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Julia has support for sparse vectors and [sparse matrices](https://en.wikipedia.org/wiki/Sparse_matrix)
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in the `SparseArrays` stdlib module. Sparse arrays are arrays that contain enough zeros
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that storing them in a special data structure leads to savings in space and execution time,
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compared to dense arrays.
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in the `SparseArrays` stdlib module. Sparse arrays are arrays that contain enough zeros that storing them in a special data structure leads to savings in space and execution time, compared to dense arrays.
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External packages which implement different sparse storage types, multidimensional sparse arrays, and more can be found in [Noteworthy external packages](@ref man-csc)
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3.[SparseMatricesCSR.jl](https://github.com/gridap/SparseMatricesCSR.jl) provides a Julia native implementation of the Compressed Sparse Rows (CSR) format.
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4.[MKLSparse.jl](https://github.com/JuliaSparse/MKLSparse.jl) accelerates SparseArrays sparse-dense matrix operations using Intel's MKL library.
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5.[SparseArrayKit.jl](https://github.com/Jutho/SparseArrayKit.jl) available for multidimensional sparse arrays.
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6.[LuxurySparse.jl](https://github.com/QuantumBFS/LuxurySparse.jl) provides static sparse array formats, as well as a coordinate format.
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7.[ExtendableSparse.jl](https://github.com/j-fu/ExtendableSparse.jl) enables fast insertion into sparse matrices using a lazy approach to new stored indices.
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