Parallel GPGPU Evaluation of Small Angle X-ray Scattering Profiles in a Markov Chain Monte Carlo Framework

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Standard

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. ed. / Joaquim Gabriel; Jan Schier; Sabine Van Huffel. Vol. 357 Springer Science+Business Media, 2013. p. 222-235 (Communications in Computer and Information Science).

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Harvard

Antonov, LD, Andreetta, C & Hamelryck, TW 2013, Parallel GPGPU Evaluation of Small Angle X-ray Scattering Profiles in a Markov Chain Monte Carlo Framework. in J Gabriel, J Schier & SV Huffel (eds), Biomedical Engineering Systems and Technologies. vol. 357, Springer Science+Business Media, Communications in Computer and Information Science, pp. 222-235, BIOSTEC 2012, Algarve, Portugal, 02/02/2012. https://doi.org/10.1007/978-3-642-38256-7_15

APA

Antonov, L. D., Andreetta, C., & Hamelryck, T. W. (2013). Parallel GPGPU Evaluation of Small Angle X-ray Scattering Profiles in a Markov Chain Monte Carlo Framework. In J. Gabriel, J. Schier, & S. V. Huffel (Eds.), Biomedical Engineering Systems and Technologies (Vol. 357, pp. 222-235). Springer Science+Business Media. Communications in Computer and Information Science https://doi.org/10.1007/978-3-642-38256-7_15

Vancouver

Antonov LD, Andreetta C, Hamelryck TW. Parallel GPGPU Evaluation of Small Angle X-ray Scattering Profiles in a Markov Chain Monte Carlo Framework. In Gabriel J, Schier J, Huffel SV, editors, Biomedical Engineering Systems and Technologies. Vol. 357. Springer Science+Business Media. 2013. p. 222-235. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-642-38256-7_15

Author

Antonov, Lubomir Dimitrov ; Andreetta, Christian ; Hamelryck, Thomas Wim. / Parallel GPGPU Evaluation of Small Angle X-ray Scattering Profiles in a Markov Chain Monte Carlo Framework. Biomedical Engineering Systems and Technologies. editor / Joaquim Gabriel ; Jan Schier ; Sabine Van Huffel. Vol. 357 Springer Science+Business Media, 2013. pp. 222-235 (Communications in Computer and Information Science).

Bibtex

@inbook{0fbc5386f2a14537a07610b53a7482e5,
title = "Parallel GPGPU Evaluation of Small Angle X-ray Scattering Profiles in a Markov Chain Monte Carlo Framework",
abstract = "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.",
author = "Antonov, {Lubomir Dimitrov} and Christian Andreetta and Hamelryck, {Thomas Wim}",
year = "2013",
doi = "10.1007/978-3-642-38256-7_15",
language = "English",
isbn = "978-3-642-38255-0",
volume = "357",
series = "Communications in Computer and Information Science",
publisher = "Springer Science+Business Media",
pages = "222--235",
editor = "Joaquim Gabriel and Jan Schier and Huffel, {Sabine Van}",
booktitle = "Biomedical Engineering Systems and Technologies",
address = "Singapore",
note = "BIOSTEC 2012 : International Joint Conference on Biomedical Engineering Systems and Technologies ; Conference date: 02-02-2012 Through 05-02-2012",

}

RIS

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