DOI: https://doi.org/10.26089/NumMet.v16r116

Gradient methods for solving inverse gravimetry and magnetometry problems on the Uran supercomputer

Authors

  • E.N. Akimova
  • V.E. Misilov
  • A.F. Skurydina
  • A.I. Tretyakov

Keywords:

inverse gravimetry and magnetometry problems
parallel algorithms
gradient-type methods
multi-core and graphics processors

Abstract

A modified linearized steepest descent method with variable weight factors is proposed to solve three-dimensional structural inverse gravimetry and magnetometry problems of finding the interfaces between constant density or magnetization layers in a multilayer medium. A linearized conjugate gradient method and its modified version with weight factors for solving the gravimetry and magnetometry problems in a multilayer medium is constructed. On the basis of the modified gradient-type methods, a number of efficient parallel algorithms are numerically implemented on an Intel multi-core processor and NVIDIA GPUs. The developed parallel iterative algorithms are compared for a model problem in terms of the relative error, the number of iterations, and the execution time.

New computational technologies

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Published

2015-04-03

Issue

Vol. 16 (2015): Issue 1.

Section

Section 1. Numerical methods and applications

Author Biographies

E.N. Akimova

N.N. Krasovskii Institute of Mathematics and Mechanics of UB RAS (IMM UB RAS)
• Leading Researcher

V.E. Misilov

N.N. Krasovskii Institute of Mathematics and Mechanics of UB RAS (IMM UB RAS)
• PhD Student

A.F. Skurydina

N.N. Krasovskii Institute of Mathematics and Mechanics of UB RAS (IMM UB RAS)
• Lead Mathematician

A.I. Tretyakov

N.N. Krasovskii Institute of Mathematics and Mechanics of UB RAS (IMM UB RAS)
• Programmer

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