I have a large matrix of the order 1M x 300 (obtained after SVD decomposition of a large item matrix). So, the matrix is a dense one with float as data type. I would like to compute the similarity matrix by multiplying the dimensionally reduced matrix with its transpose.
- I implemented the matrix multiplication method and that doesn't just end.
- What are the ways to perform matrix multiplication between the dense matrix (~1M rows x 300 columns) with its transpose?
- Will using MapReduce help in speeding up the job?
- I also saw Apache Hama being efficient for large matrix computations. Will that fit my problem?
- Strassen's algorithm is also used for large matrices, how do i use it?
Any other solutions/suggestion for it?
