Algorithms for CPU and DRAM DVFS Under Inefficiency Constraint

Dynamic voltage and frequency scaling (DVFS) of both the core and DRAM provides opportunities to trade-off performance in order to save energy. Previous approaches to core and DRAM power management using DVFS used performance, specifically acceptable performance loss, as a constraint. We present energy management algorithms that coordinate core and DRAM frequency scaling under a specified energy budget. Approaches that work under performance constraints, as we will show, are not directly applicable to systems operating under energy constraints, as it is difficult to calculate the correct performance bounds in real-time to stay under an energy budget.

Setting arbitrary energy budgets for a diverse set of applications can be harmful to application performance. We use the previously introduced concept of Inefficiency—​the additional amount of energy above the minimum required energy that can be used to improve performance—​to provide a dynamic energy constraint to our system. We introduce new power management algorithms that search the power and performance space to find the best performing point under this constraint. We demonstrate the efficacy of our algorithms using CPU DVFS and DRAM frequency scaling. We show that our algorithms have 24% lower tuning cost and save up to 5% energy with a little performance loss compared to a state-of-the-art performance constrained system.