A Hadoop approach to advanced sampling algorithms in molecular dynamics simulation on cloud computing

Cloud computing has emerged as a prevalent computing paradigm with the advantages of virtualization, scalability, fault tolerance, and a usage based pricing model. It has been widely used in various computational research fields. Replica exchange molecular dynamics (REMD) and replica exchange statistical temperature molecular dynamics (RESTMD) are two sampling algorithms in molecular dynamics. Due to the inherent parallel feature of REMD and RESTMD, it is practical to convert them into cloud computing applications. However, the performance of REMD and RESTMD on clouds has not been extensively investigated. In our work, we implemented REMD and RESTMD in cloud computing environment through Hadoop, an open source implementation of MapReduce platform, and evaluated the performance of REMD and RESTMD in cloud computing environment and in high performance computing (HPC) environment as reference. In our research, REMD and RESTMD exhibits good feasibility in cloud computing. Otherwise, cloud computing demonstrates the characteristics of virtualization, elasticity, and scalability, providing a robust environment for REMD and RESTMD.