Cloud computing is increasingly being explored as a cost effective alternative and addition to supercomputers for some High Performance Computing (HPC) applications. However, dynamic environment and interference by other virtual machines are some of the factors which prevent efficient execution of HPC applications in cloud. Through this research, we leverage a message driven adaptive runtime system to develop techniques that reduce the gap between application performance on cloud and supercomputers. Our scheme uses object migration to achieve load balance for tightly coupled parallel applications executing in virtualized environments that suffer from interfering jobs. While restoring load balance, it not only reduces the timing penalty caused by interfering jobs, but also reduces energy consumption significantly. With experimental evaluation using benchmarks and a real HPC application, we demonstrate that our scheme reduces the timing penalty and energy overhead associated with interfering jobs by at least 50%.