Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

http://kth.diva-portal.org/smash/get/diva2:1303357/FULLTEXT01

GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecu- lar simulation program. It has been developed over the last three decades with a primary focus on molecules of bio- logical interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estima- tors, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numer- ous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.

/pdf/charmm-the-biomolecular-simulation-program-4kexem0xkx.pdf

CHARMM: the biomolecular simulation program.

Motivation: Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources.

Results: Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.

Availability: GROMACS is an open source and free software available from http://www.gromacs.org.

Contact: erik.lindahl@scilifelab.se

Supplementary information:Supplementary data are available at Bioinformatics online.

Gromacs 4.5

The widely used CHARMM additive all-atom force field includes parameters for proteins, nucleic acids, lipids, and carbohydrates. In the present article, an extension of the CHARMM force field to drug-like molecules is presented. The resulting CHARMM General Force Field (CGenFF) covers a wide range of chemical groups present in biomolecules and drug-like molecules, including a large number of heterocyclic scaffolds. The parametrization philosophy behind the force field focuses on quality at the expense of transferability, with the implementation concentrating on an extensible force field. Statistics related to the quality of the parametrization with a focus on experimental validation are presented. Additionally, the parametrization procedure, described fully in the present article in the context of the model systems, pyrrolidine, and 3-phenoxymethylpyrrolidine will allow users to readily extend the force field to chemical groups that are not explicitly covered in the force field as well as add functional groups to and link together molecules already available in the force field. CGenFF thus makes it possible to perform "all-CHARMM" simulations on drug-target interactions thereby extending the utility of CHARMM force fields to medicinally relevant systems.

/pdf/charmm-general-force-field-a-force-field-for-drug-like-4mhn8ejv47.pdf

CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields.

/pdf/scalable-molecular-dynamics-with-namd-3j7xyc70g4.pdf

Scalable Molecular Dynamics with NAMD

NAMD is a parallel molecular dynamics code designed for high‐performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high‐end parallel platforms, as well as tens of processors on low‐cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu. © 2005 Wiley Periodicals, Inc. J Comput Chem 26: 1781–1802, 2005

Scalable Molecular Dynamics with NAMD.

Existing media providers such as YouTube and Hulu deliver videos by turning it into a progressive download. This can result in frequent video freezes under varying network dynamics. In this paper, we present CloudStream: a cloud-based video proxy that can deliver high-quality streaming videos by transcoding the original video in real time to a scalable codec which allows streaming adaptation to network dynamics. The key is a multi-level transcoding parallelization framework with two mapping options (Hallsh-based Mapping and Lateness-first Mapping) that optimize transcoding speed and reduce the transcoding jitters while preserving the encoded video quality. We evaluate the performance of CloudStream on our campus cloud testbed.

/pdf/cloudstream-delivering-high-quality-streaming-videos-through-4qwptuffeb.pdf

CloudStream: Delivering high-quality streaming videos through a cloud-based SVC proxy

NAMD is a portable parallel application for biomolecular simulations. NAMD pioneered the use of hybrid spatial and force decomposition, a technique now used by most scalable programs for biomolecular simulations, including Blue Matter and Desmond developed by IBM and D. E. Shaw respectively. NAMD has been developed using Charm++ and benefits from its adaptive communication- computation overlap and dynamic load balancing. This paper focuses on new scalability challenges in biomolecular simulations: using much larger machines and simulating molecular systems with millions of atoms. We describe new techniques developed to overcome these challenges. Since our approach involves automatic adaptive runtime optimizations, one interesting issue involves dealing with harmful interaction between multiple adaptive strategies. NAMD runs on a wide variety of platforms, ranging from commodity clusters to supercomputers. It also scales to large machines: we present results for up to 65,536 processors on IBM's Blue Gene/L and 8,192 processors on Cray XT3/XT4. In addition, we present performance results on NCSA's Abe, SDSC's DataStar and TACC's LoneStar cluster, to demonstrate efficient portability. We also compare NAMD with Desmond and Blue Matter.

http://charm.cs.illinois.edu/newPapers/08-01/paper.pdf

Overcoming scaling challenges in biomolecular simulations across multiple platforms

A 100-million-atom biomolecular simulation with NAMD is one of the three benchmarks for the NSF-funded sustainable petascale machine. Simulating this large molecular system on a petascale machine presents great challenges, including handling I/O, large memory footprint and getting good strong-scaling results. In this paper, we present parallel I/O techniques to enable the simulation. A new SMP model is designed to efficiently utilize ubiquitous wide multicore clusters by extending the Charm++ asynchronous message-driven runtime. We exploit node-aware techniques to optimize both the application and the underlying SMP runtime. Hierarchical load balancing is further exploited to scale NAMD to the full Jaguar PF Cray XT5 (224,076 cores) at Oak Ridge National Laboratory, both with and without PME full electrostatics, achieving 93% parallel efficiency (vs 6720 cores) at 9 ms per step for a simple cutoff calculation. Excellent scaling is also obtained on 65,536 cores of the Intrepid Blue Gene/P at Argonne National Laboratory.

/pdf/enabling-and-scaling-biomolecular-simulations-of-100-million-ah5319lk5l.pdf

Chao Mei

Papers

Scalable Molecular Dynamics with NAMD

Scalable Molecular Dynamics with NAMD.

CloudStream: Delivering high-quality streaming videos through a cloud-based SVC proxy

Overcoming scaling challenges in biomolecular simulations across multiple platforms

Enabling and scaling biomolecular simulations of 100 million atoms on petascale machines with a multicore-optimized message-driven runtime