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Despite advances in computer technology, computing in macromolecular crystallography keeps pace in its demand for CPU power. Improvements in CPU speed, together with advances in computing methods that depend on it, often translate into the possibility to solve structures that would otherwise require additional experiments. Programs for data reduction, molecular-replacement programs employing multidimensional searches on a grid in real, Patterson or reciprocal space, and phasing and refinement programs, currently have, among others, the highest requirements for CPU power. For these and other programs, speed-up of calculations as a result of parallel execution on multiprocessor computers is possible. This paper outlines the use of the OpenMP programming interface and reports its successful application for parallelization of ESSENS Kleywegt & Jones (1997). Acta Cryst. D 53 , 179–185 and SHELXL Schneider & Sheldrick (1997). Methods Enzymol . 277 , 319–343. Parallel computing, which is possible as a result of the inherent parallelism of crystallographic algorithms, extends the range of problems in macromolecular crystallography that programs can be applied to and can significantly reduce the time required for progressing from a data set to a refined model.
Kay Diederichs (Tue,) studied this question.