Automatic and effective multi-dimensional parallelisation of structured mesh based codes

The most common parallelisation strategy for many Computational Mechanics (CM) (typified by Computational Fluid Dynamics (CFD) applications) which use structured meshes, involves a 1D partition based upon slabs of cells. However, many CFD codes employ pipeline operations in their solution procedure. For parallelised versions of such codes to scale well they must employ two (or more) dimensional partitions. This paper describes an algorithmic approach to the multi-dimensional mesh partitioning in code parallelisation, its implementation in a toolkit for almost automatically transforming scalar codes to parallel form, and its testing on a range of ‘real-world’ FORTRAN codes. The concept of multi-dimensional partitioning is straightforward, but non-trivial to represent as a sufficiently generic algorithm so that it can be embedded in a code transformation tool. The results of the tests on fine real-world codes demonstrate clear improvements in parallel performance and scalability (over a 1D partition). This is matched by a huge reduction in the time required to develop the parallel versions when hand coded – from weeks/months down to hours/days.

Can effective teaching and learning strategies help student nurses to retain drug calculation skills?

Student nurses need to develop and retain drug calculation skills in order accurately to calculate drug dosages in clinical practice. If student nurses are to qualify and be fit to practise accurate drug calculation skills, then educational strategies need to not only show that the skills of student nurses have improved but that these skills have been retained over a period of time. A quasi-experimental approach was used to test the effectiveness of a range of strategies in improving retention of drug calculation skills. The results from an IV additive drug calculation test were used to compare the drug calculation skills of student nurses between two groups of students who had received different approaches to teaching drug calculation skills. The sample group received specific teaching and learning strategies in relation to drug calculation skills and the second group received only lectures on drug calculation skills. All test results for students were anonymous. The results from the test for both groups were statistically analysed using the Mann Whitney test to ascertain whether the range of strategies improved the results for the IV additive test. The results were further analysed and compared to ascertain the types and numbers of errors made in each of the sample groups. The results showed that there is a highly significant difference between the two samples using a two-tailed test (U=39.5, p<0.001). The strategies implemented therefore did make a difference to the retention of drug calculation skills in the students in the intervention group. Further research is required into the retention of drug calculation skills by students and nurses, but there does appears to be evidence to suggest that sound teaching and learning strategies do result in better retention of drug calculation skills.