Bioinspired Similarity-Based Planning Support for the Porting of Scientific Applications

In this paper, we propose a methodology to address an important aspect of software porting that receives little attention, namely planning support. When a scientific application consisting of many subroutines is to be ported, the selection of key subroutines greatly impacts the productivity and overall porting strategy because these subroutines may represent a significant aspect of the code in terms of functionality or performance. They may as well serve as indicators of the difficulty and amount of effort involved in porting a code to a new platform. The proposed methodology is based on the idea that similar subroutines can be ported with similar strategies and result in a similar-quality porting. By viewing subroutines as DNA-like sequences, we are able to use various bioinformatics techniques to conduct the similarity analysis of subroutines. To the best of our knowledge, we are one of the first exploring this bioinspired view of program to the planning problem. In the paper we describe the methodology and present a tool called Klonos to facilitate the execution of the methodology. As a proof of concept, we use Klonos to conduct experiments on the OpenMP porting of several scientific benchmarks. We also identify the advantages and limitations of the bioinspired view of a program code.