Enabling a Computational Mechanics Code for Massively Parallel Supercomputers

2013 ◽  
Author(s):  
X. Sáez ◽  
E. Casoni ◽  
G. Houzeaux ◽  
M. Vázquez ◽  
A. Jerusalem
Keyword(s):  
Computational Mechanics ◽  
Massively Parallel ◽  
Parallel Supercomputers

Monte Carlo shell model studies with massively parallel supercomputers

2017 ◽  
Vol 92 (6) ◽  
pp. 063001 ◽  
Author(s):  
Noritaka Shimizu ◽  
Takashi Abe ◽  
Michio Honma ◽  
Takaharu Otsuka ◽  
Tomoaki Togashi ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Shell Model ◽  
Massively Parallel ◽  
Model Studies ◽  
Monte Carlo Shell Model ◽  
Parallel Supercomputers

Massively parallel Monte Carlo simulations of images and analytical data for Electron Microscopy

1994 ◽  
Vol 52 ◽  
pp. 910-911
Author(s):  
A. D. Romig ◽  
J. R. Michael ◽  
S. J. Plimpton
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Analytical Data ◽  
Parallel Architecture ◽  
Thin Foil ◽  
Massively Parallel ◽  
Electron Trajectory ◽  
Monte Carlo Algorithms ◽  
Computational Speed ◽  
Parallel Supercomputers

Monte Carlo electron trajectory simulations have been adapted to run on massively parallel supercomputers. An nCUBE2 parallel supercomputer with 1024 processors has been used in these studies. The advantage of the parallel architecture is the great increase in computational speed and the fact that few changes in the standard serial Monte Carlo algorithms are required. The temporal performance of the massively parallel Monte Carlo electron trajectory simulation run on 1024 nodes has been compared with Monte Carlo codes run on other types of supercomputers (CRAY-YMP). It was found to be as much as 100 times faster than the CRAY-YMP and over 2000 times faster than a VAX 785. This increase in computational speed allows the exploration of problems, in particular those involving small probability events, which are not normally amenable to solution by traditional serial Monte Carlo simulations due tothe time intensive nature of the calculations. For example, the calculation of 1,000,000 electrons at 100 kV through a thin foil takes about 6 seconds on the nCUBE.

A MOLECULAR DYNAMICS RUN WITH 5 180 116 000 PARTICLES

2000 ◽  
Vol 11 (02) ◽  
pp. 317-322 ◽  
Author(s):  
J. ROTH ◽  
F. GÄHLER ◽  
H.-R. TREBIN
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Massively Parallel ◽  
Classical Molecular Dynamics ◽  
Dynamics Simulations ◽  
Parallel Supercomputers

We report on the development of IMD, a scalable program for classical molecular dynamics simulations on massively parallel supercomputers. New features like online-visualization and metacomputing are described.

scholarly journals Virtual Grid Engine: a simulated grid engine environment for large-scale supercomputers

2019 ◽  
Vol 20 (S16) ◽  
Author(s):  
Satoshi Ito ◽  
Masaaki Yadome ◽  
Tatsuo Nishiki ◽  
Shigeru Ishiduki ◽  
Hikaru Inoue ◽  
...  
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Massively Parallel ◽  
Scale Analysis ◽  
Large Scale Analysis ◽  
Scientific Results ◽  
Time Required ◽  
Parallel Supercomputers ◽  
Virtual Grid ◽  
Processing Service

Abstract Background Supercomputers have become indispensable infrastructures in science and industries. In particular, most state-of-the-art scientific results utilize massively parallel supercomputers ranked in TOP500. However, their use is still limited in the bioinformatics field due to the fundamental fact that the asynchronous parallel processing service of Grid Engine is not provided on them. To encourage the use of massively parallel supercomputers in bioinformatics, we developed middleware called Virtual Grid Engine, which enables software pipelines to automatically perform their tasks as MPI programs. Result We conducted basic tests to check the time required to assign jobs to workers by VGE. The results showed that the overhead of the employed algorithm was 246 microseconds and our software can manage thousands of jobs smoothly on the K computer. We also tried a practical test in the bioinformatics field. This test included two tasks, the split and BWA alignment of input FASTQ data. 25,055 nodes (2,000,440 cores) were used for this calculation and accomplished it in three hours. Conclusion We considered that there were four important requirements for this kind of software, non-privilege server program, multiple job handling, dependency control, and usability. We carefully designed and checked all requirements. And this software fulfilled all the requirements and achieved good performance in a large scale analysis.

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