A new chip aims to dramatically reduce energy consumption while accelerating the processing of large amounts of data.

Abstract: Solving the large-scale linear system of equations is one of the most fundamental problems both in theory and practice. However this problem requires too much computational resource for most ...

Generating random values with different distributions. Even ones given by table of density function. Vectors and matrices with arbitrary dimensions count. Vectors can be rotated and represented in ...

This class will cover material from three areas: Spectral Graph Theory, Numerical Linear Algebra, and Biomedical Applications. The central issue in spectral graph theory is understanding, estimating, ...

Abstract: Sparse Bayesian learning (SBL) employs Gaussian priors with unknown parameters to solve an underdetermined system of linear equation. It provides comparable performance and is significantly ...

Dramatically reducing energy consumption while accelerating the processing of large amounts of data. This is the aim of the ...

What began with a focus on weather forecasting has evolved toward addressing errors in scientific modeling. In the collaborative environment of the Penn State Institute for Computational and Data ...