Abstract: Multiplication of a sparse matrix with a dense matrix is a building block of an increasing number of applications in many areas such as machine learning and graph algorithms. However, most ...

Cannon's algorithm is a parallel ... block of the result matrix by communicating with its neighboring processors to exchange necessary data. This structured communication pattern reduces the overall ...

The Matrix-Matrix of Cannon In order to swiftly multiply two huge matrices, multiplication is a parallel approach that distributes the work over a number of processors or cores. In particular, ...

Figure 3. Parallel data distribution and communication of sparse matrix multiplication when N p = 4. The density matrix is partitioned into four row block local matrices with 1D row BN nanotube (BNNT) ...

“Matrix-matrix multiplication is a basic operation in linear algebra and an essential building block for a wide range of algorithms in various scientific fields. Theory and implementation for the ...

In this paper, we propose two efficient algorithms -- TSM2R and TSM2L -- for two classes of tall-and-skinny matrix-matrix multiplications on GPUs. Both of them focus on optimizing linear algebra ...

Parallel computing continues to advance, addressing the demands of high-performance tasks such as deep learning, scientific simulations, and data-intensive computations. A fundamental operation within ...

Abstract: Multiplication of a sparse matrix with a dense matrix is a building block of an increasing number of applications in many areas such as machine learning and graph algorithms. However, most ...