Sparse/Dense Matrix analysis for Matrix Multiplication

In matrix multiplication, Sparse Matrices can easily turn dense and bloat memory, one fully dense column and one fully dense row can cause a sparse %*% sparse operation have a dense result.

There are two issues here one with a quick Fix and one a bit more involved:

1. in ABt.Scala use check the `MatrixFlavor` of the combiner and use the flavor of the Block as the resulting Sparse or Dense matrix type:

   val comb = if (block.getFlavor == MatrixFlavor.SPARSELIKE) {
                 new SparseMatrix(prodNCol, block.nrow).t
               } else {
                 new DenseMatrix(prodNCol, block.nrow).t
               }
   

   a simlar check needs to be made in the blockify transformation.

1. More importantly, and more involved is to do an actual analysis of the resulting matrix data in the in-core mmul class and use a matrix of the appropriate Structure as a result.