https://www.sandia.gov/~sjplimp/papers/jcompphys95.pdf

Fast parallel algorithms for short-range molecular dynamics

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.

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

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

Scalable Molecular Dynamics with NAMD

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

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

The surface micromachining processes used to manufacture MEMS devices and integrated circuits transpire at such small length scales and are sufficiently complex that a theoretical analysis of them is particularly inviting. Under development at Sandia National Laboratories (SNL) is Chemically Induced Surface Evolution with Level Sets (ChISELS), a level-set based feature-scale modeler of such processes. The theoretical models used, a description of the software and some example results are presented here. The focus to date has been of low-pressure and plasma enhanced chemical vapor deposition (low-pressure chemical vapor deposition, LPCVD and PECVD) processes. Both are employed in SNLs SUMMiT V technology. Examples of step coverage of SiO{sub 2} into a trench by each of the LPCVD and PECVD process are presented.

Feature length-scale modeling of LPCVD & PECVD MEMS fabrication processes.

Molecular dynamics (MD) simulations were carried out on a blend of 50 unit, pearl-necklace chains with the object of examining the effect of intermolecular attractions on the blend structure and thermodynamics. Repulsive interactions were imposed between intermolecular sites so that the effective hard core diameter of B type chains was 1.2 times that of the A type chains. Simulations were performed for a series of runs in which the attractive interactions were systematically varied from zero to the full Lennard-Jones value. Examination of the radial distribution functions revealed that the attractive interactions had very little effect on the blend structure up to the point of phase separation. Furthermore, we found that perturbation theory accurately predicted the changes in pressure associated with the variations in the attractive strengths.

The effect of attractions on the structure and thermodynamics of model polymer blends

Summary form only given. QUICKSILVER is a 3-D electromagnetic particle-in-cell simulation code developed and used at Sandia to model relativistic charged particle transport. It was originally written for shared-memory, multi-processor supercomputers such as the Cray X/MP. A new parallel version of QUICKSILVER has been developed to enable large-scale simulations to be efficiently run on massively-parallel distributed memory supercomputers with thousands of processors, such as the Intel Tflops and Cplant machines at Sandia. The new parallel code implements all the features of the original QUICKSILVER and can be run on any platform that supports the message-passing interface (MPI) standard as well as on single-processor workstations. The original QUICKSILVER code was based on a multiple-block grid, which provided a natural strategy for extending the code to partition a simulation among multiple processors. By adding the automated capability to divide QUICKSILVER's existing blocks into sub-blocks and then distribute those sub-blocks among processors, a simulation's spatial domain can be easily and efficiently partitioned. Based upon this partitioning scheme as well as QUICKSILVER's existing particle-handling infrastructure, an algorithm has been developed for dynamically rebalancing the particle workload on a timestep-by-timestep basis that has proven to be very efficient. This paper will elaborate on the strategies used and describe the algorithms developed to parallelize and dynamically load-balance the code. Results of several benchmark simulations will be presented that illustrate the code's performance and parallel efficiency for a wide variety of simulation conditions. These calculations have as many as 10/sup 8/ grid cells and 10/sup 9/ particles and were run on thousands of processors.

Dynamic load-balancing for a parallel electromagnetic particle-in-cell code

In finite-element, transient dynamics simulations, physical objects are typically modeled as Lagrangian meshes because the meshes can move and deform with the objects as they undergo stress. In many simulations, such as computations of impacts or explosions, portions of the deforming mesh come in contact with each other as the simulation progresses. These contacts must be detected and the forces they impart to the mesh must be computed at each timestep to accurately capture the physics of interest. While the finite-element portion of these computations is readily parallelized, the contact detection problem is difficult to implement efficiently on parallel computers and has been a bottleneck to achieving high performance on large parallel machines. In this paper we describe a new parallel algorithm for detecting contacts. Our approach differs from previous work in that we use two different parallel decompositions, a static one for the finite element analysis and dynamic one for contact detection. We present results for this algorithm in a parallel version of the transient dynamics code PRONTO-3D running on a large Intel Paragon.

/pdf/a-new-parallel-algorithm-for-contact-detection-in-finite-14pn1g1b18.pdf

A new parallel algorithm for contact detection in finite element methods

The surface micromachining processes used to manufacture MEMS devices and integrated circuits transpire at such small length scales and are sufficiently complex that a theoretical analysis of them is particularly inviting. Under development at Sandia National Laboratories (SNL) is Chemically Induced Surface Evolution with Level Sets (ChISELS), a level-set based feature-scale modeler of such processes. The theoretical models used, a description of the software and some example results are presented here. The focus to date has been of low-pressure and plasma enhanced chemical vapor deposition (low-pressure chemical vapor deposition, LPCVD and PECVD) processes. Both are employed in SNLs SUMMiT V technology. Examples of step coverage of SiO2 into a trench by each of the LPCVD and PECVD process are presented.

http://www.sandia.gov/~sjplimp/papers/jmt05.pdf

Steven J. Plimpton

Papers

Feature length-scale modeling of LPCVD & PECVD MEMS fabrication processes.

The effect of attractions on the structure and thermodynamics of model polymer blends

Dynamic load-balancing for a parallel electromagnetic particle-in-cell code

A new parallel algorithm for contact detection in finite element methods

Feature length-scale modeling of LPCVD and PECVD MEMS fabrication processes