On 04/21/2009 08:34 AM Laura Creighton wrote: > It is also hard for people to process fractional numbers when they are > thinking about speed. '2 times the speed' feels a lot easier to > understand than '2.1' times the speed. And once you get to numbers > less than 1, things break down altogether. If you want to tell me > that something is slower, I don't expect to hear it as 'some number > less than 1' times the speed. I want a very hard break at the point > 0, and for you then to go about telling me how many times slower than > something that something else is. > > For most measurements, I would be happy if nobody mentioned the words > 'speed', 'faster' and 'slower' at all. What I am _really_ interested, > is a measurement of time. And I have a much easier time understanding > time quantities, which I am used to dealing with, than speed quantites > which rarely show up in life. > > So while I am always a bit hazy on what 'x times the speed' really means, > when you change this to 'this program runs in half the time, one > quarter of the time, twice the time, or even .8 of the time' I have a > much easier time of it. I'm used to measuring time, and I expect it to > be linear. I'm not used to measuring speed, and I keep worrying > 'is this linear'? 'is this logarithmic?' 'is this exponential?'. It > is only when I get to measure the actual times taken to do some sort > of task, say a benchmark, that I get any real sense of whether a change > seems to be a trivial small improvement, or a colossal major one. > > I wonder if others feel the same way. > > Laura > _______________________________________________ > [email protected] > http://codespeak.net/mailman/listinfo/pypy-dev > IMHO 'speed' is distance/time physically, and time still belongs in the denominator for measures of computing performance reasonably called 'speed', e.g. mips == millions (of) instructions (executed) /second, or gigaflops, which is giga (billions) of floating point operations /second.
When software gets involved on top of the hardware, we have measures like pystones/second: -- Python 2.5.1 (r251:54863, May 4 2007, 16:52:23) [GCC 4.1.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> from test import pystone >>> pystone.main() Pystone(1.1) time for 50000 passes = 0.9 This machine benchmarks at 55555.6 pystones/second -- Or bogomips, for a minimal software layer ... When it comes to benchmark test performance, maybe one could have bogoteps -- bogus test executions / second -- maybe with milli or kilo etc prefixed and specific test identifiers postfixed? ;-) So cpython 2.5.1 on my laptop does 55555.6 bogoteps-pystn? Relative comparisons can then be percentages, as in cpython pystones/sec being 1500% (??) of pypy pystones/sec, or analogously for whatever specific test. Using the speed measures will depend, as in physical speed, on what question you want to answer, e.g., how long will it take to get to the beach if we average 50 mph, vs how fast do we have to average driving to get to the beach in two hours. Either way, you can't drive faster than your car will go, and that's distance/time ;-) How 'fast' is your car? How 'fast' is your computing platform? Put time in denominator ;-) Regards, Bengt Richter _______________________________________________ [email protected] http://codespeak.net/mailman/listinfo/pypy-dev
