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Performance Code Complete 2 – Chapters

25/26 and Chapter 7 of K&P Compare today to 44 years

ago– The Burroughs B1700 – circa

1974 Why do we care about

performance today? First principle of

optimization:– DON’T

Second principle of optimization:– DON’T

Third principle of optimization– DON’T

B1700 Today

Proc Spd 6Mhz 3.8Ghz (dual)

Memory 64KB 2GB

Disk 2.3MB hd per track

1TB

Input Cards Keyboard/Monitor

Lang SDL C++

Cost ?50K 1K

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Optimization

Easiest technique is to turn on the compiler’s optimizer

In VS.NET do a release build vs. debug build Makes debugging harder Hopefully doesn’t introduce new bugs

– But could if there are non-deterministic parts of the program already

– Also, debug mode is known to initialize locations for easy debugging but your code may count on that initialization

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Optimization - 2

Measurement is the critical component before deciding that you should worry about performance improvement

Make sure that you have good regression tests– Eliminates issue of optimizing something so it is so fast that you

forgot to preserve the semantics and it doesn’t work any more

Often algorithm analysis is the most fruitful place to start

How much faster is binary search than linear search on a one million element array?

See you in CS 4150!

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Targets of Improvement

Program design: how a program is divided into classes may make it hard or easy to improve performance

Class & method design: choice of data types, algorithms

Operating system interactions Code compilation: the right compiler may be all you

need Hardware: why not a hardware upgrade? Code tuning: small scale changes to correct code

with hopes of running faster (or smaller)

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Timing Easiest is to use time mechanism provided by system

– 5 faith> time clean.csh

– 0.0u 2.0s 0:08 24% 0+0k 0+0io 0pf+0w

– 6 faith>

How about on Windows?– C:\Documents and Settings\kessler>time

– The current time is: 10:06:08.06

– Enter the new time:

– C:\Documents and Settings\kessler>

So, what should you do on systems like Windows to get a coarse view of time?– #include <time.h>

– double begin = clock();

– …

– double result = clock() – begin; // time in ms

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The Pareto Principle

(20% of Italians have 80% of the wealth)

You can get 80% of the result with 20% of the effort. 20% of a program consumes 80% of its execution

time (Boehm) Less than 4% of a program accounts for more than

50% of the run time (Knuth) Measure your code for hot spots, and then put

resources into optimizing the small portion(s) of the program used most

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Profiling

What is a profile?– A measure of where a program spends its time

Provides more detailed timing information about a program– Number of times a function is called– Percentage of execution time spent in a function– Some provide the information in a line by line fashion

Profiling is effective for finding hot spots in a program

How does a profiler work?

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Misconceptions

Reducing the lines of code in a high-level language improves the speed or size of the resulting machine code

Certain operations are probably faster or smaller than others

You should optimize as you go A fast program is as important as a correct one A fast program is as important as a readable one

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Strategies After deciding that you HAVE to optimize:

– Measure– Track down slow parts– Remember important principle – if you improve one part so it

takes no time, your program will only get x% faster if the part you are optimizing is taking x% of the time

Use a better algorithm or data structure– Try to determine complexity

Enable compiler optimizations– Measure before and after to make sure it is worth it

Tune the code– Adjust the loops and expressions to be faster

Don’t optimize what doesn’t matter– Rule of thumb – your time vs. how much time you’ll save over the

lifetime of the program

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Tuning The Code Collect common subexpressions

– Is probably not worth it these days Reduction in strength of operations

– Again is probably not worth it these days Unroll or eliminate loops

– Short loop vs. 3 lines– Again – many good compilers will do this already

Cache frequently used values– Again – compilers are pretty good at this

Rewrite in a lower-level language– Costs programmer time

Good, modern compilers– Already do much of this– Are often better at it than you are– Are faster– Better at optimizing straightforward code than tricky code– Can often improve your code by 40% or more!!

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Quote from McConnell – About Code-Tuning Optimizations

“Computers are dramatically faster and memory is more plentiful. In the first edition [written 10 years ago], I ran most of the tests in this chapter [26] 10,000 to 50,000 times to get meaningful, measurable results. For this edition I had to run most tests 1 million to 100 million times. When you have to run a test 100 million times to get measurable results, you have to ask whether anyone will ever notice the impact in a real program. Computers have become so powerful that for many common kinds of programs, the level of performance optimization discussed in this chapter has become irrelevant. … People writing desktop applications may not need this information, but people writing software for embedded systems, real-time systems, and other systems with strict speed or space restrictions can still benefit from it.” – pg 643-644, Chapter 26.7, Code Complete 2.

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Space Efficiency

Time is not the only measure of a program’s performance– Which is more important space or time?

First principle of space optimization?– Don’t do it

What is paging? Caching? Why do we care? Use the smallest possible data type

– int vs. short

Don’t store what you can easily recompute– What tradeoff is going on here?

– Image compression description is a good one to consider

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Summary

The best is the enemy of the good Don’t do space or time optimization

– Unless you have to– Unless you have measured it– Unless you know where the hot spots are– Unless you decide what real improvements are possible

Check algorithms and data structures– Can have the single most benefit– “Don’t put lipstick on a pig!!! ”

Turn on compiler optimization Be careful of hardware differences

– A PC with a big cache vs. no cache

Resort to detailed tuning only as last resort or if your environment demands it

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Notes About Tools

VS.Net 2005 has its own performance tools which was demonstrated in discussion yesterday