Hello,
To strengthen Brian' point, running faster on at least one platform is a
necessary but not sufficient condition for a change like this since it
is possible the change could run slower on a different platform. To
guard against that being the case, with data points across more
platforms a better informed decision can be made.
Unfortunately, to my knowledge there isn't a convenient way to run a
test like this across a large set of platforms of interest.
Cheers,
-Joe
On 5/8/2017 6:01 PM, Brian Burkhalter wrote:
Thanks for running the numbers.
On May 8, 2017, at 5:42 PM, Isaac Levy <isaac.r.l...@gmail.com
<mailto:isaac.r.l...@gmail.com>> wrote:
bitCountInt avgt 10 44550.630 ± 2670.294 ns/op
[41880, 47221]
bitCountIntNew avgt 10 33904.058 ± 1108.438 ns/op
[32796, 35012]
bitCountLong avgt 10 58638.138 ± 3736.014 ns/op
[54902, 62374]
bitCountLongNew avgt 10 38700.601 ± 526.648 ns/op
[38174, 39227]
So the ranges don’t overlap which is important.
JDK 1.8.0_131, 2.3ghz Core i7, each run counting numbers 0 to 2^14
Thing is one needs to run the benchmark on a variety of hardware. I
went through a lot of this sort of thing myself when evaluating among
other things for example the crossover thresholds for the Karatsuba
and Toom-Cook multiplication algorithms in BigInteger multiplication.
There was a lot of variation.
Thanks,
Brian
