I updated the gist with times and code snippets https://gist.github.com/lqdc/9342237
On Tuesday, March 4, 2014 5:15:29 PM UTC-8, Steven G. Johnson wrote: > > It's odd that the performance gain that you see is so much less than the > gain on my machine. > > Try putting @time in front of "for w in words" and also in front of > "words=...". That will tell you how much time is being spent in each, and > whether the limitation is really hashing performance. > > On Tuesday, March 4, 2014 7:55:12 PM UTC-5, Roman Sinayev wrote: >> >> I got to about 0.55 seconds with the above suggestions. Still about 2x >> slower than Python unfortunately. >> The reason I find it necessary for hashing to work quickly is that I use >> it heavily for both NLP and when serving data on a Julia webserver. >> >
