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Ublas : |
From: David M Garza (David.M.Garza_at_[hidden])
Date: 2006-01-31 19:48:32
I wondered if this wouldn't be the case. :) Thanks for offering though.
I've started working on using array adaptors to do the job. I've had to
create constructors for the sparse arrays which take the adapted arrays
as arguments.
Should I be using shared_array_adaptor or can I just get away with
array_adaptor? The copy I'm hoping to avoid is between the array passed
in through the subroutine argument list and the value array in a uBLAS
sparse matrix data structure. As long as I can wrap the array passed in
through the argument list, I can work the rest of the code to avoid
subsequent copies of the sparse matrix object. From what I can tell
looking at array_adaptor and shared_array_adaptor, these are the copies
I would avoid by using the shared_array_adaptor.
David
eeitan_at_[hidden] wrote:
> i do not know this package and i understand this package is not a free ware
> so...
> Quoting David M Garza <David.M.Garza_at_[hidden]>:
>
>
>>SNOPT. I'm using the interface where it will expect the matrix in
>>compressed column form. The argument list for the callback function
>>only provides the value array--it expects you to remember the index
>>arrays separately. I guess if you know SNOPT you know this already...
>>Thanks!
>>David
>>
>>eeitan_at_[hidden] wrote:
>>
>>>Quoting David M Garza <David.M.Garza_at_[hidden]>:
>>>
>>>
>>>
>>>>I'm working with a numerical optimizer designed for large, sparse
>>>>problems and written in Fortran. When the the optimizer calls back for
>>>>a Jacobian evaluation it passes the array where it expects the Jacobian
>>>>values to be placed. Is there a simple way to build a uBLAS sparse
>>>>matrix object which simply wraps this array? My first thought is no,
>>>>but my second thought is "I could make a custom allocator..." Has
>>>>someone already tackled this problem? I expect this array to be big
>>>>(10,000-100,000 elements) so I'd like to avoid just copying it.
>>>>
>>>>Thanks,
>>>>David
>>>>
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>>>>
>>>
>>>if you could tell me which optimizer it is, i will try to do so.
>>>
>>>
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>>
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