Hi Dirk,
Sorry, I guess I missed the latter part of your question. Actually this is
probably related to a bug I notice earlier. I believe that it has been
fixed in the latest git version.
Check to see if the cosine and sine components are swapped in
{pycuda}/pycuda/cuda/pycuda-complex-impl.hpp
It should look like:
static complex<_Tp> expT(const complex<_Tp>& z) {
_Tp expx = ::exp(z._M_re);
_Tp s, c;
::sincos(z._M_im, &s, &c);
return complex<_Tp>(expx * c, expx * s);
}
Good luck,
Craig
>
> Message: 3
> Date: Fri, 21 Feb 2014 12:47:26 +0100
> From: Dirk Boonzajer Flaes <[email protected]>
> To: <[email protected]>
> Subject: Re: [PyCUDA] PyCUDA Digest, Vol 68, Issue 4
> Message-ID: <[email protected]>
> Content-Type: text/plain; charset="utf-8"; Format="flowed"
>
> Dear Craig,
>
> If this would be the problem would be, the second two tests would
> return false also.
>
> Take a look at the last part of the code:
>
> ....
> # .. but the imaginary part and the real part are just swapped
> print "Imag and real swapped 1: " ,
> np.all(g_random_complex.get().imag - random_complex.real < 1e-12)
> print "Imag and real swapped 2: " ,
> np.all(g_random_complex.get().real - random_complex.imag < 1e-12)
>
> This would return false if the treshold were the problem, however it
> returns true.
>
> I found out that
>
> np.exp(1j*x) = cumath.exp(1j*(pi/2-x)) for all x.
>
> So I suspect that this is a bug in cuda. Am I right?
>
> regards,
>
> Dirk
>
> On 20-02-14 21:38, Craig Stringham wrote:
> > The GPU uses single precision by default, so you need to use a higher
> > threshold 1e-7 works.
> > Craig
> >
> >
> > On Thu, Feb 20, 2014 at 10:00 AM, <[email protected]
> > <mailto:[email protected]>> wrote:
> >
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> > 1. strange behaviour of cumath.exp (Dirk Boonzajer Flaes)
> >
> >
> >
> ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Thu, 20 Feb 2014 17:31:36 +0100
> > From: Dirk Boonzajer Flaes <[email protected]
> > <mailto:[email protected]>>
> > To: <[email protected] <mailto:[email protected]>>
> > Subject: [PyCUDA] strange behaviour of cumath.exp
> > Message-ID: <[email protected] <mailto:[email protected]>>
> > Content-Type: text/plain; charset="iso-8859-1"; Format="flowed"
> >
> > Hi All!
> >
> > I am quite new to GPU programming, but I found some strange
> > behaviour in
> > the cumath.exp function. Maybe it is well known, but to me it
> > seems that
> > the real and imaginary part are swapped. Consider the following code:
> >
> >
> > import pycuda.gpuarray as gpuarray
> > import pycuda.autoinit
> > import pycuda.cumath as cumath
> > import numpy as np
> >
> > # create some random numbers in the complex plane
> > random_reals = np.random.rand(100,100)
> > random_complex = np.exp(1j*random_reals)
> >
> > # use the same random numbers, but compute the complex numbers
> on
> > the GPU
> > g_random_reals = gpuarray.to_gpu(random_reals)
> > g_random_complex = cumath.exp(1.j*g_random_reals)
> >
> > # it seems that the two arrays are not equal
> > print "Equal: " , np.all(g_random_complex.get().real -
> > random_complex.real < 1e-12)
> >
> > # .. but the imaginary part and the real part are just swapped
> > print "Imag and real swapped 1: " ,
> > np.all(g_random_complex.get().imag - random_complex.real < 1e-12)
> > print "Imag and real swapped 2: " ,
> > np.all(g_random_complex.get().real - random_complex.imag < 1e-12)
> >
> > prints
> >
> > Equal: False
> > Imag and real swapped 1: True
> > Imag and real swapped 2: True
> >
> >
> >
> >
> > Is this indeed a bug? Or am I just missing something?
> >
> > regards,
> >
> > Dirk
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