A Fault-Tolerant Distributed Solution for the Parallel Gaussian Reduction of Huge Arrays

Solving a linear system of equations is a common task performed for most of the scientific experiments. Everyday, these applications increase their demands, pushing the computational capacity to the limits. At a certain point, our systems, running common algorithms, become unable to process such massive amounts of information. The paper analyses and modifies the standard Gaussian reduction so that a huge array may be handled by almost any distributed system. Moreover, the paper focuses on providing a decent level of fault tolerance in order to comply with a real, heterogeneous distributed system and on becoming a solution for sensitive applications.