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Re: Mathematica 20x slower than Java at arithmetic/special functions, is
*To*: mathgroup at smc.vnet.net
*Subject*: [mg115891] Re: Mathematica 20x slower than Java at arithmetic/special functions, is
*From*: Leo Alekseyev <dnquark at gmail.com>
*Date*: Mon, 24 Jan 2011 05:56:56 -0500 (EST)
*References*: <201101232233.RAA22629@smc.vnet.net>
Vivek, Oliver -- thanks for your input! My knowledge in using
Compile[] is somewhat lacking (mostly, due to the fact that I was
never able to get it to work well for me). In particular, I tried
using Compile[] much in the same way that Vivek has suggested, but I
neglected to use Evaluate[], which leads to a compiled function taking
substantially longer. Is there a quick explanation for why Evaluate[]
(or, in Oliver's example, a construct like
With[{code=code},Compile[{...},code]] necessary?..
On my (very modest) hardware, I indeed get ~25x speedup that Vivek
mentions. Oliver's code for me performs about the same (~25x
improvement) without parallelism, and 2x faster on a dual-core
machine; this actually seems reasonable since the two methods are
fairly similar.
I should note that it seems that these optimizations are very
dependent on Mathematica 8: in particular, cfunc2 (compilation of a
compiled function evaluating over some data) in Vivek's example gives
no additional gain under Mathematica 7 (makes me curious what changed
in version 8), and RuntimeAttributes -> Listable, Parallelization ->
True options that Oliver uses are new to version 8.
--Leo
On Mon, Jan 24, 2011 at 4:14 AM, Vivek J. Joshi <vivekj at wolfram.com> wrote:
> Without going into too much detail, a simple compilation of the function gives approx 6x to 25x speed up,
>
> ClearAll[grid1dc];
> grid1dc[x_,y_]=(With[{d=0.1,NN=50},
> Sum[Re[N[d BesselJ[1,2 Pi d Sqrt[m^2+n^2]]/Sqrt[m^2+n^2+10^-7]] Exp[I 2.0Pi (m x+n y)]],{m,-NN,NN,1},{n,-NN,NN,1}]])//N;
>
> gridres1da=With[{delta=0.5,xlim=2.5,ylim=2.5},
> Table[{x,y,grid1dc[x,y]},{x,-xlim,xlim,delta},{y,-ylim,ylim,delta}]];//AbsoluteTiming
> {7.371354,Null}
>
> Clear[cfunc];
> cfunc = Compile[{{x,_Real},{y,_Real}},Evaluate[grid1dc[x,y]]];
>
> gridres1da2=With[{delta=0.5,xlim=2.5,ylim=2.5},
> Table[{x,y,cfunc[x,y]},{x,-xlim,xlim,delta},{y,-ylim,ylim,delta}]];//AbsoluteTiming
> {1.237029,Null}
>
> Norm[gridres1da[[All,All,3]]-gridres1da2[[All,All,3]]]//Chop
> 0
>
> Following gives about 25x speedup,
>
> Clear[cfunc2];
> cfunc2= Compile[{{xlim,_Real},{ylim,_Real},{delta,_Real}},
> Block[{x,y},
> Table[{x,y,cfunc[x,y]},{x,-xlim,xlim,delta},{y,-ylim,ylim,delta}]]];
>
> gridres1da3=cfunc2[2.5,2.5,0.5];//AbsoluteTiming
> {0.292562,Null}
>
> Norm[gridres1da[[All,All,3]]-gridres1da3[[All,All,3]]]//Chop
> 0
>
> Vivek J. Joshi
> Kernel Developer
> Wolfram Research Inc.
>
> On Jan 24, 2011, at 4:03 AM, Leo Alekseyev wrote:
>
>> I was playing around with JLink the other day, and noticed that Java
>> seems to outperform Mathematica by ~20x in an area where I'd expect
>> Mathematica to be rather well optimized -- arithmetic involving special
>> functions. In my particular example, I am simply evaluating a sum of
>> Bessel functions. I understand that much depends on the underlying
>> implementation, but I just want to run this by Mathgroup to see if
>> this is to be expected, or maybe if I'm doing something suboptimal in
>> Mathematica. Here's the code that I'm running:
>>
>> grid1dc[x_,
>> y_] = (With[{d = 0.1, NN = 50},
>> Sum[Re[N[
>> d BesselJ[1, 2 Pi d Sqrt[m^2 + n^2]]/
>> Sqrt[m^2 + n^2 + 10^-7]] Exp[
>> I 2.0 Pi (m x + n y)]], {m, -NN, NN, 1}, {n, -NN, NN, 1}]=
]) //
>> N
>>
>> and
>>
>> gridres1da =
>> With[{delta = 0.5, xlim = 2.5, ylim = 2.5},
>> Table[{x, y, grid1dc[x, y]}, {x, -xlim, xlim, delta}, {y, -ylim,
>> ylim, delta}]]
>>
>>
>> Java implementation uses Colt and Apache common math libraries for the
>> Bessels and complex numbers, uses a double for loop, and consistently
>> runs 15-20 times faster.
>>
>> --Leo
>>
>
>
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