Projects per year
Abstract
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, rang- ing 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 paral- lel 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, includ- ing GPUs from NVIDIA and AMD, Intel’s Xeon Phi and multi-core CPUs with SIMD instruction sets.
Original language | English |
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Pages (from-to) | 119-134 |
Number of pages | 16 |
Journal | International Journal of High Performance Computing Applications |
Volume | 29 |
Issue number | 2 |
Early online date | 9 Apr 2014 |
DOIs | |
Publication status | Published - May 2015 |
Bibliographical note
BUDE is now one of the fastest HPC applications ever developed, and also one of the most performance portable ever reported in the literature, sustaining over 40% of peak performance across a diverse range of many-core computer architectures, such as GPUs, Xeon Phi, and even multi-core CPUs with wide vector instructions.Keywords
- molecular docking
- in silico virtual drug screening,
- many-core
- GPU
- OpenCL
- performance portability
Fingerprint
Dive into the research topics of 'High performance in silico virtual drug screening on many-core processors'. Together they form a unique fingerprint.Projects
- 1 Finished
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Development of Molecular Docking Software utilising GPGPU's
Sessions, R. B. (Principal Investigator)
1/09/12 → 1/03/14
Project: Research
Equipment
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HPC (High Performance Computing) and HTC (High Throughput Computing) Facilities
Alam, S. R. (Manager), Williams, D. A. G. (Manager), Eccleston, P. E. (Manager) & Greene, D. (Manager)
Facility/equipment: Facility
Profiles
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Professor Simon N McIntosh-Smith
- School of Computer Science - Professor in High Performance Computing
- Microelectronics
Person: Academic , Group lead