Distributed computations, such as distributed matrix multiplication, can be vulnerable to significant security issues, notably Byzantine attacks. These attacks may target either worker nodes or ...

Accelerating matrix multiplication is crucial to achieve high performance in many application domains, including neural networks, graph analytics, and scientific computing. These applications process ...

Implementations of matrix multiplication via diffusion and reactions, thus eliminating the need for electronics, have been proposed as a stepping stone to realize molecular nano-neural networks (M3N).

Conclusion 🎯 This numerical computation library provides a comprehensive suite of algorithms essential for scientific computing and engineering applications. The dual implementation approach (manual ...

The official SuiteSparse library: a suite of sparse matrix algorithms authored or co-authored by Tim Davis, Texas A&M University ...