hints for computer design

HINTS FOR COMPUTER DESIGN

Travis McVey, Diego Velasquez, Mark Whylie, Drem Darios, Elroy

Ashtian Jr.

HINTS FOR COMPUTER SYSTEM DESIGN

Members of the group Part of the paper

Diego Velasquez Introduction

Drem Darios Functionality (From 2.1 to 2.3)

Elroy Ashtian Jr Functionality (From 2.4 to 2.5)

Travis McVey Speed

Mark Whylie Fault Tolerance

Diego Velasquez Conclusion

Outline:

Section 1 IntroductionBy: Diego Velasquez

Introduction Abstract:

Paper based in the experienced of Butler W. Lampson.

General hints for computer system design illustrated using examples.

Introduction Points explain in the paper:

Designing a computer system is different from designing an algorithm.

There is no a best way to build a system. They are just hints The hints are illustrated by a number of

examples. They range from: hardware, operating systems, programming systems, and applications programs.

Introduction Each hint is summarized by a slogan. The following table organizes the slogans in two axes:

Why? where?

FunctionalityDoes it work?

SpeedIs it fast enough?

Fault-toleranceDoes it keep working?

CompletenessSeparate normal and worst case

Safety first Shed load End-to end End-to-end

Interface Do one thing well:Don’t GeneralizeDon’t hide powerUse procedure arguments Leave it to the clientKeep basic interfaces stableKeep a place to stand

Make it fastSplit ResourcesStatic AnalysisDynamic translation

End-to-endLog UpdatesMake action atomic

Implementation Plan to throw one away Keep SecretsUse a good idea againDivide and conquer

Cache answersUse hintsUse brute forceCompute in backgroundBatch processing

Make action atomicUse hint

Section 2 Functionality – Section 2.3

By: Drem Darios

FUNCTIONALITYThe most vague but most important hint is to obtain the right functionality for a system.

Interface design must satisfy three things:• It should be simple• It should be complete, meaning normal and worst

cases are considered• It should admin a sufficiently small and fast

implementation

Car ExampleDriving

OperateCar

BrakePedal

BrakeController

BrakeLine Brakes

Accelerator ThrottleController Fuel Engine

SteeringWheel Steering system Steering

ColumnWheelAngle

User Program

Interface

Devices

Software

HardwareAbstract Interface

Device Interface Modules

Hardware Interface

Keep it simple

Do one thing and do it well• When an interface undertakes too much it results in a large, slow, and

complicated implementation• Some interfaces are ok to sacrifice performance for functionality

Get it right!• Do not generalize; generalization is generally wrong• The Tenex System Example

The problem with this design is that is made it possible to gain access by guessing a password of length n in 64n tries (on average) rather than 128n/2

CorollariesMake it fast rather than powerful

If it’s fast the client can program the function it wants and another client program some other function Just as before, simpler is better. It is better to be simple and fast than powerful and slow

Don’t hide power The purpose of abstraction is to conceal the undesired properties but desired ones shouldn’t be

hidden. If a low level of abstraction allows something to be done quickly , it shouldn’t be hidden by higher

levels

Use procedure arguments to provide flexibility in an interface A good example of this is an enumeration procedure that returns a result set based on a certain

property. The best interface would allow the client to pass their own filter to the enumeration procedure rather than fighting with built in mechanism.

Leave it to the client If it is cheap to pass control of an interface back and forth, the interface should just quickly solve one

problem and leave the rest to the client.

Section 2.3 Continuity – Section 3

By: Elroy Ashtian, Jr.

ContinuityKeep basic interfaces stable. Software Interfaces Type-checking & Non type-checking

programming language Ex. Type-checking language – Mesa

ContinuityKeep a place to stand Compatibility package

Tenex

World-swap debugger Useful in bootstrapping

ex. BIOS to OS

Making implementations work

Plan to throw one away Testing & Prototyping

Keep secrets of the implementation Secrets Assumptions between the parts

• Downside to Fewer Assumptions

Making implementations work

Divide and conquer• Solving a complex problem

• ex. Alto's Scavenger Program & Dover raster printer

Use a good idea again, instead of generalizing it.

• An Idea– ex. replication of data

• Small amount of data• Large amounts of data

Handling all the casesHandle normal and worse cases as a

rule Error Handling Interlisp-D & Cedar programming

systems Reference-counting garbage collector Cedar’s additional functions

Handling all the cases • Rare Problem with referencing-counting

– Overflow – Solution: An overflow count table

• Paging system– Worst case scenario: all dirty pages

Bravo editor Piece Table Editing Cleanup process

Section 3 SpeedBy: Travis McVey

Splitting Resources It is usually Faster to allocate dedicated

resources, but this increases cost Examples

Use Static Analysis A program can read data much faster

when the data is read sequentially When in sequential order the data

becomes predictable However, it is very difficult for a

programmer to go over the code and optimize the disk transfers

This leads to Dynamic Analysis by demand paging which is at least as good

Dynamic Translation Make translation easy – so it can be quickly

interpreted is a nice change from bit to bit translation

Another idea of this scheme is to translate on demand and cache the result

Cache Short definition: Storing information that

takes a long time to compute. Cache MUST:

Be true – invalidate the value and/or update the value

Not “Thrash”

Cache Examples Hardware: Bad Examples: Software: Bravo Editor

Hint Like a cache entry is the saved result of

some computation and is used to make the system faster

How is it different? How is it effective?

Examples of a Hint In Alto and Pilot Operating Systems Arpanet Operating System Smalltalk Program

Brute Force Do not forget Brute Force is always an

option – and easier as the cost of Hardware comes down

Example in Chess: Special-purpose Hardware by Belle beats sophisticated algorithms

Compute in the Background

When it is possible, computing in the background

Examples: Electronic Mail Garbage Collectors Banks Paging Systems

Batch Processing Doing things incrementally Disks and tapes work better when

accessed Sequentially Errors Recovery is much simpler Example: Bank of America

Safety First When “Allocating Resources” it is more

important to prevent disaster than to optimize

General Purpose systems cannot be optimized

Sad Truth Leads to Shedding the load

Shed Load Do not let the System become

overloaded – must take control Bob Morris’s and the “Red Button” Arpanet Operating System Example

Section 4 Fault ToleranceBy: Mark Whylie

Fault Tolerance Making a system reliable is not really

hard, if you know how to go about it. The issue arises when you attempt to add reliability to a existing design.

Fault Tolerance End-to-end error recovery is absolutely

necessary for a reliable system, and any other error detection or recovery is not logically necessary, but is strictly for performance.

Example: Consider the operation of transferring a file from a disk using the NTFS file system on machine A to a disk consisting of the ext3 file system on machine B.

What would be the logical thing to do to test that the file actually did transfer successfully with all bits still in the correct order?

Answer: Obviously you would just open the file from machines B's disk, compute a checksum on machine B, and compute the same checksum on machines A's disk for the same file and if they are equal we can assume that the transaction was successful.

Here we have an end to end check.

HOWEVER!!! However, if we decide to implement more intermediate

checks after looking at the end to end technique we notice that these intermediate steps are not sufficient at all.

For instance, we could have transferred the file from A's disk to A's memory, then from A's memory over a network to B's memory then move the file from B's memory to its disk.

But the pitfall with this is that if we transfer this file over the network without checking for packet loss, we could have random bits missing from the file when it arrives at its destination on B’s disk.

So obviously all this extra headache can be avoided in this example by just comparing the checksums at the source and destination to see if they match. However, let me point out that performing these intermediate checks would be for performance gains.

Fault Tolerance Another Great example of end to end for reliable

systems is the pup Internet. In this network a data packet is transferred from a

source to a destination. These packets may traverse various networks at different rates where each individual networks may implement different intermediate strategies to catch errors before proceeding.

For instance, some networks may only be used to temporarily store and forward packets.

But a pitfall here may be that there are so many packets coming through a particular node that a forwarder queue becomes clobbered and when this occurs it is forced to drop packets.

Fault Tolerance In instances like these intermediate steps becomes unreliable as in

this case the sender of the packet has no way to know if the packet reached its destination or not as these intermediate checks are local to each individual network that the packet is traversing.

However, to face these uncertainties the pup internet provides good services with an implementation by attempting only "best efforts" delivery.

In this case, clients provide there own error control to deal with problems. However, the packet transport does attempt to report problems to its clients, by providing a modest amount of error control (a 16-bit checksum), notifying senders of discarded packets when possible, etc.

These services are intended to improve performance in the face of unreliable communication and overloading; since they too are best efforts, they don't complicate the implementation much.

Fault Tolerance However, there are two pitfalls with the

end-to-end strategy: 1) it requires a cheap test for success. 2) It can lead to working systems with sever

performance defects, which may not be obvious until a operation is placed on heavy load.

Fault Tolerance We use log updates to record the truth about the state

of an object. A log is a very simple data structure which can be

reliably written and read, and cheaply forced out on disk or other storage that can survive a crash i.e. some portable media. These files are append only so it ensure that a log is valid

whenever a crash occurs To use a log, record every update as a log entry, consisting of

the name of the update procedure and its arguments. This allows the same statement from the log to be executed later i.e. after a crash. Keeping the log in this order allows a sequence of log entries to be re-executed, starting with an object in its original state, and produce the same object that was produced in its original execution.

Logs The update procedure must be a true

function: Its result does not depend on any state outside

its arguments; It has no side effects, except on the object

in whose log it appears. The arguments must be values, one of:

Immediate values, such as integers, strings etc. An immediate value can be a large thing, like an array or even a list, but the entire value must be copied into the log entry.

Fault Tolerance However, most objects are not immutable

since they are updated. Each update to a object changes its version.

However in the case of a log a simple way to refer a particular version of an object is to identify the object in the log and all the updates done to it.

When we replay the log file and begin with the original object we can choose from the number of updates queue to identify what version of the object we want to access.

Fault Tolerance Make actions atomic or restartable. An

atomic action is one which completes or has no effect. In most storage systems fetch and store operations are atomic so either it completely retrieves some arbitrary word or it doesn't. This eliminates the need for intermediate steps when attempting to recover from any errors.

Section 5 ConclusionBy: Diego Velasquez

“Most humbly do I take my leave, my lord”

Conclusion

Why? where?

FunctionalityDoes it work?

SpeedIs it fast enough?

Fault-toleranceDoes it keep working?

CompletenessSeparate normal and worst case

Safety first Shed load End-to end End-to-end

Interface Do one thing well:Don’t GeneralizeDon’t hide powerUse procedure arguments Leave it to the clientKeep basic interfaces stableKeep a place to stand

Make it fastSplit ResourcesStatic AnalysisDynamic translation

End-to-endLog UpdatesMake action atomic

Implementation Plan to throw one away Keep SecretsUse a good idea againDivide and conquer

Cache answersUse hintsUse brute forceCompute in backgroundBatch processing

Make action atomicUse hint

The slogans in the paper are collected in the table below.