Energy Efficient Computing
In this talk I give an overview of the algorithms we have developed at UCSD to significantly lower the energy consumption in computing systems. We derived optimal power management strategies for stationary workloads that have been implemented both in HW and SW. Run-time adaptation can be done via an online learning algorithm that selects among a set of policies. We generalize the algorithm to include thermal management since we found that minimizing the power consumption does not necessarily reduce the overall energy costs.