Burak Yavuz created SPARK-3418:
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Summary: Additional BLAS and Local Sparse Matrix support
Key: SPARK-3418
URL: https://issues.apache.org/jira/browse/SPARK-3418
Project: Spark
Issue Type: New Feature
Components: MLlib
Reporter: Burak Yavuz
Currently MLlib doesn't have Level-2 and Level-3 BLAS support. For Multi-Model
training, adding support for Level-3 BLAS functions is vital.
In addition, as most real data is sparse, support for Local Sparse Matrices
will also be added, as supporting sparse matrices will save a lot of memory and
will lead to better performance. The ability to left multiply a dense matrix
with a sparse matrix, i.e. `C := alpha * A * B + beta * C` where `A` is a
sparse matrix will also be added. However, `B` and `C` will remain as Dense
Matrices for now.
I will post performance comparisons with other libraries that support sparse
matrices such as Breeze and Matrix-toolkits-JAVA (MTJ) in the comments.
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