Abstract: Migrating application from on premise HPC cluster to serverless platform is tedious task and involves significant amount of human efforts as cloud infrastructure needs to be created, data along with libraries and application code need to be copied from on-premise to cloud, and application need to be made compliant for execution on cloud. Present disclosure provides method and system for performing automated migration of high performance computing application to serverless platform. The system first check cloud readiness of application based on operation qualification parameters of application. In case application is found to be cloud ready, the system determines whether application can be executed on serverless platform based on execution time of the application and permissible limits defined for application in service level agreements.

Abstract: State of the art predictive maintenance systems that generate predictions with respect to maintenance of High Performance Computing (HPC) systems have the disadvantage that they either are reactive, or the predictions are affected due to quality issues associated with the data being collected from the HPC systems. The disclosure herein generally relates to predictive maintenance, and, more particularly, to a method and system for predictive maintenance of High Performance Computing (HPC) systems. The system performs abstraction and cleansing on performance data collected from the HPC systems, and generates a cleansed performance data, on which a Machine Leaning (ML) prediction is applied to generate predictions with respect to maintenance of the HPC systems.