8984

Acceleration of the MMFF94 routines within OpenBabel using Eigen and OpenCL

Omar Valerio Minero
The University of Edinburgh – EPCC
The University of Edinburgh, 2012
@phdthesis{minero2012acceleration,

   title={Acceleration of the MMFF94 routines within OpenBabel using Eigen and OpenCL},

   author={Minero, Omar Valerio},

   year={2012}

}

Download Download (PDF)   View View   Source Source   Source codes Source codes

Package:

523

views

Over the last few decades, computer modelling and computer simulation have become an invaluable tool for computational chemists interested in advancing their research and experiment in a more efficient, cost effective way with new molecules. As computer capabilities increase the demand for more accurate models and faster simulations has also grown. Some of these models have proved more successful than others with regards to their predictive power, and therefore experienced widespread adoption and support. One of these models in particular, the Merck Molecular Forcefield 94 (MMFF94), has been chosen as a study research subject for this work. The MMFF94 model and its parallelization using multicore and GPU technologies is presented in this work, using as a study frame, the implementation provided in OpenBabel, an open source cheminformatics software, that uses MMFF94 internally to compute the energy of a molecule, among other applications. The work dissects OpenBabel MMFF94 implementation with respect to its parallelization, proposes a software architecture to test and compare between single-threaded, multicore and GPUparallelized versions of MMFF94. Implementation and benchmarking were carried out for Eigen, OpenMP and OpenCL. Results of the benchmarking are discussed in the context of three different applications within OpenBabel: obenergy, obminimize and obconformer. Each of these applications scaling properties are presented together with a discussion on bottlenecks and implementation drawbacks with regard to their parallelization. In the only case where an application performance gain has been achieved (obconformer), the enabling code has been contributed back to the OpenBabel project.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

184 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1311 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: