Replacing the doseq's with dotimes speeds it up a little more:
(defn gaussian-matrix5 [^"[[D" arr]
(dotimes [x (alength arr)]
(dotimes [y (alength (first arr))]
(aset-double ^doubles (aget arr (int x)) (int y) (next-
gaussian)))))
but I'm getting reflection warnings on alength. I guess it doesn't
cause a problem because they're only called once?
Also adding type hints to the more functional version of my first
attempt speeds things up quite a bit:
(defn gaussian-matrix2 [L]
(into-array ^doubles
(map double-array (partition L (repeatedly (* L L) next-
gaussian)))))
But it's still about 4x slower than gaussian-matrix5 above. There must
be a way to improve on the inner loop here that doesn't require using
indices, right?
On Sep 20, 12:32 pm, Jason Wolfe <jawo...@berkeley.edu> wrote:
> Oops, I found aset-double2 with tab completion and figured it was
> build-in. Forgot it was a utility I built some time ago, a stub for a
> Java method that does the setting.
>
> Also, I got the type hint for the "arr" arg wrong, although it didn't
> seem to matter.
>
> Here's a fixed version in standard Clojure that's basically as fast:
>
> user> (defn gaussian-matrix4 [^"[[D" arr ^int L]
> (doseq [x (range L) y (range L)] (aset-double ^doubles
> (aget arr (int x)) (int y) (.nextGaussian ^Random r))))
> #'user/gaussian-matrix4
> user> (do (microbench (gaussian-matrix3 (make-array Double/TYPE 10
> 10) 10)) (microbench (gaussian-matrix4 (make-array Double/TYPE 10 10)
> 10)) )
> min; avg; max ms: 0.000 ; 0.033 ; 8.837 ( 56828 iterations)
> min; avg; max ms: 0.009 ; 0.038 ; 7.132 ( 50579 iterations)
>
> It seems like you should be able to just use aset-double with multiple
> indices (in place of aset-double2), but I can't seem to get the type
> hints right.
>
> -Jason
>
> On Sep 20, 7:36 am, Ranjit <rjcha...@gmail.com> wrote:
>
> > 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
>
>
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