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Distributed Computing Systems. Hugh C. Lauer Adjunct Professor (Slides include materials from Operating System Concepts , 7 th ed., by Silbershatz, Galvin, & Gagne and from Modern Operating Systems , 2 nd ed., by Tanenbaum). Outline for Today. Introduction to CS-4513

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distributed computing systems

Distributed Computing Systems

Hugh C. LauerAdjunct Professor

(Slides include materials from Operating System Concepts, 7th ed., by Silbershatz, Galvin, & Gagne and from Modern Operating Systems, 2nd ed., by Tanenbaum)

Introduction

outline for today
Outline for Today
  • Introduction to CS-4513
  • What is “Distributed Computing”
    • An example of a distributed computation
  • Networks
  • Assignment of Project #1

Introduction

introduction to cs 4513
Introduction to CS-4513
  • Continues CS-3013, Operating Systems
    • File Systems
      • One lecture in C-Term CS-3013
      • No coverage in A-Term CS-3013
  • Networks & Communication
  • Computations that run on more than one machine
      • Close together
      • Far apart
  • Internet and World Wide Web

Introduction

textbook and web
Textbook and Web
  • Textbooks:– You should own or have access to one of the following from CS-3013
    • Operating Systems Concepts, 7th ed, by Silberschatz, Galvin, and Gagne, John Wiley and Sons, 2005
    • Modern Operating Systems, 2nd edition, by Andrew S. Tanenbaum, Prentice Hall, 2001
  • Supplemental Text:–
    • Distributed Systems: Principles and Paradigms, Tanenbaum and Van Steen, Prentice-Hall, 2007
  • Course Information:
    • http://www.cs.wpi.edu/~cs4513/d07/

Introduction

prerequisites
Prerequisites
  • Prerequisites:
    • CS-3013, Operating Systems or equivalent
    • C and C++ programming, esp. low level programming
    • Data structures
    • Unix/Linux user experience and access
    • Computer Organization
  • 1st reading assignment: any of the following
    • Silbershatz, §16.1-16.4
    • Tanenbaum, §8.3
    • Tanenbaum & Van Steen, Chapter 1

Introduction

schedule logistics
Schedule

Goddard Hall 227

9:00 – 10:50 AM

Tuesdays and Fridays thru May 1

No class on April 17

14 classes total

Exams

Mid-term on April 3

Final on May 1

Unannounced Quizzes

May occur at any time

May be at beginning, middle, or end of class

Mobile Phones, pagers, laptops, and other devices OFF during class

~4 Programming Projects

Fossil Lab

Office Hours

Adjunct Office, Fuller 239

by appointment, or

Normally ½ hour before and after class

Teaching Assistant

Choong-Soo Leeclee01 **at** cs.wpi.edu

Contact

<Professor’s last name> @ cs.wpi.edu

Adjunct office phone:(508) 831-6470 (shared, no messages)

Schedule & Logistics

Introduction

grading
Grading
  • Grading
    • Exams – 35%
    • Programming Projects (~4) – 35%
    • Class participation, homework, & quizzes – 30%
  • Unless otherwise noted, assignments are to be completed individually, not groups
  • Late Policy – 10%/day
    • But contact Professor for extenuating circumstances
  • WPI Academic Honesty policy

Introduction

miscellaneous
Miscellaneous
  • Is this course the capstone for a Minor in CS?
  • Anyone needing a project for BS & MS credit?

Introduction

ground rule
Ground Rule
  • There are no “stupid” questions.
  • It is a waste of your time and the class’s time to proceed when you don’t understand the basic terms.
  • If you don’t understand it, someone else probably doesn’t, either.

Introduction

introductions
Introductions
  • Who are you?
    • Name, year, degree, major
    • Work experience in computing, etc.?
  • C & C++ experience
    • Other programming experience
  • Why CS-4513 – Distributed Computing Systems?
  • Anything else relevant?

Introduction

instructor hugh c lauer adjunct professor
Instructor — Hugh C. LauerAdjunct Professor
  • Ph. D. Carnegie-Mellon 1972-73
    • Dissertation “Correctness in Operating Systems”
  • Lecturer: University of Newcastle upon Tyne, UK
  • 30+ years in research and development in industry in USA
  • Research and system topics
    • Operating Systems
    • Proofs of Correctness
    • Computer Architecture
    • Networks and Distributed Computing
    • Real-time networking
    • 3D Volume Rendering
    • Surgical Simulation and Navigation

Introduction

systems experience
Systems Experience
  • University of Newcastle
  • Systems Development Corporation
  • Xerox Corporation (Palo Alto)
  • Software Arts, Inc.
  • Apollo Computer
  • Eastman Kodak Company
  • Mitsubishi Electric Research Labs (MERL)
  • Real-Time Visualization
      • Founded and spun out from MERL
      • Acquired by TeraRecon, Inc.
  • SensAble Technologies, Inc.
  • Currently: CTO, Dimensions Imaging, Inc.

Introduction

accomplishments
Accomplishments
  • 21 US Patents
  • Two seminal contributions to CS
    • Duality Hypothesis of Operating System Structures (with Roger Needham)
    • First realization of opaque types in type-safe programming languages (with Ed Satterthwaite)
  • VolumePro™
    • World’s first 2D, 3D, and 4D volume rendering system at interactive speeds for medical, seismic, and scientific visualization

Introduction

volumepro
VolumePro™
  • Interactive volume rendering of 3D data such as
      • MRI scans
      • CT scans
      • Seismic scans
  • Two generations of ASICs, boards, software
      • VolumePro 500 – 1999
      • VolumePro 1000 – 2001
  • CTO, Chief Architect of VolumePro 1000
      • 7.5-million gate, high-performance ASIC
      • 109 Phong-illuminated samples per second

Introduction

class discussion

Class Discussion

What is Distributed Computing?

Introduction

distributed system
Distributed System
  • Collection of computers that are connected together and (sometimes) interact
  • Many independent problems at same time
      • Similar
      • Different
  • Or …
    • One very big problem (or a small number)
  • Computations that are physically separated
      • Client-server
      • Inherently dispersed computations

Introduction

distributed computing spectrum
Distributed Computing Spectrum
  • Many independent problems at same time
      • Similar — e.g., banking & credit card; airline reservations
      • Different — e.g., university computer center; your own PC
  • Or …
    • One very big problem (or a few)
  • Computations that are physically separated
      • Client-server
      • Inherently dispersed computations

Introduction

multiprocessing distributed computing a spectrum
Multiprocessing  Distributed Computing(a spectrum)
  • Many independent problems at same time
      • Similar — e.g., banking & credit card; airline reservations
      • Different — e.g., university computer center; your own PC
  • Or …
    • One very big problem (too big for one computer)
      • Weather modeling, finite element analysis; drug discovery; gene modeling; weapons simulation; etc.
  • Computations that are physically separated
      • Client-server
      • Inherently dispersed computations

Introduction

multiprocessing distributed computing a spectrum20
Multiprocessing  Distributed Computing(a spectrum)
  • Many independent problems at same time
      • Similar — e.g., banking & credit card; airline reservations
      • Different — e.g., university computer center; your own PC
  • Or…
    • One very big problem (too big for one computer)
      • Weather modeling, Finite element analysis; Drug discovery; Gene modeling; Weapons simulation; etc.
  • Computations that are physically separated
      • Client-server
      • Dispersed – routing tables for internet; electric power distribution.

Introduction

observation
Observation
  • Same spectrum applies to multiprocessor systems
    • Much more tightly coupled that traditional “distributed systems”
  • Some differences
    • “Multiprocessor systems”
      • Usually under same management
      • Very fast communication
    • “Distributed systems”
      • Sometimes not under same management
      • Slower communication

Introduction

another observation attributed to r hamming
Another Observation(attributed to R. Hamming)
  • When you change the operating point of a system by an order of magnitude …

… you introduce qualitative changes in how to approach problems

Introduction

let s look at an example
Let’s look at an example
  • An inherently distributed computation
    • I.e., parts of the computation must occur at physically separate locations
    • Under separate administrations
  • Internet routing tables

Introduction

the internet
The Internet
  • A vast collection of independent computers
    • ~ 600  106
  • All connected together
  • Any computer can send a message to any other
  • Messages broken up into little packets
  • Question: how do packets find their way to destinations?

Introduction

internet
Internet

Introduction

distributed routing algorithm simplified example
Distributed routing algorithm(simplified example)
  • Each node “knows” which networks are directly connected to it.
  • Each node maintains table of distant networks
      • [network #, 1st hop, distance]
  • Adjacent nodes periodically exchange tables
  • Update algorithm (for each network in table)
      • If (my distance to network>neighbor’s distance to network + my distance to neighbor), then …
      • … update my table entry for that network so that neighbor is first hop.

Introduction

distributed routing algorithm result
Distributed routing algorithm(result)
  • All nodes in Internet maintain reasonably up-to-date routing tables
  • Rapid responses to changes in network topology, congestion, failures, etc.
  • Very reliable with no central management!

Introduction

characteristic
Characteristic
  • The routing algorithm is inherently distributed
  • Different parts execute in physically separated locations
  • Only nearby nodes “know” whether
    • Neighbors are up or down
    • Networks are congested or not

Introduction

big networks
Big networks
  • Network management systems
      • Monitoring health of network (e.g., routing tables)
      • Identifying actual or incipient problems
      • Data and statistics for planning purposes

Introduction

questions

Questions?

Next TopicProgramming Project

Introduction