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AGSOE: Arbeitsgruppe Physik sozio-ökonomischer Systeme
AGSOE 3: Financial Markets and Risk Management II
AGSOE 3.2: Vortrag
Montag, 23. März 2009, 10:45–11:15, BAR 205
GPU Accelerated Fluctuation Analysis and Complex Pattern Formation — •Tobias Preis1,2, Peter Virnau1, Wolfgang Paul1, and Johannes J. Schneider1 — 1Department of Physics, Mathematics and Computer Science, Johannes Gutenberg University of Mainz - Staudinger Weg 7, D-55099 Mainz, Germany — 2Artemis Capital Asset Management GmbH, Gartenstr. 14, D-65558 Holzheim, Germany
The compute unified device architecture is a fundamentally new programming approach for managing computations on a graphics processing unit (GPU) as a data-parallel computing device. With continuously increasing number of cores in combination with a high memory bandwidth, a recent GPU offers incredible resources for computational physics. We apply this revolutionary new technology to methods of fluctuation analysis, which includes determination of the scaling behavior of a stochastic process and the equilibrium autocorrelation function. Additionally, the recently introduced pattern formation conformity [T. Preis et al , Europhys. Lett. 82, 68005 (2008)], which quantifies pattern-based complex short-time correlations of a time series, is calculated on a GPU and analyzed in detail. Results are obtained up to 84 times faster than on a current central processing unit core. When we apply this method to high-frequency time series of the German BUND future, we find significant pattern based correlations on short time scales. Furthermore, an anti-persistent behavior can be found on short time scales. Additionally, we compare the recent GPU generation, which provides a theoretical peak performance of up to roughly 1012 floating point operations per second with the previous one.