Parallel GPGPU Evaluation of Small Angle X-ray Scattering Profiles in a Markov Chain Monte Carlo Framework
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Parallel GPGPU Evaluation of Small Angle X-ray Scattering Profiles in a Markov Chain Monte Carlo Framework. / Antonov, Lubomir Dimitrov; Andreetta, Christian; Hamelryck, Thomas Wim.
Biomedical Engineering Systems and Technologies. red. / Joaquim Gabriel; Jan Schier; Sabine Van Huffel. Bind 357 Springer Science+Business Media, 2013. s. 222-235 (Communications in Computer and Information Science).Publikation: Bidrag til bog/antologi/rapport › Bidrag til bog/antologi › Forskning › fagfællebedømt
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TY - CHAP
T1 - Parallel GPGPU Evaluation of Small Angle X-ray Scattering Profiles in a Markov Chain Monte Carlo Framework
AU - Antonov, Lubomir Dimitrov
AU - Andreetta, Christian
AU - Hamelryck, Thomas Wim
N1 - Conference code: 5
PY - 2013
Y1 - 2013
N2 - Inference of protein structure from experimental data is of crucial interest in science, medicine and biotechnology. Low-resolution methods, such as small angle X-ray scattering (SAXS), play a major role in investigating important biological questions regarding the structure of proteins in solution.To infer protein structure from SAXS data, it is necessary to calculate the expected experimental observations given a protein structure, by making use of a so-called forward model. This calculation needs to be performed many times during a conformational search. Therefore, computational efficiency directly determines the complexity of the systems that can be explored.We present an efficient implementation of the forward model for SAXS with full hardware utilization of Graphics Processor Units (GPUs). The proposed algorithm is orders of magnitude faster than an efficient CPU implementation, and implements a caching procedure employed in the partial forward model evaluations within a Markov chain Monte Carlo framework.
AB - Inference of protein structure from experimental data is of crucial interest in science, medicine and biotechnology. Low-resolution methods, such as small angle X-ray scattering (SAXS), play a major role in investigating important biological questions regarding the structure of proteins in solution.To infer protein structure from SAXS data, it is necessary to calculate the expected experimental observations given a protein structure, by making use of a so-called forward model. This calculation needs to be performed many times during a conformational search. Therefore, computational efficiency directly determines the complexity of the systems that can be explored.We present an efficient implementation of the forward model for SAXS with full hardware utilization of Graphics Processor Units (GPUs). The proposed algorithm is orders of magnitude faster than an efficient CPU implementation, and implements a caching procedure employed in the partial forward model evaluations within a Markov chain Monte Carlo framework.
U2 - 10.1007/978-3-642-38256-7_15
DO - 10.1007/978-3-642-38256-7_15
M3 - Book chapter
SN - 978-3-642-38255-0
VL - 357
T3 - Communications in Computer and Information Science
SP - 222
EP - 235
BT - Biomedical Engineering Systems and Technologies
A2 - Gabriel, Joaquim
A2 - Schier, Jan
A2 - Huffel, Sabine Van
PB - Springer Science+Business Media
T2 - BIOSTEC 2012
Y2 - 2 February 2012 through 5 February 2012
ER -
ID: 43870343