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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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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.