High performance in silico virtual drug screening on many-core processors

Simon N McIntosh-Smith, James R Price, Richard B Sessions, Amaurys Avila Ibarra

Research output: Contribution to journalArticle (Academic Journal)peer-review

77 Citations (Scopus)
622 Downloads (Pure)


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 languageEnglish
Pages (from-to)119-134
Number of pages16
JournalInternational Journal of High Performance Computing Applications
Issue number2
Early online date9 Apr 2014
Publication statusPublished - 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.


  • molecular docking
  • in silico virtual drug screening,
  • many-core
  • GPU
  • OpenCL
  • performance portability


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