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UID:submissions.supercomputing.org_SC23_sess310_drs105@linklings.com
SUMMARY:High Performance Computing for Optimization of Radiation Therapy T
reatment Plans
DESCRIPTION:Doctoral Showcase, Posters\n\nFelix Liu (KTH Royal Institute o
f Technology, Sweden; Raysearch Laboratories)\n\nModern radiation therapy
relies heavily on computational methods to design optimal treatment plans
(control parameters for the treatment machine) for individual patients. Th
ese parameters are determined by constructing and solving a mathematical o
ptimization problem. Ultimately, the goal is to create treatment plans for
each patient such that a high dose is delivered to the tumor, while spari
ng surrounding healthy tissue as much as possible. Solving the optimizatio
n problem can be computationally expensive, as it requires both a method t
o compute the delivered dose in the patient and an algorithm to solve a (i
n general) constrained and nonlinear optimization problem.\n\nThe goal of
this thesis project has been to investigate the use of HPC hardware and me
thods to accelerate the computational workflow in radiation therapy treatm
ent planning. First, we propose two methods to bring the optimization to H
PC hardware using GPU acceleration and distributed computing for dose summ
ation and objective function calculation respectively. We show that our me
thods achieve competitive performance compared to state-of-the-art librari
es and scale well, up to the Amdahl’s law limit.\n\nThen, we investigate m
ethods to accelerate interior point methods, a popular algorithm for const
rained optimization. We investigate the use of iterative Krylov subspace l
inear solvers to solve Newton systems from interior point methods and show
that we can compute solutions in reasonable time for our problems, in spi
te of extreme ill-conditioning. This approach presents one avenue by which
constrained optimization solvers for radiation therapy could be ported to
GPU accelerators.\n\nTag: Applications\n\nRegistration Category: Tech Pro
gram Reg Pass\n\nSession Chairs: André Brinkmann (Johannes Gutenberg Unive
rsity Mainz) and Xubin He (Temple University, Department of Computer and I
nformation Sciences)
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