Balanced Technical Computing - Solving Big Data problems a novel way

<!--HTML--><p style="text-align:justify;"> Laplace’s explanation of the special 4:2:1 orbit ratio of Jupiter’s 3 innermost Galilean moons, the “Laplace resonance”, was assumed by Astronomers for centuries to be a stable phenomenon. However recent observations have shown that the Laplace resonance of the Jovian system is breaking, in part due to tidal forces. The loss of the Laplace resonance will have a profound impact on the Galilean moons including the extinguishing of Io’s volcanoes and the freezing of an ocean that has been predicted to exist under the surface of Europa. <p style="text-align:justify;"> In this presentation we use the Jovian Laplace resonance as an example of Big Data problem, more specifically solved using Balanced Computing clusters. Balanced Computing focuses on solving large computational problems requiring a roughly equivalent amount of CPU, memory and I/O. Time allowing, we will talk about Tetration Analytics, another “Big Data” use case using novel sensor technology. <h4>About the speakers</h4> <p style="text-align:justify;"> <a href="https://en.wikipedia.org/wiki/Landon_Curt_Noll" target="_blank">Landon Noll</a> is an Astronomer, Mathematician, Computer Scientist, Inventor and a Principal Engineer at Cisco. <p style="text-align:justify;"> Rene Raeber is a Distinguished Engineer at Cisco, expert in Datacenter Architecture, Application Centric Infrastructure and Tetration Analytics. He is working among others on data processing technologies for the SKA.