Parallel Aligning Multiple Metabolic Pathways on Hybrid CPU and GPU Architectures.

Metabolic pathway alignment remains an important tool in systems biology, and has become even more important with the growing mass of metabolic pathway data. However, the process of aligning multiple metabolic pathways scale poorly with either the number of pathways or with the size of pathways, and no attempts have been made to exploit the parallelism of the pathway alignments to improve the efficiency. This paper proposes a parallel metabolic pathway alignment method called PMMPA. In PMMPA, we design a commonly used parallel algorithm for the computation of reaction (node) similarity in GPU, and implement a parallel strategy for aligning multiple metabolic pathways in multi-core CPU. The experimental results show that this parallel alignment implementation achieves at most 300 times faster than the single-threaded version, the parallel implementation of aligning metabolic pathways on the hybrid CPU and GPU architecture is promising in improving the efficiency.