Power consumption due to data movement in distributed programming models

The amount of energy consumed due to data movement poses a serious challenge when implementing and using distributed programming models. Message-passing models like MPI provide the user with explicit interfaces to initiate data-transfers among distributed processes. In this work, we establish the notion that from a programmer's standpoint, design decisions like the size of the data-payload to be transferred and the number of explicit MPI calls to service such transfers have a direct impact on the power signatures of communication kernels. Upon closer look, we additionally observe that the choice of the transport layer (along with the associated interconnect) and the design of the data transfer protocol, both, contribute to these signatures. This paper presents a fine-grained study on the impact of the power and energy consumption due to data movement in distributed programming models. We hope that results discussed in this work would motivate application and system programmers to include energy consumption as one of the important design factors while targeting HPC systems.