Parameter scan of an effective group difference pseudopotential using grid computing

被引:17
作者
Sudholt, W
Baldridge, KK
Abramson, D
Enticott, C
Garic, S
机构
[1] Univ Calif San Diego, Dept Chem & Biochem, La Jolla, CA 92093 USA
[2] Univ Calif San Diego, San Diego Supercomp Ctr, La Jolla, CA 92093 USA
[3] Monash Univ, Sch Comp Sci & Software Engn, Clayton, Vic 3800, Australia
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
grid computing; distributed parametric modeling; QM/MM methods; pseudopotentials;
D O I
10.1007/BF03040952
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Computational modeling in the health sciences is still very challenging and much of the success has been despite the difficulties involved in integrating all of the technologies, software, and other tools necessary to answer complex questions. Very large-scale problems are open to questions of spatio-temporal scale, and whether physico-chemical complexity is matched by biological complexity. For example, for many reasons, many large-scale biomedical computations today still tend to use rather simplified physics/chemistry compared with the state of knowledge of the actual biology/biochemistry. The ability to invoke modern grid technologies offers the ability to create new paradigms for computing, enabling access of resources which facilitate spanning the biological scale.
引用
收藏
页码:137 / 146
页数:10
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