Computational Efficiency vs. Maintainability and Portability. Experiences with the Sparse Grid Code SG++

Software in computational science and engineering often lacks good software engineering practices. One of several reasons is that a high computational performance and efficiency does not coincide very well with software quality attributes such as flexibility, extensibility, usability, modularity or maintainability. Where low-level programming is required to exploit parallel hardware to the best extent, common programming paradigms such as object-oriented programming cannot be applied any more. To achieve as much software quality as possible, the tradeoff between computational efficiency and maintainability and portability has to be chosen carefully.We demonstrate some optimizations that have to be applied at the example of SG++, a numerics framework for the efficient solution of higher-dimensional problems in science and engineering with sparse grids. We discuss the performance advantages and software quality disadvantages they cause. We explain the criteria for the design decisions in SG++ and report on the lessons learned.