Transcript Rosetta Demostrator Project MASC, Adelaide University and

CS 351 Computer Architecture
Instructor:
Bala Ravikumar (Ravi)
116 I Darwin Hall
Office hours: TBA
Catalog Description:
Lecture, 4 hours. Instruction set design; stages of
instruction execution, data and control path design; CISC,
RISC, stack architectures; pipelining; program optimization
techniques, memory hierarchy: cache models and design
issues, virtual memory and secondary storage; I/O
interfacing; advanced topics to include some of the
following: parallel architectures, DSP or other special
purpose architecture, FPGA, reconfigurable architecture,
asynchronous circuit design.
Prerequisite: CS 215 and CS 252, or consent of instructor.
Course Goals:
Computer architecture deals with the functionality of all the
major components of a computer:
• instruction set architecture
• ALU
• control and data paths
• cache and main memory
• I/O
• network and bus interconnection
The main focus will be on the following topics:
• performance measures of computer systems
• MIPS assembly language
• computer arithmetic and ALU circuit design
• CPU design
• pipelining
• cache memory
• multicore CPU and parallel programming (as time permits).
Text:
Computer Organization and Design: The
hardware/software interface, 4th edition,
Morgan-Kaufman Publishers
ISBN: 978-0-123744937.
Other References:
• Parhami, Behrooz, Computer Architecture: From Microprocessors to
Supercomputers, Oxford University Press, 556 + xx pp., February 2005 (ISBN 019-515455-X).
• M. Murdocca and V. Heuring, Computer Architecture, Prentice-Hall.
• W. Stallings, Computer Organization and Architecture: Designing for
Performance, Prentice-Hall.
Assigned Work and Evaluation:
Quiz (10 - 15%) – There will be a quiz every class. Duration:
10 to 15 minutes.
Two Mid-Term tests (20 - 25%) – Both tests will be in class
and will be about 100 minutes long. Each test will have a
closed-book and an open-book section.
Home Work assignments (20 - 30%) – This will include some
implementation (in MIPS assembly language, hardware
description language etc.) as well as other design and
problem solving exercises.
Final Examination (35 - 40%) – The final examination will be
comprehensive and will have a closed- and an open-book
section.
Useful online sources
http://www.cs.wisc.edu/arch/www/
http://www.cs.utexas.edu/users/dburger/teaching/c
s382m-f03/homework/papers.html
History of computer architecture
Abacus is probably more than 3000 years old.
Still in use in many countries – in Asia, Africa and Middle-east.
(Some can use it to calculate faster than by a calculator.)
Used by visually impaired people.
Pascal’s work on calculating machines
Pascal began work on his calculator in 1642, when he was only 19 years
old. He had been assisting his father, who worked as a tax commissioner,
and sought to produce a device which could reduce some of his workload.
By 1652 Pascal had produced fifty prototypes and sold just over a dozen
machines, but the cost and complexity of the Pascaline – combined with
the fact that it could only add and subtract, and the latter with difficulty –
was a barrier to further sales, and production ceased in that year.
Babbage’s calculators
• Babbage built difference engine.
• had all features seen in modern
computers- means for:
• reading input data, storing data,
• performing calculations,
• producing output and
• automatically controlling the
operations of the machine.
•Babbage’s analytical engine is a
model of a general-purpose computer,
but it was too complex to be built in his
life time.
Turing’s work on computers
• The process of encryption used by Enigma (a German code)
was known for a longtime. But decoding was a much harder
task.
• Alan Turing, a British Mathematician, and others in England,
built an electromechanical machine to decode the message
sent by ENIGMA.
• The Colossus was a successful code breaking machine that
came out of Turing's research.
• Colossus had all the features of an electronic computer.
• Vacuum tubes to store the contents of a paper tape that
is fed into the machine.
• Computations took place among the vacuum tubes and
programming was performed with plug boards.
Shannon’s work on digital computers


Shannon showed in his Master’s thesis (at MIT)
how to use Boolean algebra to design circuits that
define any Boolean function.
Shannon also developed information theory that
formed the basis for error-correcting codes. This
concept became a central idea in networking and
storage devices.
Watch this youtube video clip on Shannon:
http://www.youtube.com/watch?v=z2Whj_nLx8&feature=PlayList&p=688DB457F0B24F42&playnext=1&playnext_from=PL&index=12
ENIAC

Built at U of Pennsylvania around 1940.




ENIAC consisted of 18000 vacuum tubes, which
made up the computing section of the machines
programming and data entry were performed by
setting switches.
There was no concept of stored program.
But these were not serious limitations since ENIAC
was intended to do special-purpose calculations.
ENIAC was not ready until the war was over, but it
was successfully used for nine years after the war
(1946-1955).
Chapter 1
Computer Abstractions and Technology

Progress in computer technology
Underpinned by Moore’s Law
“Every two years, the number of transistors in IC doubles.”


Makes novel applications feasible






Computers in automobiles – pollution control, ABS,
airbags etc.
Cell phones
Human genome project
World Wide Web – ~1 billion web sites, ~10 billion web
pages.
Search Engines
Computers are pervasive
§1.1 Introduction
The Computer Revolution
Moore’s law
Classes of Computers

Desktop computers



Server computers




General purpose, variety of software
Subject to cost/performance tradeoff
Network based
High capacity, performance, reliability
Range from small servers to building sized
Embedded computers


Hidden as components of systems
Stringent power/performance/cost constraints
The Processor Market
What You Will Learn

How programs are translated into the
machine language



The hardware/software interface
What determines program performance



And how the hardware executes them
And how it can be improved
How hardware designers improve
performance
What is parallel processing
Understanding Performance

Algorithm


Programming language, compiler, architecture


Determine number of machine instructions executed
per operation
Processor and memory system


Determines number of operations executed
Determine how fast instructions are executed
I/O system

Determines how fast I/O operations are executed

Application software


Written in high-level language
System software


Compiler: translates HLL code to
machine code
Operating System: service code




Handling input/output
Managing memory and storage
Scheduling tasks & sharing resources
Hardware

Processor, memory, I/O controllers
§1.2 Below Your Program
Below Your Program
Levels of Program Code

High-level language



Assembly language


Level of abstraction closer to
problem domain
Provides for productivity and
portability
Textual representation of
instructions
Hardware representation


Binary digits (bits)
Encoded instructions and data
The BIG Picture

Same components for
all kinds of computer


Desktop, server,
embedded
Input/output includes

User-interface devices


Storage devices


Display, keyboard, mouse
Hard disk, CD/DVD, flash
Network adapters

For communicating with
other computers
§1.3 Under the Covers
Components of a Computer