The CSR library provides a sparse matrix class (in compressed sparse row format)
along with various matrix operations. Its capabilities are a subset of those
scipy.sparse.csr_matrix, with both the matrix type itself
and most of the operations accessible from Numba’s nopython mode.
csr.CSR class is the main entry point for using this package.
CSR is not currently suitable for use as a general-purpose sparse matrix package. It is quite good at representing sparse matrices in a form suitable for custom computations with Numba, and when the Intel MKL is available its Sparse BLAS is used to accelerate several operations.
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This material is based upon work supported by the National Science Foundation under Grant No. IIS 17-51278. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.