Edward Chang Electrical Computer Engineering

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ECE154

Computer Architecture

Lecture #1

Edward Chang

Electrical & Computer Engineering

ECE154 Team

l Instructor: Edward Chang

l TAs

– Chao, Chia-Tso – Gadepalli, S.

l Office Hours and Contact Information

– Check class Web site frequently

– http://www.mmdb.ece.ucsb.edu/~ece154/

l

Class Email Address

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Textbook and Prerequisite

l “Computer Architectures: A Quantitative

Approach’’, 3rd _{edition, J. Hennessy and D.}

Patterson

l Prerequisite

– Basic digital logic

– Assembly programming – Simple OS concepts

Assignments and Exams

l 6 Homework Assignments l Midterm on 2/10

l Final on 3/12 l Grading

– HW: 20%; Midterms: 30%; Final: 50%

l Policies

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Discussion Session Signup

l Four Sessions (Friday)

– 8 – 9am 387 104 – 12 – 1pm SNDCR 1637 – 1 – 2pm 387 103 – 2 – 3pm PHELP 1445

Course Outline

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Today

’

s Outline

l Class Goals

l What is Computer Architecture

– Design process, constraints, tools

l Performance

– Execution Time vs. Throughput – CPU time equation

– Amdhal’s law

l Basic Design Principles l Chip Cost

Class Goals

l Understand how computer systems are organized and

why they are organized that way

l Be conversant with techniques for analyzing performance

and comparing systems

l Introduction to computer implementation techniques l Will discuss advanced topics

– Instruction-set architecture

– Hardware and software techniques for instruction-level parallelism

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Components of a General

-

Purpose

Computer System

l Programmable Processor

– CPU, DSP, microprocessor

l Memory

– For program and data – Cache, DRAM, MEMS

l Storage

l Buses and Controllers

– Connecting CPU, memory, storage

– Connecting networks

Computer Architecture?

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History of Computer Systems

l 1960s – 1970s

– Mainframes and minicomputers

l Late 1970

– Emergence of microprocessor

l Late 1980

– C and compilers – Unix

– RISC

Relative Performance

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The Contribution of Architectural

Innovation

l 2001 Statistics

– Base circuit design performance: X – Architectural innovation: 15 X

l ECE154 is about

– Innovative architecture ideas

– Measured by a quantitative approach

Computer Categories

l Desktops

– Examples: PCs, workstations – Metrics: latency (graphics & IO)

l Servers

– Examples: Web, database servers

– Metrics: throughput, reliability, scalability

l Embedded Systems

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Technology Trends

(Yearly Improvement)

l Integrated Circuit: logic

– 35% increase in density, 55% a chip – 15% speedup

l Integrated Circuit: memory

– 60% increase in density – 7% reduction in latency – 14% increase in throughput

l Magnetic Disks

– 100% increase in density

– Access time improvement 33% in ten years

l Networking

– Little improvement in latency – Large improvement in bandwidth

Technology Trends

(Yearly Improvement)

l Feature Size (f)

– Shrinks from 10 microns (1971) to 0.18 (2001)

l Device Size

– Shrinks quadratically with decrease in feature size

l Transistor Count

– Improves quadratically w.r.t. 1/f

l Transistor Performance

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Performance Bottlenecks

l Wires

– No improvement

– Pentium IV allocates 2 out of 20-stage pipeline for wire delay

l Power

– Switching frequency * load capacitance * voltage2 – The 1st_{microprocessor consumes 1/10 watt} – 2GHz Pentium-4 consumes 100 watts

Changing Technology Changes

Architecture

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Cost, Price, and Trends

l Factors Affect Cost

– Yield – Competition

l Price

– Memory: Price = cost – CPU: Price = (1+k%) cost

l Computer Price

– Dominated by processor, – Monitor

Relative Performance

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Measuring Performance

l X performs N time better than Y

– X runs N-times faster than Y

– X takes 1/N time, compared to Y, to complete the task – X takes 1/N+1 time, compared to Y, to complete the task – X responds N-times faster than Y

l Improve a system performance by N folds

– Decrease its running time by N folds – Increase its throughput by N folds

l CAQA’s position

– Use Execution Time_{to measure performance}

Execution Time

l Elapsed Time l Response Time l CPU Time

– User CPU time and system CPU time – The choice of CAQA to measure processor

performance (throughout Chapter 4)

l Many Benchmarks

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Benchmark Examples

Performance Summary

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Execution Time

40 110

1001 Total Time

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Computer C

Computer B

Computer A

Arithmetic Means

l B is 9.1 faster than A for P1 + P2 l C is 25 times faster than A for P1 + P2 l C is 2.75 times faster than B for P1 + P2

l Arithmetic mean is fine

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Weighted Execution Time

l Weighted Arithmetic Mean

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Weighted Arithmetic Means

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Geometric Means

l The Weighted Arithmetic Mean differs

depending on which machine is the reference one.

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Geometric Mean

1.0

Normalized to C Normalized to B

Normalized to A

Summary of Means

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Design Principles

l

Make the Common Case Fast

l

Principle of Locality

l

Parallelism

Make the Common Case Fast

l

Amdahl’s Law

– The performance gain is limited by the fraction of time the faster mode can be used

l

Example

– Meal time = Order time + Eating time – 40 mins = 20 mins + 20 mins

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Make the Common Case Fast

Examples

l

IO time is 60% of the execution time, and

CPU time 40%

l

Speeding up CPU 10 times achieves

overall speedup of

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CPU Performance Equation

Computer Architecture?

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Summary

l

Computer Architecture

– Design to last through trends

l

Performance Metrics

– Amdahl's law – CUP time formula

l

Design Principles

– Make the common case fast – Locality

– Parallelism

References

l