Abstract-Over the past decade, high performance applications have embraced parallel programming and computing models. While parallel computing offers advantages such as good utilization of dedicated hardware resources, it also has several drawbacks such as poor fault-tolerance, scalability, and ability to harness available resources during run-time. The advent of cloud computing presents a viable and promising alternative to parallel computing because of its advantages in offering a distributed computing model. In this work, we establish directives that serve as guidelines for the design and implementation or identification of a suitable cloud computing framework to build or convert a high performance application to run in the cloud. We show that following these directives leads to an elastic implementation that has better scalability, run-time resource adaptability, fault tolerance, and portability across cloud computing platforms, while requiring minimal effort and intervention from the user. We illustrate this by converting an MPI implementation of replica exchange, a parallel tempering molecular dynamics application, to an elastic cloud application using the Work Queue framework that adheres to these directive. We observe better scalability and resource adaptability of this elastic application on multiple platforms, including a homogeneous cluster environment (SGE) and heterogeneous cloud computing environments such as Microsoft Azure and Amazon EC2.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.