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.ula...@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.da...@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.ula...@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.da...@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.ula...@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 >>> >> >> >
