| Re: Is it possible to speed up the Interpolate command? [message #89242] |
Thu, 07 August 2014 17:42  |
Michael Galloy
Messages: 1114
Registered: April 2006
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Senior Member |
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On 8/7/14, 4:11 pm, sjm7w6@gmail.com wrote:
> I've been stuck on figuring out how to speed up an interpolation
> calculation and wondered if anyone has any suggestions?
>
> Here's the situation:
>
> I have a bunch (about 450,000) of 2d matrices that I need to
> interpolate within. Within each of the matrices, I'm looking to
> interpolate for 100 x/y combinations where I want values at points
> (x_1, y_1), (x_2, y_2), etc. (I am not looking to regrid the data,
> i.e., I don't need x_1,y_2). The matrices are currently stacked in a
> datacube (dimensions are 14 x 28 x 450000). Each of the matrices has
> the same x/y locations for the points to be interpolated. I thereby
> use "interpolate" to interpolate each matrix for the 100 values and
> then loop over the 3rd dimension. This utilizes the bilinear
> interpolation. Though, I have the matrices stacked in the data cube,
> I do not want a trilinear interpolation as the 3 dimension is
> independent. Here's the current code:
>
> for i=0, numlines-1 do begin
> Values(*,i)=interpolate(datacube(*,*,i),x_loc,y_loc) endfor
>
> Numlines is the n_elements(3rd dimension), which is the 450,000
> referenced above. The x and y dimensions of the data cube are 14 and
> 28, respectively..
>
> The interpolation is taking about 2 seconds to run. I'm looking to
> find a way to trim it as much as possible...hopefully less than 0.1
> seconds. This may be difficult given that the interpolation is
> calculating 45,000,000 values.
>
> Things I've tried: 1) I first removed the interpolation from the for
> loop. However, the combination of that interpolation with reforming
> the output result into the matrix I need requires this process to
> actually take longer than the for loop above...this provides evidence
> the existence of the for loop is not the rate limiting step.
>
> 2) I rearranged the datacube into a very large 2d matrix (basically
> stacking in the 2nd dimension as opposed to creating the 3rd
> dimension). This lead to the same calculation time as the original
> way above, so no gains there..
>
> I need a bilinear interpolation due to the first two dimensions being
> linked so interpol will not work. I do not need regridded data, so I
> don't think that Krig2d or bilinear offer any help.
>
> I know that I can speed up the code by simply decreasing the size of
> the 3rd dimension and/or by interpolating for less than 100 values
> per matrix, but I'm trying to avoid this.
>
> Any suggestions on how to calculate this faster?
>
> Thank you for your time.
>
You could try GPULib; it has a GPU accelerated interpolation routine.
Demo at: http://www.txcorp.com/home/gpulib. (Full disclosure: I am the
product manager for GPULib.) It only does bilinear interpolation, but it
sounds like you just want to do a stack of bilinear interpolations.
Mike
--
Michael Galloy
www.michaelgalloy.com
Modern IDL: A Guide to IDL Programming (http://modernidl.idldev.com)
Research Mathematician
Tech-X Corporation
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