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 >> > >
