The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/.

/pdf/ucsf-chimera-a-visualization-system-for-exploratory-research-59xu54fhxg.pdf

UCSF Chimera--a visualization system for exploratory research and analysis.

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

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.

/pdf/scalable-molecular-dynamics-with-namd-51o1z7rwp8.pdf

Scalable molecular dynamics with NAMD

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

Scalable Molecular Dynamics with NAMD

We describe the development, current features, and some directions for future development of the Amber package of computer programs. This package evolved from a program that was constructed in the late 1970s to do Assisted Model Building with Energy Refinement, and now contains a group of programs embodying a number of powerful tools of modern computational chemistry, focused on molecular dynamics and free energy calculations of proteins, nucleic acids, and carbohydrates.

/pdf/the-amber-biomolecular-simulation-programs-e2nyq1ef44.pdf

The Amber biomolecular simulation programs

NAMD2: Greater Scalability for Parallel Molecular Dynamics

Many parallel scientific applications have dynamic and irregular computational structure. However, most such applications exhibit persistence of computational load and communication structure. This allows us to embed measurement-based automatic load balancing framework in run-time systems of parallel languages that are used to build such applications. In this paper, we describe such a framework built for the Converse [4] in teroperable runtime system. This framework is composed of mechanisms for recording application performance data, a mechanism for object migration, and interfaces for plug-in load balancing strategy objects. In terfaces for strategy objects allow easy implementation of novel load balancing strategies that could use application characteristics on the entire machine, or only a local neighborhood. We present the performance of a few strategies on a synthetic benchmark and also the impact of automatic load balancing on an actual application.

Run-Time Support for Adaptive Load Balancing

Synthetic nanopores have arisen as a convenient means of characterizing single molecules, with DNA being one of the most popular subjects. By applying an electric field, ions and charged biomolecules like DNA can be compelled to interact with, or translocate through, nanopores in thin membranes. The use of the nanopore method for characterizing nucleic acids gained initial momentum in 1996 with a landmark paper by Kasianowicz et al.

/pdf/modeling-transport-through-synthetic-nanopores-38sc5vjgcl.pdf

Modeling transport through synthetic nanopores

Desktop workstations represent a largely untapped source of computational power for parallel computing. Two of the main problems in utilizing these workstations are developing strategies for migrating load so that partially loaded workstations can contribute CPU cycles to the computation, and making dynamically migratable application programs easy to write. This paper describes object arrays, a construct which makes dynamically migratable applications easier to write, and a simple strategy for migrating load on a workstation cluster.

Adapting to load on workstation clusters

Parallel languages are tools for constructing efficient application programs, while reducing the required labor. In this light, using the most appropriate tool for each component of a complex system seems natural, resulting in multi-paradigm multilingual programming. The Converse system developed at Illinois addresses the issues involved in supporting multilingual applications. This paper describes the development of a large parallel application in Computational Biophysics from the point of view of multilingual programming. NAMD, a molecular dynamics program, is implemented using three different “paradigms”: Parallel message-driven objects, Message-Passing, and Multithreading. The issues faced in implementing such a system, and the advantages of multilingual approach are discussed. NAMD is already operational on many parallel machines. Some preliminary performance results are presented and the lessons learned from this experience are discussed.

Robert Brunner

Papers

NAMD2: Greater Scalability for Parallel Molecular Dynamics

Run-Time Support for Adaptive Load Balancing

Modeling transport through synthetic nanopores

Adapting to load on workstation clusters

NAMD: A Case Study in Multilingual Parallel Programming