Aug 2, 2022 · Given two sparse matrices (Sparse Matrix and its representations | Set 1 (Using Arrays and Linked Lists)), perform operations such as add, multiply or transpose of the …

In-depth solution and explanation for LeetCode 311. Sparse Matrix Multiplication in Python, Java, C++ and more. Intuitions, example walk through, and complexity analysis. Better than official …

We present a new algorithm that multiplies A and B using O(m0.7n1 .2 n2 +o(1)) algebraic operations (i.e., multiplications, additions and subtractions) over. The na ̈ıve matrix …

SpGEMM is a special case of general matrix multiplication (GEMM) when two input matrices are sparse matrices.

Generalized sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high performance graph algorithms as well as for some linear solvers, such as algebraic multi-grid.

To address this problem, this paper proposes an efficient sparse matrix multiplication accelerator architecture, SpArch, which jointly optimizes the data locality for both input and output matrices.

Jul 1, 2005 · Let A and B two n × n matrices over a ring R (e.g., the reals or the integers) each containing at most m nonzero elements. We present a new algorithm that multiplies A and B …

We implement two novel algorithms for sparse-matrix dense-matrix multiplication (SpMM) on the GPU. Our algorithms expect the sparse input in the popular compressed-sparse-row (CSR) …

the new algorithm is also faster than the best known matrix multiplication algorithm for dense matrices which uses O ( n 2 : 38 ) algebraic operations. The new algorithm is obtained using a …

3 days ago · In prior work, Gupta et al. (SPAA 2022) presented a distributed algorithm for multiplying sparse \(n \times n\) matrices, using n computers. They assumed that the input …