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Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

Postal Subscription Code 80-970

2018 Impact Factor: 1.129

Front. Comput. Sci.    2010, Vol. 4 Issue (4) : 480-488    https://doi.org/10.1007/s11704-010-0120-5
Research articles
JASMIN: a parallel software infrastructure for scientific computing
Zeyao MO,Aiqing ZHANG,Xiaolin CAO,Qingkai LIU,Xiaowen XU,Hengbin AN,Wenbing PEI,Shaoping ZHU,
Laboratory of Computational Physics, High Performance Computing Center, Institute of Applied Physics and Computational Mathematics, Beijing 100088, China;
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Abstract The exponential growth of computer power in the last 10 years is now creating a great challenge for parallel programming toward achieving realistic performance in the field of scientific computing. To improve on the traditional program for numerical simulations of laser fusion in inertial confinement fusion (ICF), the Institute of Applied Physics and Computational Mathematics (IAPCM) initializes a software infrastructure named J Adaptive Structured Meshes applications INfrastructure (JASMIN) in 2004. The main objective of JASMIN is to accelerate the development of parallel programs for large scale simulations of complex applications on parallel computers. Now, JASMIN has released version 1.8 and has achieved its original objectives. Tens of parallel programs have been reconstructed or developed on thousands of processors. JASMIN promotes a new paradigm of parallel programming for scientific computing. In this paper, JASMIN is briefly introduced.
Keywords J Adaptive Structured Meshes applications INfrastructure (JASMIN)      parallel computing      scientific computing      
Issue Date: 05 December 2010
 Cite this article:   
Zeyao MO,Xiaolin CAO,Aiqing ZHANG, et al. JASMIN: a parallel software infrastructure for scientific computing[J]. Front. Comput. Sci., 2010, 4(4): 480-488.
 URL:  
https://academic.hep.com.cn/fcs/EN/10.1007/s11704-010-0120-5
https://academic.hep.com.cn/fcs/EN/Y2010/V4/I4/480
Dongarra J. The international top 500 list for computers. www.top500.org
Benioff M R, Lazowska E D. Reports of president's information technology advisory committee(PITAC), computational science: ensuringAmerica's competitiveness. June 2005
Lawrence Livermore national laboratory. LLNL computation directorate annual report 2007, UCRL-TR-402150. 2007
Dimitri F K. Advanced simulation & computing: the next ten years,a publication of the office of advanced simulation & computing, NNSA Defense Programs. 2009
Post D E, Votta L G. Computational science demands a new paradigm. Physics Today, 2005, 58(1): 35–41

doi: 10.1063/1.1881898
Sarkar V, Harrod W, Snavelg A Z. Software challenges in extremescale systems. Journal of Physics: ConferenceSeries, 2009, 180(1):012045

doi: 10.1088/1742-6596/180/1/012045
Zhu S. A brief report on scientific computing. Physics, 2009, 38(8): 545–551 (in Chinese)
Mo Z, Pei W. Scientific computing application codes. Physics, 2009, 38(8): 552–558 (in Chinese)
Gropp W, Lusk E, Skjellum A. Using MPI: portable parallel programmingwith the message-passing interface. 2nd ed. Cambridge: MIT Press, 1999
Dongarra J, Luszczek P, Petitet A. The LINPACK benchmark: past,present, and future. Concurrency (Chichester,England), 2003, 15(9): 803–820
www.iwr.uni-hdidelberg.de/groups/techsim, May 31, 2010
ASMIN, Technical Report No.T09-JMJL-01, 2009. Mo Z, Zhang A, Wittum G. Scalable heuristic algorithms for theparallel execution of data flow acyclic digraphs. SIAM Journal on Scientific Computing, 2009, 31(5): 3626–3642

doi: 10.1137/050634554
Karypis G, Kumar V. Graph partitioningtechniques for high performance scientific simulations. In: Dongarra J, Foster I, Fox J, et al, eds. Sourcebook of Parallel Computing. San Francisco: Morgan Kaufmann Publisher, 2003
Mo Z, Zhang B. Multilevel averaging weight method for dynamic load imbalance problems. International Journal of Computer Mathematics, 2001, 76(4): 463–477

doi: 10.1080/00207160108805040
Pei W. The construction of simulation algorithms for Laser Fusion. Communication in Computational Physics, 2007, 2(2): 255–270
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