CS 3500 L Performance l Code Complete 2 – Chapters 25/26 and Chapter 7 of K&P l Compare today to 44 years ago – The Burroughs B1700 – circa 1974 l Why do we care about performance today? l First principle of optimization: – DON’T l Second principle of optimization: – DON’T l Third principle of optimization – DON’T B1700Today Proc Spd6Mhz3.8Ghz (dual) Memory64KB2GB Disk2.3MB hd per track 1TB InputCards Keyboard/ Monitor LangSDLC++ Cost?50K1K

CS 3500 L Optimization l Easiest technique is to turn on the compiler’s optimizer l In VS.NET do a release build vs. debug build l Makes debugging harder l 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

CS 3500 L Optimization - 2 l Measurement is the critical component before deciding that you should worry about performance improvement l 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 l Often algorithm analysis is the most fruitful place to start l How much faster is binary search than linear search on a one million element array? l See you in CS 4150!

CS 3500 L Targets of Improvement l Program design: how a program is divided into classes may make it hard or easy to improve performance l Class & method design: choice of data types, algorithms l Operating system interactions l Code compilation: the right compiler may be all you need l Hardware: why not a hardware upgrade? l Code tuning: small scale changes to correct code with hopes of running faster (or smaller)

CS 3500 L Timing l 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> l 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> l So, what should you do on systems like Windows to get a coarse view of time? – #include – double begin = clock(); –…–… – double result = clock() – begin; // time in ms

CS 3500 L The Pareto Principle (20% of Italians have 80% of the wealth) You can get 80% of the result with 20% of the effort. l 20% of a program consumes 80% of its execution time (Boehm) l Less than 4% of a program accounts for more than 50% of the run time (Knuth) l Measure your code for hot spots, and then put resources into optimizing the small portion(s) of the program used most

CS 3500 L Profiling l What is a profile? – A measure of where a program spends its time l 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 l Profiling is effective for finding hot spots in a program l How does a profiler work?

CS 3500 L Misconceptions l Reducing the lines of code in a high-level language improves the speed or size of the resulting machine code l Certain operations are probably faster or smaller than others l You should optimize as you go l A fast program is as important as a correct one l A fast program is as important as a readable one

CS 3500 L Strategies l 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 l Use a better algorithm or data structure – Try to determine complexity l Enable compiler optimizations – Measure before and after to make sure it is worth it l Tune the code – Adjust the loops and expressions to be faster l 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

CS 3500 L Tuning The Code l Collect common subexpressions – Is probably not worth it these days l Reduction in strength of operations – Again is probably not worth it these days l Unroll or eliminate loops – Short loop vs. 3 lines – Again – many good compilers will do this already l Cache frequently used values – Again – compilers are pretty good at this l Rewrite in a lower-level language – Costs programmer time l 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!!

CS 3500 L 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 , Chapter 26.7, Code Complete 2.

CS 3500 L Space Efficiency l Time is not the only measure of a program’s performance – Which is more important space or time? l First principle of space optimization? – Don’t do it l What is paging? Caching? Why do we care? l Use the smallest possible data type – int vs. short l Don’t store what you can easily recompute – What tradeoff is going on here? – Image compression description is a good one to consider

CS 3500 L Summary l The best is the enemy of the good l 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 l Check algorithms and data structures – Can have the single most benefit – “Don’t put lipstick on a pig!!! ” l Turn on compiler optimization l Be careful of hardware differences – A PC with a big cache vs. no cache l Resort to detailed tuning only as last resort or if your environment demands it

CS 3500 L Notes About Tools l VS.Net 2005 has its own performance tools which was demonstrated in discussion yesterday