Abstract: Convolution neural networks (CNNs) have been extensively used in machine learning applications. The most time-consuming part of CNNs are convolution operations. A common approach to ...

A high-performance implementation of matrix multiplication using Strassen’s algorithm and OpenMP-based parallelization. Developed as part of a Parallel Computing course to explore recursive algorithms ...

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for static ...

Abstract: This paper investigates sparse matrix-vector (SpMV) multiplication algorithm performance for unstructured sparse matrices. The development of an SpMV multiplication algorithm for this type ...

Montgomery algorithms represent a transformative advancement in the computation of modular arithmetic, specifically designed to bypass the costly division steps inherent in traditional methods. By ...

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