Parallel Scalable PDE Constrained Optimization Antenna Identification in Hyperthermia Cancer Treatment Planning

Date

2009-01-01

Author

SCHENK, Olaf
Manguoğlu, Murat
CHRİSTEN, Matthias
SATHE, Madan

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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.

Subject Keywords

General Computer Science

URI

https://hdl.handle.net/11511/35309

Journal

Computer Science Research and Development

DOI

https://doi.org/10.1007/s00450-009-0080-x

Collections

Department of Computer Engineering, Article

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Citation Formats

O. SCHENK, M. Manguoğlu, M. CHRİSTEN, and M. SATHE, “Parallel Scalable PDE Constrained Optimization Antenna Identification in Hyperthermia Cancer Treatment Planning,” Computer Science Research and Development, pp. 0–0, 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35309.