Advanced Computer Architecture - Lecture 3: Quantitative principles (Cont’d)

Advanced Computer Architecture - Lecture 3: Quantitative principles (Cont’d). This lecture will cover the following: design for performance; I/O performance; laws and principles; performance enhancement; concluding: quantitative principles;...

CS 704 Advanced Computer Architecture

Lecture 3

Design for Performance

Prof Dr M Ashraf Chughtai

Today’s Topics

Recap

I/O performance

Laws and Principles

Performance enhancement

Concluding: quantitative principles

Home work

Summary

Recap: Lecture 1-2

Computer architecture verses

organization

Technological Developments

Computer design cycle

throughput

Price-Performance design

Computer I/O System

Producer-Server model

– Producer: the device that generates request to be serviced

– Queue : the area where the tasks accumulate waiting to be serviced

– Server: the device performing the requested service

– Response Time: the time a task takes from the moment it is placed in the buffer to the time server finishes the task

Server

I/O device/

controller

Producer Queue

Arrivals departures

I/O Performance Parameters

Diversity: Which I/O device can

connect to the CPU

Capacity: How many I/O devices can connect to the CPU

Latency : Overall Overall response time to

complete a task

Bandwidth: Number of task completed

in specified time - throughput

I/O Transaction Time

The interaction time or transaction time of

a computer is sum of three times:

– Entry Time: the time for user to enter a

command – average 0 25 sec; from keyboard 4.0 sec.

– System Response Time : time between

when user enters the command and system

responds

– Think Time: the time from reception of the

command until the user enters the next

command

Throughput verses Response time: Performance Measures Cont’d

| | | | | | 0% 20% 40% 60% 80% 100%

200 _

150 _

100 _

50 _

20 0















% of maximum throughput - bandwidth

Response time and throughput calculation

Arrivals Departures

If the system is in steady state, then the

number of tasks entering the system must be

equal to the number of tasks leaving the system

Little’s Law:

Mean number of tasks in system =

Mean response time x Arrival rate

Little’s Law – A Little queuing theory

Mean number of tasks in the system =

(Time accumulated ) / (Time observe ) Mean response time =

(Time accumulated ) / (Number tasks ) Arrival rate λ =

(Number tasks ) / (Time observe )

The expression for mean number of task may be written as:

Time accumulated Time accumulated x Number tasks

= Time observe Number tasks Time observe

Amdahl's Law

Suppose that enhancement E accelerates a fraction F of the task by a factor S, and the remainder of the task is unaffected

Original

Execution time of the Fraction Enhanced Time for Fraction F to be

Enhanced by factor S

Amdahl's Law

Speedup due to enhancement E:

Ex Time with E

Performance with E

Performance without E

Amdahl’s Law

Amdahl’s Law

=

1

Amdahl’s Law

Floating point instructions improved to run 2X; but only 10% of actual

instructions are FP

Amdahl’s Law

Floating point instructions improved to run 2X; but only 10% of actual

instructions are FP

Amdahl’s Law

=

1

Amdahl’s Law

Solution