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High performance in silico virtual drug screening on many-core processors
Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more comp...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4425459/ https://www.ncbi.nlm.nih.gov/pubmed/25972727 http://dx.doi.org/10.1177/1094342014528252 |
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author | McIntosh-Smith, Simon Price, James Sessions, Richard B Ibarra, Amaurys A |
author_facet | McIntosh-Smith, Simon Price, James Sessions, Richard B Ibarra, Amaurys A |
author_sort | McIntosh-Smith, Simon |
collection | PubMed |
description | Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more computationally intensive approaches, such as molecular docking. The latter simulates the binding of drug molecules to their targets, typically protein molecules. In this work, we describe BUDE, the Bristol University Docking Engine, which has been ported to the OpenCL industry standard parallel programming language in order to exploit the performance of modern many-core processors. Our highly optimized OpenCL implementation of BUDE sustains 1.43 TFLOP/s on a single Nvidia GTX 680 GPU, or 46% of peak performance. BUDE also exploits OpenCL to deliver effective performance portability across a broad spectrum of different computer architectures from different vendors, including GPUs from Nvidia and AMD, Intel’s Xeon Phi and multi-core CPUs with SIMD instruction sets. |
format | Online Article Text |
id | pubmed-4425459 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-44254592015-05-11 High performance in silico virtual drug screening on many-core processors McIntosh-Smith, Simon Price, James Sessions, Richard B Ibarra, Amaurys A Int J High Perform Comput Appl Original Articles Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more computationally intensive approaches, such as molecular docking. The latter simulates the binding of drug molecules to their targets, typically protein molecules. In this work, we describe BUDE, the Bristol University Docking Engine, which has been ported to the OpenCL industry standard parallel programming language in order to exploit the performance of modern many-core processors. Our highly optimized OpenCL implementation of BUDE sustains 1.43 TFLOP/s on a single Nvidia GTX 680 GPU, or 46% of peak performance. BUDE also exploits OpenCL to deliver effective performance portability across a broad spectrum of different computer architectures from different vendors, including GPUs from Nvidia and AMD, Intel’s Xeon Phi and multi-core CPUs with SIMD instruction sets. SAGE Publications 2015-05 /pmc/articles/PMC4425459/ /pubmed/25972727 http://dx.doi.org/10.1177/1094342014528252 Text en © The Author(s) 2014 http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution 3.0 License (http://www.creativecommons.org/licenses/by/3.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (http://www.uk.sagepub.com/aboutus/openaccess.htm) |
spellingShingle | Original Articles McIntosh-Smith, Simon Price, James Sessions, Richard B Ibarra, Amaurys A High performance in silico virtual drug screening on many-core processors |
title | High performance in silico virtual drug screening on many-core processors |
title_full | High performance in silico virtual drug screening on many-core processors |
title_fullStr | High performance in silico virtual drug screening on many-core processors |
title_full_unstemmed | High performance in silico virtual drug screening on many-core processors |
title_short | High performance in silico virtual drug screening on many-core processors |
title_sort | high performance in silico virtual drug screening on many-core processors |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4425459/ https://www.ncbi.nlm.nih.gov/pubmed/25972727 http://dx.doi.org/10.1177/1094342014528252 |
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