Automatic data layout for distributed-memory machines

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Abstract
The goal of languages like Fortran D or High Performance Fortran (HPF) is to provide a simple yet efficient machine-independent parallel programming model. After the algorithm selection, the data layout choice is the key intellectual challenge in writing an efficient program in such languages. The performance of a data layout depends on the target compilation system, the target machine, the problem size, and the number of available processors. This makes the choice of a good layout extremely difficult for most users of such languages. If languages such as HPF are to find general acceptance, the need for data layout selection support has to be addressed. We beleive that the appropriate way to provide the needed support is through a tool that generates data layout specifications automatically. This article discusses the design and implementation of a data layout selection tool that generates HPF-style data layout specifications automatically. Because layout is done in a tool that is not embedded in the target compiler and hence will be run only a few times during the tuning phase of an application, it can use techniques such as integer programming that may be considered too computationally expensive for inclusion in production compilers. The proposed framework for automatic data layout selection builds and examines search spaces of candidate data layouts. A candidate layout is an efficient layout for some part of the program. After the generation of search spaces, a single candidate layout is selected for each program part, resulting in a data layout for the entire program. A good overall data layout may require the remapping of arrays between program parts. A performance estimator based on a compiler model, an execution model, and a machine model are needed to predict the execution time of each candidate layout and the costs of possible remappings between candidate data layouts. In the proposed framework, instances of NP-complete problems are solved during the construction of candidate layout search spaces and the final selection of candidate layouts from each search space. Rather than resorting to heuristics, the framework capitalizes on state-of-the-art 0-1 integer programming technology to compute optimal solutions of these NP-complete problems. A prototype data layout assistant tool based on our framework has been implemented as part of the D system currently under development at Rice University. The article reports preliminary experimental results. The results indicate that the framework is efficient and allows the generation of data layouts of high quality.

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