The combination of increasing component power consumption, a desire for denser systems, and the required performance growth in the face of technology-scaling issues are posing enormous challenges for powering and cooling of server systems. The challenges are directly linked to the peak power consumption of servers. Our solution, Power Shifting, reduces the peak power consumption of servers minimizing the impact on performance. We reduce peak power consumption by using workload-guided dynamic allocation of power among components incorporating real-time performance feedback, activity-related power estimation techniques, and performance-sensitive activity-regulation mechanisms to enforce power budgets. We apply our techniques to a computer system with a single processor and memory. Power shifting adds a system power manager with a dynamic, global view of the system's power consumption to continuously re-budget the available power amongst the two components. Our contributions include: • Demonstration of the greater effectiveness of dynamic power allocation over static budgeting, • Evaluation of different power shifting policies, • Analysis of system and workload factors critical to successful power shifting, and • Proposal of performance-sensitive power budget enforcement mechanisms that ensure system reliability.
Policies that allocate dynamically power budget of an application between processor and memory have been proposed ( REF ).
A performance-conserving approach for reducing peak power consumption in server systems
ICS '05
Computer Science