Thanks Jason, this is great. I was confused earlier because I wasn't seeing reflection warnings, but it turns out that was only because I was evaluating the function definitions in the emacs buffer, and the warnings weren't visible.
I have a question about gaussian-matrix3 though. What is "aset- double2"? Is that a macro that has a type hint for an array of doubles? Thanks, -Ranjit On Sep 19, 5:37 pm, Jason Wolfe <jawo...@berkeley.edu> wrote: > Hi Ranjit, > > The big perf differences you're seeing are due to reflective calls. > Getting the Java array bits properly type-hinted is especially tricky, > since you don't always get good reflection warnings. > > Note that aset is only fast for reference types: > > user> (doc aset) > ------------------------- > clojure.core/aset > ([array idx val] [array idx idx2 & idxv]) > Sets the value at the index/indices. Works on Java arrays of > reference types. Returns val. > > So, if you want to speed things up ... here's your starting point: > > user> (set! *warn-on-reflection* true) > true > user> (import java.util.Random) > (def r (Random. )) > > (defn next-gaussian [] (.nextGaussian r)) > > (defn gaussian-matrix1 [arr L] > (doseq [x (range L) y (range L)] (aset arr x y (next-gaussian)))) > > (defn gaussian-matrix2 [L] > (into-array (map double-array (partition L (repeatedly (* L L) > next-gaussian))))) > > Reflection warning, NO_SOURCE_FILE:1 - reference to field nextGaussian > can't be resolved. > > user> (do (microbench (gaussian-matrix1 (make-array Double/TYPE 10 > 10) 10)) (microbench (gaussian-matrix2 10)) ) > min; avg; max ms: 2.944 ; 4.693 ; 34.643 ( 424 iterations) > min; avg; max ms: 0.346 ; 0.567 ; 11.006 ( 3491 iterations) > > ;; Now, we can get rid of the reflection in next-guassian: > > user> (defn next-gaussian [] (.nextGaussian #^Random r)) > #'user/next-gaussian > user> (do (microbench (gaussian-matrix1 (make-array Double/TYPE 10 > 10) 10)) (microbench (gaussian-matrix2 10)) ) > min; avg; max ms: 2.639 ; 4.194 ; 25.024 ( 475 iterations) > min; avg; max ms: 0.068 ; 0.130 ; 10.766 ( 15104 iterations) > nil > > ;; which has cut out the main bottleneck in gaussian-matrix2. > ;; 1 is still slow because of its array handling. > ;; here's a fixed version: > > user> (defn gaussian-matrix3 [^doubles arr ^int L] > (doseq [x (range L) y (range L)] (aset-double2 arr (int x) (int > y) (.nextGaussian ^Random r)))) > #'user/gaussian-matrix3 > > user> (do (microbench (gaussian-matrix1 (make-array Double/TYPE 10 > 10) 10)) (microbench (gaussian-matrix2 10)) (microbench (gaussian- > matrix3 (make-array Double/TYPE 10 10) 10)) ) > min; avg; max ms: 2.656 ; 4.164 ; 12.752 ( 479 iterations) > min; avg; max ms: 0.065 ; 0.128 ; 9.712 ( 15255 iterations) > min; avg; max ms: 0.000 ; 0.035 ; 10.180 ( 54618 iterations) > nil > > ;; which is 100x faster than where we started. > > A profiler is often a great way to figure out what's eating up time. > Personally, I've never found the need to use a disassembler. > > Cheers, Jason -- You received this message because you are subscribed to the Google Groups "Clojure" group. To post to this group, send email to clojure@googlegroups.com Note that posts from new members are moderated - please be patient with your first post. To unsubscribe from this group, send email to clojure+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/clojure?hl=en
