A cluster-based solution for high performance hmmpfam using EARTH execution model

Hmmpfam is a widely used computation-intensive bioinformatics software for sequence classification. The contribution of this paper is the first largely scalable and robust cluster-based solution of parallel hmmpfam based on EARTH (Efficient Architecture for Running Threads), which is an event-driven fine-grain multi-threaded programming execution model. Compared with the original PVM implementation, our implementation shows notable improvements on absolute speed-up and better scalability. Experiments on two advanced supercomputing clusters at Argonne National Laboratory (ANL) achieve an absolute speedup of 222.8 on 128 dual-CPU nodes for a representative data set, which means that the total execution time is reduced from 15.9 hours (serial program) to only 4.3 minutes.