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 netlibjava instead
(will it remain in MLlib in future releases)?
Best regards, Alexander
