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CDASH : a cloud‐enabled program for structure solution from powder diffraction data
Author(s) -
Spillman Mark J.,
Shankland Kenneth,
Williams Adrian C.,
Cole Jason C.
Publication year - 2015
Publication title -
journal of applied crystallography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.429
H-Index - 162
ISSN - 1600-5767
DOI - 10.1107/s160057671502049x
Subject(s) - cloud computing , computer science , scalability , computational science , dash , diffraction , parallel computing , parallelism (grammar) , database , operating system , physics , optics
The simulated annealing approach to crystal structure determination from powder diffraction data, as implemented in the DASH program, is readily amenable to parallelization at the individual run level. Very large scale increases in speed of execution can be achieved by distributing individual DASH runs over a network of computers. The CDASH program delivers this by using scalable on‐demand computing clusters built on the Amazon Elastic Compute Cloud service. By way of example, a 360 vCPU cluster returned the crystal structure of racemic ornidazole ( Z ′ = 3, 30 degrees of freedom) ca 40 times faster than a typical modern quad‐core desktop CPU. Whilst used here specifically for DASH , this approach is of general applicability to other packages that are amenable to coarse‐grained parallelism strategies.