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This effort is still a "work in progress". Please feel free to add comments. BRBut please make them stand out by bolding or underlining them. – Edward J. Yoon

Why sparse matrices?

ScaLAPACK handles only dense and banded matrices, But, Hama will be handles sparse matrices.

• Optimization algorithms are too complexity
• Sparse matrix operations cannot be optimized, However, Optimization has no value in the large-scale
• Many classes of problems result in matrices with a large number of zeros
• A sparse matrix is a special class of matrix that allows only the non-zero terms to be stored
• Reduction in the storage requirements for sparse matrices
• Significant speed improvement as many calculations involving zero elements are neglected
  

Storage of sparse matrices

I choosed HBase(sparse matrix storage) to reduce storage and complexity.

• Hama use column-oriented storage of matrices (HBase) , and so compressed column format is a natural choice of sparse storage
• Hama forces the elements of each column to be stored in increasing order of their row index
  

  1  0  0       (1,1) = 1           
  0  3  1       (2,2) = 3
  0  0  0       (2,3) = 1

Sparse Functions

• conversion
• Manipulate sparse matrices
• Graph Theory
• Reordering
• Linear Algebra
• Iterative techniques
• Miscellaneous