11–20 of 53 posts
Something here doesn't sit right with me. Please don't launch into a lecture on algorithmic complexity and cache lines if you are running on Ruby on Rails.
Replace the token matcher with a simple classifier (a maxent will work very well here) with n-gram of characters features through a hash-kernel and you get a very accurate, fast and low memory system.
I've build one two-years ago who accurately classified a bit over 100 different languages with only 64k features in the end. (So requiring only 8*64ko of memory) And this was without using file extensions as they weren't available in our case.
Before any hard optimizations, first check the methods used, and next the algorithm, anything else should go after.
Something here doesn't sit right with me. Please don't launch into a lecture on algorithmic complexity and cache lines if you are running on Ruby on Rails.
Slow platforms are exactly where you need to talk algorithmic complexity. Switching to a faster environment would only reduce a routine's execution time by a constant multiplier—switching algorithms has the potential to do much more.
This just feels like "we have this huge and slow Ruby behemoth here, but using magic Judy arrays we made this little gear turn insanely fast!".
Sometimes Mods change the title to be the original article title. And sometimes they change it from the original article title to something else!
I would have liked to seen the Judy array implementation in pure Ruby, so we could compare apples to apples. I'm not trying to troll... but basically they solved their problem by: * Avoiding Ruby language features * Rewriting it in a different language This is why I lean towards static languages like Go, Scala, and Java.
Wow this is an incredibly interesting and accessible article on performance tuning. I have two questions: 1) Is there an easy tutorial somewhere on calling out to native code from Ruby? 2) Could the team at Github possible give a little more detail on what you did to get all of those pretty benchmarking graphs? How did you get all of the info on memory usage and CPU activity (I assume it wasn't just time {command} >…
The canonical documentation is here: https://github.com/ruby/ruby/blob/trunk/README.EXT
I wonder if something like Crystal could have helped. https://github.com/manastech/crystal