scholarly journals On the numerical solution of chaotic dynamical systems using extend precision floating point arithmetic and very high order numerical methods

2011 ◽  
Vol 16 (3) ◽  
pp. 340-352 ◽  
Author(s):  
Scott A. Sarra ◽  
Clyde Meador

Multiple results in the literature exist that indicate that all computed solutions to chaotic dynamical systems are time-step dependent. That is, solutions with small but different time steps will decouple from each other after a certain (small) finite amount of simulation time. When using double precision floating point arithmetic time step independent solutions have been impossible to compute, no matter how accurate the numerical method. Taking the well-known Lorenz equations as an example, we examine the numerical solution of chaotic dynamical systems using very high order methods as well as extended precision floating point number systems. Time step independent solutions are obtained over a finite period of time. However even with a sixteenth order numerical method and with quad-double floating point numbers, there is a limit to this approach.

Author(s):  
Jack Dongarra ◽  
Laura Grigori ◽  
Nicholas J. Higham

A number of features of today’s high-performance computers make it challenging to exploit these machines fully for computational science. These include increasing core counts but stagnant clock frequencies; the high cost of data movement; use of accelerators (GPUs, FPGAs, coprocessors), making architectures increasingly heterogeneous; and multi- ple precisions of floating-point arithmetic, including half-precision. Moreover, as well as maximizing speed and accuracy, minimizing energy consumption is an important criterion. New generations of algorithms are needed to tackle these challenges. We discuss some approaches that we can take to develop numerical algorithms for high-performance computational science, with a view to exploiting the next generation of supercomputers. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.


2020 ◽  
Vol 39 (6) ◽  
pp. 1-16
Author(s):  
Gianmarco Cherchi ◽  
Marco Livesu ◽  
Riccardo Scateni ◽  
Marco Attene

1964 ◽  
Vol 7 (1) ◽  
pp. 10-13 ◽  
Author(s):  
Robert T. Gregory ◽  
James L. Raney

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