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

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions Not only does this combination of a

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GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation

This article describes the software suite GROMACS (Groningen MAchine for Chemical Simulation) that was developed at the University of Groningen, The Netherlands, in the early 1990s. The software, written in ANSI C, originates from a parallel hardware project, and is well suited for parallelization on processor clusters. By careful optimization of neighbor searching and of inner loop performance, GROMACS is a very fast program for molecular dynamics simulation. It does not have a force field of its own, but is compatible with GROMOS, OPLS, AMBER, and ENCAD force fields. In addition, it can handle polarizable shell models and flexible constraints. The program is versatile, as force routines can be added by the user, tabulated functions can be specified, and analyses can be easily customized. Nonequilibrium dynamics and free energy determinations are incorporated. Interfaces with popular quantum-chemical packages (MOPAC, GAMES-UK, GAUSSIAN) are provided to perform mixed MM/QM simulations. The package includes about 100 utility and analysis programs. GROMACS is in the public domain and distributed (with source code and documentation) under the GNU General Public License. It is maintained by a group of developers from the Universities of Groningen, Uppsala, and Stockholm, and the Max Planck Institute for Polymer Research in Mainz. Its Web site is http://www.gromacs.org.

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GROMACS: Fast, flexible, and free

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

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

Introduction : Ligand-gated ion channels (LGICs) are thought to mediate a significant proportion of anesthetic effects. We built atomic level models of the glycine alpha one receptor (GlyRa1) to ex ...

Anesthetic Binding Sites in a GlyRa1 Model Based on Open State Prokaryotic Ion Channel Templates

Since 2010, the Swedish e-Science Research Centre (SeRC) is funding and coordinating e-Science activities in a broad spectrum of scientific disciplines. After an initial 5-year phase that produced outstanding results, SeRC is increasingly focusing on fostering interactions between disciplines and has created so-called Multidisciplinary Collaborative Programs (MCPs). In these programs, domain researchers collaborate with e-Science methods and tool developers and e-Infrastructure providers. In this paper we give an overview of the initial phase of SeRC and present the new programs that started operating in 2019.

The Future of Swedish e-Science: SeRC 2.0

The Swedish e-Science Research Centre (SeRC) The Swedish e-Science Research Centre (SeRC) is based on a collaboration between four Swedish universities: The KTH Royal Institute of Technology (KTH), Stockholm University (SU), Karolinska Institutet (KI) and Linköping University (LiU). SeRC’s mission statement is to develop state-of-the-art eScience tools and provide e-infrastructure support to existing and emerging e-Science research communities to help bring about scientific breakthroughs in Sweden. SeRC was founded in 2010 as the result of the Strategic Research Area (SRA) initiative launched by the Swedish Government Bill on Research Policy in 2008, where a total of 24 different strategic research areas were defined – one of which was e-Science. Initially SeRC was granted funding for 5 years. During those first 5 years, SeRC built up an organization for e-Science research, which has been highly successful. This was reflected in the excellent grades that SeRC received when the SRAs in Sweden were evaluated in 2015, and the fact that after this, SeRC received funding for at least 5 more years. This new phase of SeRC partly focuses on activities relating to emerging technologies (such as exascale systems and data-driven science) while also consolidating SeRC’s ongoing efforts in working towards a long-lasting e-Science environment in Sweden.

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e-Science in Scandinavia

System for supporting computational tasks in a computer network. The system comprises a dataflow network execution unit adapted to start the execution of a dataflow network program in response to a predefined set of input data being provided. The dataflow network is adapted to provide output from the execution of the dataflow network program.

Dynamic dataflow network

In the version of this Article originally published, the name of co-author Annemarie Perez Boerema was coded wrongly, resulting in it being incorrect when exported to citation databases. This has been corrected, though no visible changes will be apparent.

/pdf/publisher-correction-structure-of-the-chloroplast-ribosome-4a19oprbh2.pdf

Erik Lindahl

Papers

Anesthetic Binding Sites in a GlyRa1 Model Based on Open State Prokaryotic Ion Channel Templates

The Future of Swedish e-Science: SeRC 2.0

e-Science in Scandinavia

Dynamic dataflow network

Publisher Correction: Structure of the chloroplast ribosome with chl-RRF and hibernation-promoting factor.