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Sparse Matrix Storage Formats
It is more efficient to store only the non-zero elements of a sparse matrix. There are a number of common storage formats used for sparse matrices, but most of them employ the same basic technique. That is, store all non-zero elements of the matrix into a linear array and provide auxiliary arrays to describe the locations of the non-zero elements in the original matrix.
Storage Formats for the Direct Sparse Solvers
Storing the non-zero elements of a sparse matrix into a linear array is done by walking down each column (column-major format) or across each row (row-major format) in order, and writing the non-zero elements to a linear array in the order they appear in the walk.
Sparse Matrix Storage Formats for Sparse BLAS Levels 2 and Level 3
These sections describe in detail the sparse matrix storage formats supported in the current version of the Intel® oneAPI Math Kernel Library (oneMKL) Sparse BLAS Level 2 and Level 3.
- DSS Symmetric Matrix Storage
- DSS Nonsymmetric Matrix Storage
- DSS Structurally Symmetric Matrix Storage
- DSS Distributed Symmetric Matrix Storage
- Sparse BLAS CSR Matrix Storage Format
- Sparse BLAS CSC Matrix Storage Format
- Sparse BLAS Coordinate Matrix Storage Format
- Sparse BLAS Diagonal Matrix Storage Format
- Sparse BLAS Skyline Matrix Storage Format
- Sparse BLAS BSR Matrix Storage Format