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Parallel scalable PDE-constrained optimization: antenna identification in hyperthermia cancer treatment planning

  • Olaf Schenk
  • Murat Manguoglu
  • Ahmed Sameh
  • Matthias Christen
  • Madan Sathe
Special Issue Paper

Abstract

We present a PDE-constrained optimization algorithm which is designed for parallel scalability on distributed-memory architectures with thousands of cores. The method is based on a line-search interior-point algorithm for large-scale continuous optimization, it is matrix-free in that it does not require the factorization of derivative matrices. Instead, it uses a new parallel and robust iterative linear solver on distributed-memory architectures. We will show almost linear parallel scalability results for the complete optimization problem, which is a new emerging important biomedical application and is related to antenna identification in hyperthermia cancer treatment planning.

Keywords

PDE-constrained optimization   Large-scale parallel optimization  Biomedical application  Saddle-point matrices  Sparse liner solver 

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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Olaf Schenk
    • 1
  • Murat Manguoglu
    • 2
  • Ahmed Sameh
    • 2
  • Matthias Christen
    • 1
  • Madan Sathe
    • 1
  1. 1.Computer Science DepartmentUniversity of BaselBaselSwitzerland
  2. 2.Computer SciencesUniversity of PurdueWest LafayetteUSA

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