An approach for the fast analysis of "irregular", i.e., of conformal, periodic or aperiodic, 2D arrays, based on the use of the p-series approach and Non-Uniform FFT (NUFFT) routines is proposed. The approach allows for modulating the computational burden depending on the array curvature and, thanks to the use of the NUFFT, the asymptotic growth of the computing time reduces to that of a few, standard FFTs. A sub-array partition strategy is also sketched and shown to further unburden the procedure and control the accuracy. The approach has been implemented in both sequential and parallel codes enabling its execution on CPUs and on cost-effective, massively parallel computing platforms like Graphic Processing Units (GPUs). Its performance in terms of computational efficiency and accuracy has been assessed by an extensive numerical analysis and also against benchmarks provided by algorithms based on fast Matrix-Vector Multiplication routines.

Fast CPU/GPU pattern evaluation of irregular arrays

CAPOZZOLI, AMEDEO;CURCIO, CLAUDIO;D'ELIA, GIUSEPPE;LISENO, ANGELO;VINETTI, PIETRO
2010

Abstract

An approach for the fast analysis of "irregular", i.e., of conformal, periodic or aperiodic, 2D arrays, based on the use of the p-series approach and Non-Uniform FFT (NUFFT) routines is proposed. The approach allows for modulating the computational burden depending on the array curvature and, thanks to the use of the NUFFT, the asymptotic growth of the computing time reduces to that of a few, standard FFTs. A sub-array partition strategy is also sketched and shown to further unburden the procedure and control the accuracy. The approach has been implemented in both sequential and parallel codes enabling its execution on CPUs and on cost-effective, massively parallel computing platforms like Graphic Processing Units (GPUs). Its performance in terms of computational efficiency and accuracy has been assessed by an extensive numerical analysis and also against benchmarks provided by algorithms based on fast Matrix-Vector Multiplication routines.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11588/368287
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