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From Debasish Das <debasish.da...@gmail.com>
Subject Re: Which linear algebra interface to use within Spark MLlib?
Date Thu, 19 Mar 2015 22:06:59 GMT
Yeah it will be better if we consolidate the development on one of
them...either Breeze or mllib.BLAS...

On Thu, Mar 19, 2015 at 2:25 PM, Ulanov, Alexander <alexander.ulanov@hp.com>
wrote:

>  Thanks for quick response.
>
>  I can use linealg.BLAS.gemm, and this means that I have to use MLlib
> Matrix. The latter does not support some useful functionality needed for
> optimization. For example, creation of Matrix given matrix size, array and
> offset in this array. This means that I will need to create matrix in
> Breeze and convert it to MLlib. Also, linalg.BLAS misses some useful BLAS
> functions I need, that can be found in Breeze (and netlib-java). The same
> concerns are applicable to MLlib Vector.
>
> Best regards, Alexander
>
> 19.03.2015, в 14:16, "Debasish Das" <debasish.das83@gmail.com> написал(а):
>
>   I think for Breeze we are focused on dot and dgemv right now (along
> with several other matrix vector style operations)...
>
>  For dgemm it is tricky since you need to do add dgemm for both
> DenseMatrix and CSCMatrix...and for CSCMatrix you need to get something
> like SuiteSparse which is under lgpl...so we have to think more on it..
>
>  For now can't you use dgemm directly from mllib.linalg.BLAS ? It's in
> master...
>
>
> On Thu, Mar 19, 2015 at 1:49 PM, Ulanov, Alexander <
> alexander.ulanov@hp.com> wrote:
>
>>  Thank you! When do you expect to have gemm in Breeze and that version
>> of Breeze to ship with MLlib?
>>
>>  Also, could someone please elaborate on the linalg.BLAS and Matrix? Are
>> they going to be developed further, should in long term all developers use
>> them?
>>
>> Best regards, Alexander
>>
>> 18.03.2015, в 23:21, "Debasish Das" <debasish.das83@gmail.com>
>> написал(а):
>>
>>    dgemm dgemv and dot come to Breeze and Spark through netlib-java....
>>
>>  Right now both in dot and dgemv Breeze does a extra memory allocate but
>> we already found the issue and we are working on adding a common trait that
>> will provide a sink operation (basically memory will be allocated by
>> user)...adding more BLAS operators in breeze will also help in general as
>> lot more operations are defined over there...
>>
>>
>> On Wed, Mar 18, 2015 at 8:09 PM, Ulanov, Alexander <
>> alexander.ulanov@hp.com> wrote:
>>
>>> Hi,
>>>
>>> Currently I am using Breeze within Spark MLlib for linear algebra. I
>>> would like to reuse previously allocated matrices for storing the result of
>>> matrices multiplication, i.e. I need to use "gemm" function C:=q*A*B+p*C,
>>> which is missing in Breeze (Breeze automatically allocates a new matrix to
>>> store the result of multiplication). Also, I would like to minimize gemm
>>> calls that Breeze does. Should I use mllib.linalg.BLAS functions instead?
>>> While it has gemm and axpy, it has rather limited number of operations. For
>>> example, I need sum of the matrix by row or by columns, or applying a
>>> function to all elements in a matrix. Also, MLlib Vector and Matrix
>>> interfaces that linalg.BLAS operates seems to be rather undeveloped. Should
>>> I use plain netlib-java instead (will it remain in MLlib in future
>>> releases)?
>>>
>>> Best regards, Alexander
>>>
>>
>>
>

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