Recently, a research team from the FhG Institute for Applied Solid State Physics and the University of Cologne has made significant progress in the field of quantum computing by proposing a new ...

Primary Algorithm : Algorithmically, Sparse-Sparse multiplication problems manifests itself in three possible forms:(a) Multiplication of a sparse matrix with a sparse diagonal, sparse block-diagonal, ...

Abstract: The solution of sparse matrix equations is essential in scientific computing. However, traditional solvers on digital computing platforms are limited by memory bottlenecks in largescale ...

Abstract: On multicore architectures, the ratio of peak memory bandwidth to peak floating-point performance (byte:flop ratio) is decreasing as core counts increase, further limiting the performance of ...

In this video from PASC17, Alfio Lazzaro (University of Zurich, Switzerland) presents: Increasing Efficiency of Sparse Matrix-Matrix Multiplication. “Matrix-matrix multiplication is a basic operation ...

This repository provides implementations of various matrix completion algorithms based on convex optimization. Convex optimization is particularly useful in this context because it offers theoretical ...