Repository with codes for simulating and optimising quantum key distribution protocols. - pyqkd/matrix_multiply_parallel.py at main · gnypit/pyqkd ...

Objective: Matrix multiplication is a fundamental operation in various fields, including computer graphics, machine learning, and scientific computing. This project aims to optimize matrix ...

In many application areas, certain parts of the algorithm, which was then implemented in a computer programming environment can be run in parallel. Individual sections of the application can be sent ...

Nowadays high-performance computing is gradually implementing Exa-scale computing, and the performance of single node has reached several T-flops. Communication problem has become one of the main ...

The parallel calculation process of matrix multiplication, six kinds of color matrices represent the parallel calculation process for simplifying. The left figure shows the block diagonal matrices in ...

On-chip optical neural networks (ONNs) have recently emerged as an attractive hardware accelerator for deep learning applications, characterized by high computing density, low latency, and compact ...

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 ...

Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the sparse matrix-vector multiplication (SpMV) is critical for ...