Multiscale Dataflow Computing

17 June 2013
12:00
Dr Oskar Menser
Abstract

*****     PLEASE NOTE THIS SEMINAR WILL TAKE PLACE ON MONDAY 17TH JUNE 2013     *****

Computing is an exercise of discretization of the real world into space, time, and value. While discretization in time and space is well understood in the sciences, discretization of value is a scientific domain full of opportunity. Maxeler's Multiscale Dataflow Computing allows the programmer to finely trade off discretization of value with real performance measured in wallclock time.

In this talk I will show the connection between discretization of value and Kolmogorov Complexity on one hand and approximation theory on the other. Utilizing the above concepts together with building general purpose computing systems based on dataflow concepts, has enabled us to deliver production systems for Oil & Gas imaging (modelling, multiple elimination, RTM, Geomechanics), Finance Risk (derivatives modelling and scenario analysis), as well as many scientific application such as computing weather models, Astrochemistry, and brain simulations. Algorithms range from 3D Finite Difference, Finite Elements (sparse matrix solvers), pattern matching, conjugate gradient optimization, to communication protocols and bitcoin calculations. Published results of users of our machines show a 20-50x total advantage in computations per unit space (1U) and computations per Watt.

*****     PLEASE NOTE THIS SEMINAR WILL TAKE PLACE ON MONDAY 17TH JUNE 2013     *****

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