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Showing papers by "Erik Lindahl published in 2015"


Journal ArticleDOI
TL;DR: GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules, and provides a rich set of calculation types.

12,985 citations


Book ChapterDOI
01 Jan 2015
TL;DR: GROMACS as mentioned in this paper is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest supercomputers in the world.
Abstract: GROMACS is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest supercomputers in the world. Here, we describe some of the ways we have been able to realize this through the use of parallelization on all levels, combined with a constant focus on absolute performance. Release 4.6 of GROMACS uses SIMD acceleration on a wide range of architectures, GPU offloading acceleration, and both OpenMP and MPI parallelism within and between nodes, respectively. The recent work on acceleration made it necessary to revisit the fundamental algorithms of molecular simulation, including the concept of neighborsearching, and we discuss the present and future challenges we see for exascale simulation - in particular a very fine-grained task parallelism. We also discuss the software management, code peer review and continuous integration testing required for a project of this complexity.

726 citations


Book ChapterDOI
TL;DR: GROMACS as discussed by the authors is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest supercomputers in the world.
Abstract: GROMACS is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest supercomputers in the world. Here, we describe some of the ways we have been able to realize this through the use of parallelization on all levels, combined with a constant focus on absolute performance. Release 4.6 of GROMACS uses SIMD acceleration on a wide range of architectures, GPU offloading acceleration, and both OpenMP and MPI parallelism within and between nodes, respectively. The recent work on acceleration made it necessary to revisit the fundamental algorithms of molecular simulation, including the concept of neighborsearching, and we discuss the present and future challenges we see for exascale simulation - in particular a very fine-grained task parallelism. We also discuss the software management, code peer review and continuous integration testing required for a project of this complexity.

403 citations


Journal ArticleDOI
TL;DR: A new way to correct for these approximations to achieve exact treatment of Lorentz-Berthelot combination rules within the cutoff is presented, and only a very small approximation error remains outside the cutoff.
Abstract: Long-range lattice summation techniques such as the particle-mesh Ewald (PME) algorithm for electrostatics have been revolutionary to the precision and accuracy of molecular simulations in general. Despite the performance penalty associated with lattice summation electrostatics, few biomolecular simulations today are performed without it. There are increasingly strong arguments for moving in the same direction for Lennard-Jones (LJ) interactions, and by using geometric approximations of the combination rules in reciprocal space, we have been able to make a very high-performance implementation available in GROMACS. Here, we present a new way to correct for these approximations to achieve exact treatment of Lorentz-Berthelot combination rules within the cutoff, and only a very small approximation error remains outside the cutoff (a part that would be completely ignored without LJ-PME). This not only improves accuracy by almost an order of magnitude but also achieves absolute biomolecular simulation performance that is an order of magnitude faster than any other available lattice summation technique for LJ interactions. The implementation includes both CPU and GPU acceleration, and its combination with improved scaling LJ-PME simulations now provides performance close to the truncated potential methods in GROMACS but with much higher accuracy.

98 citations


Journal ArticleDOI
TL;DR: A new framework is presented that enables fully automated generation of GROMACS topologies for any of these force fields and an automated setup for parallel adaptive optimization of high-throughput free energy calculation by adjusting lambda point placement on the fly.
Abstract: Free energy calculation has long been an important goal for molecular dynamics simulation and force field development, but historically it has been challenged by limited performance, accuracy, and creation of topologies for arbitrary small molecules. This has made it difficult to systematically compare different sets of parameters to improve existing force fields, but in the past few years several authors have developed increasingly automated procedures to generate parameters for force fields such as Amber, CHARMM, and OPLS. Here, we present a new framework that enables fully automated generation of GROMACS topologies for any of these force fields and an automated setup for parallel adaptive optimization of high-throughput free energy calculation by adjusting lambda point placement on the fly. As a small example of this automated pipeline, we have calculated solvation free energies of 50 different small molecules using the GAFF, OPLS-AA, and CGenFF force fields and four different water models, and by incl...

87 citations


Journal ArticleDOI
TL;DR: This work describes how the distributed execution framework Copernicus allows the expression of algorithms such as free-energy perturbation, Markov state modeling, metadynamics, or milestoning in generic workflows: dataflow programs and facilitates the optimization of these algorithms with adaptive sampling.
Abstract: Computational chemistry and other simulation fields are critically dependent on computing resources, but few problems scale efficiently to the hundreds of thousands of processors available in current supercomputers-particularly for molecular dynamics. This has turned into a bottleneck as new hardware generations primarily provide more processing units rather than making individual units much faster, which simulation applications are addressing by increasingly focusing on sampling with algorithms such as free-energy perturbation, Markov state modeling, metadynamics, or milestoning. All these rely on combining results from multiple simulations into a single observation. They are potentially powerful approaches that aim to predict experimental observables directly, but this comes at the expense of added complexity in selecting sampling strategies and keeping track of dozens to thousands of simulations and their dependencies. Here, we describe how the distributed execution framework Copernicus allows the expression of such algorithms in generic workflows: dataflow programs. Because dataflow algorithms explicitly state dependencies of each constituent part, algorithms only need to be described on conceptual level, after which the execution is maximally parallel. The fully automated execution facilitates the optimization of these algorithms with adaptive sampling, where undersampled regions are automatically detected and targeted without user intervention. We show how several such algorithms can be formulated for computational chemistry problems, and how they are executed efficiently with many loosely coupled simulations using either distributed or parallel resources with Copernicus.

50 citations


Journal ArticleDOI
TL;DR: A bias-exchange metadynamics refinement protocol is presented that incorporates SAXS data as collective variables and therefore tags all possible configurations with their corresponding free energies, which allows identification of a unique structural solution.
Abstract: The small-angle X-ray scattering (SAXS) methodology enables structural characterization of biological macromolecules in solution. However, because SAXS provides low-dimensional information, several potential structural configurations can reproduce the experimental scattering profile, which severely complicates the structural refinement process. Here, we present a bias-exchange metadynamics refinement protocol that incorporates SAXS data as collective variables and therefore tags all possible configurations with their corresponding free energies, which allows identification of a unique structural solution. The method has been implemented in PLUMED and combined with the GROMACS simulation package, and as a proof of principle, we explore the Trp-cage protein folding landscape.

44 citations


Journal ArticleDOI
TL;DR: Structural and dynamic components of the conformational gating are identified in the eukaryotic glutamate-gated chloride channel by means of molecular dynamics simulations with and without the l-glutamate agonist bound, and changes in the transmembrane domain alter the free energy of ion passage.
Abstract: Cys-loop receptors are central to propagation of signals in the nervous system. The gating of the membrane-spanning pore is triggered by structural rearrangements in the agonist-binding site, locat ...

19 citations


Journal ArticleDOI
TL;DR: This work has used molecular dynamics simulations to examine how lipid and water dynamics are affected as two lipid bilayers approach each other, and shows that the water dynamics become glassy, and diffusion of lipids in the apposed leaflets becomes coupled across the water layer, while the “outer” leaflets remain unaffected.
Abstract: Biomembrane interfaces create regions of slowed water dynamics in their vicinity. When two lipid bilayers come together, this effect is further accentuated, and the associated slowdown can affect the dynamics of larger-scale processes such as membrane fusion. We have used molecular dynamics simulations to examine how lipid and water dynamics are affected as two lipid bilayers approach each other. These two interacting fluid systems, lipid and water, both slow and become coupled when the lipid membranes are separated by a thin water layer. We show in particular that the water dynamics become glassy, and diffusion of lipids in the apposed leaflets becomes coupled across the water layer, while the “outer” leaflets remain unaffected. This dynamic coupling between bilayers appears mediated by lipid–water–lipid hydrogen bonding, as it occurs at bilayer separations where water–lipid hydrogen bonds become more common than water–water hydrogen bonds. We further show that such coupling occurs in simulations of vesi...

17 citations


Journal ArticleDOI
TL;DR: Pentameric ligand-gated ion channels are heavily implicated in neurological effects of alcohol, yet high-resolution structural data in this family of receptors are limited.
Abstract: Pentameric ligand-gated ion channels are heavily implicated in neurological effects of alcohol, yet high-resolution structural data in this family of receptors are limited. The prokaryotic ligand-gated ion channel GLIC is a potentially valuable model system whose structure …

1 citations