On Thursday, February 5, 2015 at 9:35:52 PM UTC+1, Mike Galloy wrote:
> On 2/5/15, 3:41 AM, superchromix wrote:
>>
>> hi Mike,
>>
>> I notice that there is a new function called GPULEASTSQUARES. Is
>> this an implementation of the GPU-based least squares fitting which
>> you have mentioned in the past? It would be great if you could
>> include a usage example in the documentation.
>>
>> best Mark
>>
>
> The GPULib distribution includes a unit test for GPULEAST_SQUARES shown
> below (ignore the ASSERT statements, that is just checking to make sure
> things are as the test expects along the way):
>
> function gpuleast_squares_ut::test_float
> compile_opt strictarr
>
> assert, !gpu.mode ne 0, 'GPULEAST_SQUARES not available in emulation
> mode', /skip
> assert, !gpu.mode eq 0L || gpulmgr(/full), 'GPULib not licensed for
> LAPACK calculations', /skip
> assert, !gpu.mode eq 0L || gpuMagmaPresent(), 'MAGMA not present', /skip
>
> a = [[1., 2., 1.], [4., 10., 15.], [3., 7., 1.]]
> dims = size(a, /dimensions)
> m = dims[0]
> n = dims[1]
>
> b = [2., 3., 7.]
>
> standard = la_least_squares(a, b)
>
> da = gpuputarr(a, ERROR=err)
> assert, err eq 0, 'CUDA error: %s', gpu_errormessage(err)
>
> db = gpuputarr(b, ERROR=err)
> assert, err eq 0, 'CUDA error: %s', gpu_errormessage(err)
>
> dresult = gpuleast_squares(da, db, ERROR=err)
> assert, err eq 0, 'CUDA error: %s', gpu_errormessage(err)
>
> result = gpugetarr(dresult, ERROR=err)
> assert, err eq 0, 'CUDA error: %s', gpu_errormessage(err)
>
> error = total(abs(standard - result), /preserve_type)
> assert, error lt self.tolerance * n * 10.0, 'incorrect result: error
> = %g', error
>
> gpuFree, [da, db, dresult]
>
> return, 1
> end
>
>
> function gpuleast_squares_ut::test_double
> compile_opt strictarr
>
> assert, !gpu.mode ne 0, 'GPULEAST_SQUARES not available in emulation
> mode', /skip
> assert, !gpu.mode eq 0L || gpulmgr(/full), 'GPULib not licensed for
> LAPACK calculations', /skip
> assert, !gpu.mode eq 0L || gpuMagmaPresent(), 'MAGMA not present', /skip
> assert, !gpu.mode eq 0L || gpuDoubleCapable(), 'CUDA device not
> double capable', /skip
>
> a = [[1.0D, 2.0D, 1.0D], [4.0D, 10.0D, 15.0D], [3.0D, 7.0D, 1.0D]]
> dims = size(a, /dimensions)
> m = dims[0]
> n = dims[1]
>
> b = [2.0D, 3.0D, 7.0D]
>
> standard = la_least_squares(a, b, /DOUBLE)
>
> da = gpuputarr(a, ERROR=err)
> assert, err eq 0, 'CUDA error: %s', gpu_errormessage(err)
>
> db = gpuputarr(b, ERROR=err)
> assert, err eq 0, 'CUDA error: %s', gpu_errormessage(err)
>
> dresult = gpuleast_squares(da, db, ERROR=err)
> assert, err eq 0, 'CUDA error: %s', gpu_errormessage(err)
>
> result = gpugetarr(dresult, ERROR=err)
> assert, err eq 0, 'CUDA error: %s', gpu_errormessage(err)
>
> error = total(abs(standard - result), /preserve_type)
> assert, error lt self.tolerance * n * 10.0, 'incorrect result: error
> = %g', error
>
> gpuFree, [da, db, dresult]
>
> return, 1
> end
>
> Mike
> --
> Michael Galloy
> www.michaelgalloy.com
> Modern IDL: A Guide to IDL Programming (http://modernidl.idldev.com)
> Research Mathematician
> Tech-X Corporation
I see - thanks. I guess I was looking for a non-linear least squares solver.
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