NODE ANALYSIS One of the systematic ways

More information

Efficient Execution Path Exploration for Detecting Races in Concurrent Programs

Efficient Execution Path Exploration for Detecting Races in Concurrent Programs IAENG Intenational Jounal of Compute Science, 403, IJCS_40_3_02 Efficient Execution Path Exploation fo Detecting Races in Concuent Pogams Theodous E. Setiadi, Akihiko Ohsuga, and Mamou Maekaa Abstact Concuent

More information

A Novel Parallel Deadlock Detection Algorithm and Architecture

A Novel Parallel Deadlock Detection Algorithm and Architecture A Novel Paallel Deadlock Detection Aloithm and Achitectue Pun H. Shiu 2, Yudon Tan 2, Vincent J. Mooney III {ship, ydtan, mooney}@ece.atech.ed }@ece.atech.edu http://codesin codesin.ece.atech.eduedu,2

More information

CAM I/O Scheduler. Netflix, Inc. AsiaBSDCon 2015

CAM I/O Scheduler. Netflix, Inc. AsiaBSDCon 2015 CAM I/O Schedule ワーナーラーシュ フーメー Netflix, Inc. AsiaBSDCon 2015 東京 2015 年 4 月 15 日 http://people.feebsd.og/~imp/asiabsdcon2015/iosched-slides.pdf http://people.feebsd.og/~imp/asiabsdcon2015/pape.pdf Outline

More information

CPU Structure and Function

CPU Structure and Function Lecture 7 CPU Structure and Function Ch 12.1-4 [Sta06] Registers Instruction cycle Pipeline Dependences Dealing with Branches ALU General structure of CPU Calculations, comparisons Registers Fast work

More information

Assessment of Track Sequence Optimization based on Recorded Field Operations

Assessment of Track Sequence Optimization based on Recorded Field Operations Assessment of Tack Sequence Optimization based on Recoded Field Opeations Matin A. F. Jensen 1,2,*, Claus G. Søensen 1, Dionysis Bochtis 1 1 Aahus Univesity, Faculty of Science and Technology, Depatment

More information

A Full-mode FME VLSI Architecture Based on 8x8/4x4 Adaptive Hadamard Transform For QFHD H.264/AVC Encoder

A Full-mode FME VLSI Architecture Based on 8x8/4x4 Adaptive Hadamard Transform For QFHD H.264/AVC Encoder 20 IEEE/IFIP 9th Intenational Confeence on VLSI and System-on-Chip A Full-mode FME VLSI Achitectue Based on 8x8/ Adaptive Hadamad Tansfom Fo QFHD H264/AVC Encode Jialiang Liu, Xinhua Chen College of Infomation

More information

Modeling a shared medium access node with QoS distinction

Modeling a shared medium access node with QoS distinction Modeling a shaed medium access node with QoS distinction Matthias Gies, Jonas Geutet Compute Engineeing and Netwoks Laboatoy (TIK) Swiss Fedeal Institute of Technology Züich CH-8092 Züich, Switzeland email:

More information

IP Multicast Simulation in OPNET

IP Multicast Simulation in OPNET IP Multicast Simulation in OPNET Xin Wang, Chien-Ming Yu, Henning Schulzinne Paul A. Stipe Columbia Univesity Reutes Depatment of Compute Science 88 Pakway Dive South New Yok, New Yok Hauppuage, New Yok

More information

Hierarchically Clustered P2P Streaming System

Hierarchically Clustered P2P Streaming System Hieachically Clusteed P2P Steaming System Chao Liang, Yang Guo, and Yong Liu Polytechnic Univesity Thomson Lab Booklyn, NY 11201 Pinceton, NJ 08540 Abstact Pee-to-pee video steaming has been gaining populaity.

More information

Module 4c: Pipelining

Module 4c: Pipelining Module 4c: Pipelining R E F E R E N C E S : S T A L L I N G S, C O M P U T E R O R G A N I Z A T I O N A N D A R C H I T E C T U R E M O R R I S M A N O, C O M P U T E R O R G A N I Z A T I O N A N D A

More information

We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors

We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors We ae IntechOpen, the wold s leading publishe of Open Access books Built by scientists, fo scientists,800 6,000 0M Open access books available Intenational authos and editos Downloads Ou authos ae among

More information

(a, b) x y r. For this problem, is a point in the - coordinate plane and is a positive number.

(a, b) x y r. For this problem, is a point in the - coordinate plane and is a positive number. Illustative G-C Simila cicles Alignments to Content Standads: G-C.A. Task (a, b) x y Fo this poblem, is a point in the - coodinate plane and is a positive numbe. a. Using a tanslation and a dilation, show

More information

Prioritized Traffic Recovery over GMPLS Networks

Prioritized Traffic Recovery over GMPLS Networks Pioitized Taffic Recovey ove GMPLS Netwoks 2005 IEEE. Pesonal use of this mateial is pemitted. Pemission fom IEEE mu be obtained fo all othe uses in any cuent o futue media including epinting/epublishing

More information

i-pcgrid Workshop 2016 April 1 st 2016 San Francisco, CA

i-pcgrid Workshop 2016 April 1 st 2016 San Francisco, CA i-pcgrid Wokshop 2016 Apil 1 st 2016 San Fancisco, CA Liang Min* Eddy Banks, Bian Kelley, Met Kokali, Yining Qin, Steve Smith, Philip Top, and Caol Woodwad *min2@llnl.gov, 925-422-1187 LDRD 13-ERD-043

More information

Cold Drawn Tube. Problem:

Cold Drawn Tube. Problem: Cold Dawn Tube Poblem: An AISI 1 cold-dawn steel tube has an ID of 1.5 in and an OD of 1.75 in. What maximum extenal pessue can this tube take if the lagest pincipal nomal stess is not to exceed 8 pecent

More information

Title. Author(s)NOMURA, K.; MOROOKA, S. Issue Date Doc URL. Type. Note. File Information

Title. Author(s)NOMURA, K.; MOROOKA, S. Issue Date Doc URL. Type. Note. File Information Title CALCULATION FORMULA FOR A MAXIMUM BENDING MOMENT AND THE TRIANGULAR SLAB WITH CONSIDERING EFFECT OF SUPPO UNIFORM LOAD Autho(s)NOMURA, K.; MOROOKA, S. Issue Date 2013-09-11 Doc URL http://hdl.handle.net/2115/54220

More information

Environment Mapping. Overview

Environment Mapping. Overview Envionment Mapping 1 Oveview Intoduction Envionment map constuction sphee mapping Envionment mapping applications distant geomety eflections 2 1 Oveview Intoduction Envionment map constuction sphee mapping

More information

CPU Structure and Function

CPU Structure and Function CPU Structure and Function Chapter 12 Lesson 17 Slide 1/36 Processor Organization CPU must: Fetch instructions Interpret instructions Fetch data Process data Write data Lesson 17 Slide 2/36 CPU With Systems

More information

Computer Architecture: A Constructive Approach. Joel Emer Computer Science & Artificial Intelligence Lab. Massachusetts Institute of Technology

Computer Architecture: A Constructive Approach. Joel Emer Computer Science & Artificial Intelligence Lab. Massachusetts Institute of Technology Compute Achitectue: A Constuctive Appoach Bypassing Joel Eme Compute Science & Atificial Intelligence Lab. assachusetts Institute of Technology ach 19, 2012 L12-1 Six Stage Pipeline etch p c ecode eg ead

More information

EITF20: Computer Architecture Part2.2.1: Pipeline-1

EITF20: Computer Architecture Part2.2.1: Pipeline-1 EITF20: Computer Architecture Part2.2.1: Pipeline-1 Liang Liu liang.liu@eit.lth.se 1 Outline Reiteration Pipelining Harzards Structural hazards Data hazards Control hazards Implementation issues Multi-cycle

More information

Monitors. Lecture 6. A Typical Monitor State. wait(c) Signal and Continue. Signal and What Happens Next?

Monitors. Lecture 6. A Typical Monitor State. wait(c) Signal and Continue. Signal and What Happens Next? Monitos Lectue 6 Monitos Summay: Last time A combination of data abstaction and mutual exclusion Automatic mutex Pogammed conditional synchonisation Widely used in concuent pogamming languages and libaies

More information

Exploiting Superword Level Parallelism with Multimedia Instruction Sets

Exploiting Superword Level Parallelism with Multimedia Instruction Sets Exploiting Supewod Level Paallelism with Multimedia Instuction Sets Samuel Lasen and Saman Amaasinghe MIT Laboatoy fo Compute Science Cambidge, MA 0239 fslasen,samang@lcs.mit.edu Abstact Inceasing focus

More information

Lecture 3. Pipelining. Dr. Soner Onder CS 4431 Michigan Technological University 9/23/2009 1

Lecture 3. Pipelining. Dr. Soner Onder CS 4431 Michigan Technological University 9/23/2009 1 Lecture 3 Pipelining Dr. Soner Onder CS 4431 Michigan Technological University 9/23/2009 1 A "Typical" RISC ISA 32-bit fixed format instruction (3 formats) 32 32-bit GPR (R0 contains zero, DP take pair)

More information

DYNAMIC STORAGE ALLOCATION. Hanan Samet

DYNAMIC STORAGE ALLOCATION. Hanan Samet ds0 DYNAMIC STORAGE ALLOCATION Hanan Samet Compute Science Depatment and Cente fo Automation Reseach and Institute fo Advanced Compute Studies Univesity of Mayland College Pak, Mayland 074 e-mail: hjs@umiacs.umd.edu

More information

ANALYTIC PERFORMANCE MODELS FOR SINGLE CLASS AND MULTIPLE CLASS MULTITHREADED SOFTWARE SERVERS

ANALYTIC PERFORMANCE MODELS FOR SINGLE CLASS AND MULTIPLE CLASS MULTITHREADED SOFTWARE SERVERS ANALYTIC PERFORMANCE MODELS FOR SINGLE CLASS AND MULTIPLE CLASS MULTITHREADED SOFTWARE SERVERS Daniel A Menascé Mohamed N Bennani Dept of Compute Science Oacle, Inc Geoge Mason Univesity 1211 SW Fifth

More information