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Ten Pounds in a Five-Pound Sack Zac Lippard. Program Space as Cost  How big is it?  Space occupied is a principle cost!  Is it worth paying the price.

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Presentation on theme: "Ten Pounds in a Five-Pound Sack Zac Lippard. Program Space as Cost  How big is it?  Space occupied is a principle cost!  Is it worth paying the price."— Presentation transcript:

1 Ten Pounds in a Five-Pound Sack Zac Lippard

2 Program Space as Cost  How big is it?  Space occupied is a principle cost!  Is it worth paying the price for space, or is it better to use the money elsewhere?  Eliminate unnecessary size expenditures by setting size targets, control sizes, and devise size-reduction techniques.

3 Size Control  Size control is partly technical, partly managerial.  Separate the system into subsystem components and set control sizes for each.  The wise program manager prepares a kitty for later allocation.

4 OS/360  Setting size targets for core is not enough.  Relied on cheap disk access and therefore slowed down performance.  Even though core targets were met by the programmers, execution was incredible slow.

5 Whats the Lesson?  Set total size budgets as well as resident- size budgets so as to not run over the amount of space you have available.  Define specifically what a module must do when you set the size for it.  Most important lesson: Foster a total- system, user-oriented attitude!  Don’t go over the top!

6 Small Programs  No space budgeting or controlling can do this.  It takes invention and craftsmanship.  Trade functions for size.  It’s cheaper to by the package then everything individually.  Must decide how fine-grained the program is to be.

7 Space-Time Trade-Offs  More space, the faster the software.  Managers can do two things to ensure this happens:  Make sure the programmers are trained well.  Use programming technology to functional preference  Two sets of functions: the quick and the squeezed.

8 Invention  Strategic breakthroughs in programming.  Find code that creates a faster program.  Cooley-Tukey Fast Fourier Transform  Reduced computation time by using n 2 instead of n log n  Representation of data and tables can help in further breakthroughs.

9 The End


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