Abstract:

Diffraction, particularly of X-rays, is a powerful technique for the investigation of structure, microstructure and dynamical properties of matter. In order to link theoretical methods, like Molecular Dynamics and other atomistic approaches, and diffraction experiments we developed a new software for calculating the powder diffraction pattern of nano-sized objects on the GPUs. The software, soon to be made available under GPL license, allows the use of GPUs on different hosts for a direct (brute-force) computation of the Debye scattering equation.

(L Geliso, C. L. Azanza Ricardo, M. Leoni and P. Scardi: “Real-space calculation of powder diffraction patterns on graphics processing units”, Journal of Applied Crystallography 43:647-653, 2010. [DOI])

Exploitation of novel computer architectures, such as general purpose GPUs, is allowing researchers to accelerate the realization of frontier models in particle-based simulation, by enabling an increase in the level of realism in the description of the particles and their interactions and increasing both the number of particles and the timescales simulated.

This one-day meeting focuses on the new and exciting area of the exploitation of GPUs and related technology in the area of biomolecular simulations.

In addition to a programme of national and international speakers in the field, there is the opportunity to present a poster on your research. Read the rest of this entry »

Abstract:

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks.

John E. Stone, David J. Hardy, Ivan S. Ufimtsev, and Klaus Schulten: “GPU-Accelerated Molecular Modeling Coming of Age”, Journal of Molecular Graphics and Modelling, Volume 29, Issue 2, September 2010, Pages 116-125. [DOI])

HOOMD-blue performs general-purpose particle dynamics simulations on a single workstation, taking advantage of NVIDIA GPUs to attain a level of performance equivalent to many cores on a fast cluster. Flexible and configurable, HOOMD-blue is currently being used for coarse-grained molecular mynamics simulations of nano-maertials, glasses, and surfactants, dissipative particle dynamics simulations (DPD) of polymers, and crystallization of metals.

HOOMD-blue 0.9.1 adds many new features. Highlights include:

• 10 to 50 percent faster performance over 0.9.0
• DPD (Dissipative Particle Dynamics) capability
• EAM (Embedded Atom Method) capability
• Removed limitation on number of exclusions
• Support for compute 2.1 devices (such as the GTX 460)
• Support for CUDA 3.1
• and more

HOOMD-blue 0.9.1 is available for download under an open source license. Check out the quick start tutorial to get started, or check out the full documentation to see everything it can do.

Simbios, the NIH Center for Biomedical Computation at Stanford University, is excited to announce the release of OPENMM 2.0.

OPENMM was designed to enhance the performance of almost any molecular dynamics simulation package (MD package) by allowing the code to be executed on high performance computer architectures, in particular Graphics Processing Units (GPUs). Most molecular dynamics packages can be modified to call OPENMM, resulting in significant acceleration on such high performance architectures, without changing the way users interact with the MD package. Read the rest of this entry »

Petapath, NVIDIA and Supermicro would like to invite researchers, students and industrial users to a series of free seminars and workshops dedicated to the Bio Workbench. The seminars will principally cover the use of AMBER 11′s CUDA-accelerated PMEMD (Particle Mesh Ewald Molecular Dynamics) tool but will be of interest to anyone using other molecular dynamics packages covered by the Bio Workbench.

Guest speakers include Ross Walker (SDSC) and Ian Gould (UCL) and currently there are two events being held in the UK, the 8th of July at Imperial College London and the 16th of July at The University of Manchester. Please visit www.petapath.com/nvidia to register.

GPU-Accelerated Ion Placement

The Theoretical and Computational Biophysics Group, NIH Resource for Macromolecular Modeling and Bioinformatics (www.ks.uiuc.edu) at the University of Illinois at Urbana-Champaign, presents a Workshop on GPU Programming for Molecular Modeling to be held August 6-8, 2010, at the Beckman Institute for Advanced Science and Technology, on the University of Illinois campus in Urbana, Illinois, USA. Application, selection, and notification of participants is on-going through July 29, 2010.

Note: Participants are encouraged to attend the multi-site “Proven Algorithmic Techniques for Many-core Processors” workshop the preceding week (August 2-6) at the location of their choice. Registration for this workshop is required for participants without equivalent GPU-programming training or experience.

HOOMD-blue stands for Highly Optimized Object-oriented Many-particle Dynamics — Blue Edition. It performs general-purpose particle dynamics simulations on a single workstation, taking advantage of  NVIDIA GPUs to attain a level of performance equivalent to dozens of processor cores on a fast cluster.

HOOMD-blue 0.9.0 is a major new release. Highlights include:

• Support for Fermi generation GPUs
• Performance enhancements
• New pair potentials
• Particle data is now accessible from hoomd scripts
• Binary format dump files for simulation restarts
• Numerous small enhancements to enable easily restartable jobs
• 2D simulations are now possible
• Integration methods can now be applied to specified groups of particles
• All IMD commands issued by VMD are now understood
• … and more

HOOMD-blue 0.9.0 is available for download under an open source license.

Molecular Workshop Series – Running and Developing MD Algorithms on GPUs with OpenMM and PyOpenMM + Intro to MD and Trajectory Analysis

Simbios is excited to announce its upcoming Molecular Dynamics (MD) Workshop Series, highlighting new capabilities within the recently released OpenMM 1.0 and introducing PyOpenMM for rapid MD code development with high performance:

Day 1: Running and Developing MD Algorithms on GPUs with OpenMM
Day 2: Introduction to MD and Trajectory Analysis with Markov State Models

When: March 1-2, 2010 (sign up for one or two days)
Where: Stanford University

Registration is free but required and spaces are limited. Please visit http://simbios.stanford.edu/MDWorkshops.htm for the workshop agenda and to register.

Occasionally, we receive news submissions pointing us to interesting older papers that somehow slipped by without our notice. This post collects a few of those. If you want your work to be posted on GPGPU.org  in a timely manner, please remember to use the news submission form.

• Joshua A. Anderson, Chris D. Lorenz and Alex Travesset present and discuss molecular dynamics simulations and compare a single GPU against a 36-CPU cluster (General purpose molecular dynamics simulations fully implemented on graphics processing units, Journal of Computational Physics 227(10), May 2008, DOI 10.1016/j.jcp.2008.01.047).
• Wen-mei Hwu et al. derive and discuss goals and concepts of programming models for fine-grained parallel architectures, from the point of view of both a programmer and a hardware /compiler designer, and analyze CUDA as one current representative  (Implicitly parallel programming models for thousand-core microprocessors, Proceedings of DAC’07, June 2007, DOI 10.1145/1278480.1278669).
• Jeremy Sugerman et al. present GRAMPS, a prototype implementation of future graphics hardware that allows pipelines to be specified as graphs in software (GRAMPS: A Programming Model for Graphics Pipelines, ACM Transactions on Graphics 28(1), January 2009, DOI 10.1145/1477926.1477930).
• William R. Mark discusses concepts of future graphics architectures in this contribution to the 2008 ACM Queue special issue on GPUs (Future graphics architectures, ACM Queue 6(2), March/April 2008,  DOI 10.1145/1365490.1365501).
• BSGP by Qiming Hou et al. is a new programming language for general purpose GPU computing that achieves the same efficiency as well-tuned CUDA programs but makes code much easier to read, develop and maintain (BSGP: bulk-synchronous GPU programming, ACM Siggraph 2008, August 2008, DOI 10.1145/1399504.1360618).
• Finally, Che et al. and Garland et al. survey the field of GPU computing and discuss many different application domains. These articles are, in addition to the ones we have collected on the developer pages, recommended to GPGPU newcomers.