The proposed parallel algorithm computes the Correlation Dimension from a time series generated by a dynamical system, using a box-assisted approach and a virtual shared memory model. The algorithm is tested on a cluster of workstations; it shows good performance and allows the efficient computation of D_2 also for high-dimensional systems, when an extremely large number of points is needed.
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