Parallel Distributed Infrastructure for Minimization of Energy

ParaDIME @ ARM Research, Cambridge

Mon, 2015-09-21

ParaDIME disseminated its research results as a part of the invited talk series at the ARM Research in Cambridge on 18th of September.  This talk was attended by people from both ARM Cambridge and and from ARM, Austin, USA through a live feed.

First part of the talk was focused on how to design and implement energy-aware computing and power estimation in servers, MPSoCs and various types of data centers to help achieve an energy efficient computing future. Power and energy consumption of data centers are steadily increasing and the work performed by the data centers is not proportional to the power dissipated, where every µA is a revenue for the entity. On the one hand, the hardware community is proposing various methodologies to address this issue such as low-power processors, heterogeneity, etc. to reduce the power of the servers. On the other hand, the software community proposes mechanisms such as virtual machines (VMs), work-load scheduling, etc. to increase the utilization of the processor. In order to properly evaluate the impact of these mechanisms, we need an accurate power monitoring and estimation tool at the hardware host level, the VM level and the system-level. Achieving the target exascale performance and designing a green cloud computing infrastructure require the design of dynamic and smart techniques that recognize the hardware-software characteristics and optimization of the trade-off among performance, energy, and power in an application-aware manner. Second part of the talk was focused on a novel heterogeneous platform with the integration of three devices (CPU, GPU, FPGA) into a single system, i.e. Trigeneous platforms, to efficiently accelerate and to minimize energy of computation intensive applications in both high-performance computing and embedded system domains.