Better chemistry through parallel in time algorithms

March 17, 2014
New parallel in time algorithms speed up high-level molecular dynamics simulations to enable predictions involving the properties of complex materials.

Molecular dynamics simulations often take too long to be practical for simulating chemical processes that occur on long timescales. Scientists DOE's Pacific Northwest National Laboratory, the University of Chicago, and the University of California at San Diego showed that time integration algorithms working in parallel can significantly speed up computationally demanding molecular dynamics simulations, opening new avenues for studying complex, long-lasting processes as diverse as carbon sequestration and energy production and storage.

Molecular dynamics simulations provide valuable data about the physical movements and interactions of atoms and molecules over time. Unlike classical approaches, ab initio (AIMD) simulations accurately calculate the movements of electrons, enabling scientists to study reactions that involve breaking or forming covalent bonds. Although AIMD simulations are useful in areas such as industrial and biological catalysis, their use is limited because they are computationally costly.

More time-efficient simulations have been made possible by massively parallel supercomputers and parallel algorithms, which distribute the computational workload across different processors or computers. Still, AIMD approaches currently take several months to simulate events that span picoseconds, even though many important chemical processes take much longer.

To address this problem, the researchers tested several parallel algorithms that distribute computations for different time intervals of a chemical event to different processors. These parallel in time algorithms sped up a conventional of 1,000 silicon atoms by a factor of 3. They also sped up a challenging AIMD simulation of an atmospherically important chemical reaction involving hydrochloric acid by a factor of 14. When the AIMD of this chemical process was done on the massively parallel supercomputer, the use of parallel in time algorithms compared with sequential algorithms reduced the duration of each computational time step from 32 to 7 seconds. Computing resources were used at the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the DOE's Office of Biological and Environmental Research, and the National Energy Research Scientific Computing Center.

The parallel in time algorithms are suitable for cloud computing. The speedup provided by these algorithms occurred even when they were implemented on machines connected by very slow networks. Moreover, these algorithms can be implemented using scripting languages, as well as standard quantum chemistry packages. Taken together, the findings demonstrate that parallel in time algorithms can allow researchers to use powerful AIMD simulations to study realistic and complex that take place on long timescales.

Explore further: Parallel in time algorithms enable simulation of long-lasting chemical processes

More information: Bylaska EJ, JQ Weare, and JH Weare. 2013. "Extending molecular simulation time scales: Parallel in time integrations for high-level quantum chemistry and complex force representations." Journal of Chemical Physics 139(7):074114. DOI: 10.1063/1.4818328.

Related Stories

Scaling Goes eXtreme: Researchers reach 34K CPUs

May 25, 2010

(PhysOrg.com) -- Currently, researchers have demonstrated the scalability of high-level excited-state coupled-cluster approaches and parallel-in-time algorithms, reaching a staggering 34,000 Core Processing Units.  Researchers ...

Learning molecular models from data

January 14, 2014

Dr. Heinz Koeppl is part of a new team of scientists at IBM's Zurich research lab focused on systems biology and he is not afraid to claim that one day, soon, advanced biological processes, like cell mitosis, will be represented ...

Recommended for you

Scientific advances can make it easier to recycle plastics

November 17, 2017

Most of the 150 million tons of plastics produced around the world every year end up in landfills, the oceans and elsewhere. Less than 9 percent of plastics are recycled in the United States, rising to about 30 percent in ...

The spliceosome—now available in high definition

November 17, 2017

UCLA researchers have solved the high-resolution structure of a massive cellular machine, the spliceosome, filling the last major gap in our understanding of the RNA splicing process that was previously unclear.

Ionic 'solar cell' could provide on-demand water desalination

November 15, 2017

Modern solar cells, which use energy from light to generate electrons and holes that are then transported out of semiconducting materials and into external circuits for human use, have existed in one form or another for over ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.