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Delayed difference scheme for large scale scientific simulations.

Dheevatsa Mudigere1, Sunil D Sherlekar1, Santosh Ansumali2

  • 1Parallel Computing Lab, Intel Labs, Bangalore 560103, India.

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|December 6, 2014
PubMed
Summary
This summary is machine-generated.

By adopting a delayed difference approach from nonlinear dynamics, this study significantly reduces computational time in scientific algorithms. The new method maintains comparable error and stability to existing techniques.

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Area of Science:

  • Computational Science
  • Nonlinear Dynamics
  • Statistical Mechanics

Background:

  • Modern heterogeneous computing environments exhibit complex nonlinear system behaviors.
  • Existing computational methods may not fully leverage the unique characteristics of these systems.

Purpose of the Study:

  • To introduce a novel computational approach inspired by nonlinear dynamics and statistical mechanics.
  • To reduce the sequential fraction of scientific computing algorithms.
  • To analyze the error and stability of the proposed method.

Main Methods:

  • Applying the concept of time-scale separation.
  • Replacing traditional difference equations with a delayed difference equations approach.
  • Conducting comprehensive theoretical analysis for error and stability.

Main Results:

  • Substantial reduction in the sequential fraction of scientific computing algorithms.
  • Demonstrated error and stability comparable to existing schemes.
  • Validation for a broad class of well-characterized problems.

Conclusions:

  • The delayed difference approach offers a more efficient method for scientific computing in nonlinear systems.
  • This technique provides a robust alternative with equivalent performance in terms of error and stability.
  • The findings have implications for optimizing complex computational tasks.