Coefficient matrix of linear equations from finite element method (FEM) is sparse and symmetrical. For the sake of CPU operational time saving to accesses data in matrix decomposition and reducing ...

The Matrix first hit theatres in 1999, and it’s safe to say it’s been living rent-free in our minds ever since. This sci-fi ...

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math ...

Our results offer surprising insights into sparse signal recovery. For example, as far as support recovery is concerned, the well-known bound in Compressive Sensing with the Gaussian measurement ...

DBCSR is a library designed to efficiently perform sparse matrix-matrix multiplication, among other operations. It is MPI and OpenMP parallel and can exploit Nvidia and AMD GPUs via CUDA and HIP. To ...