Abstract

The emerging data-intensive applications of today are comprised of non-uniform CPU and I/O intensive workloads, thus imposing a requirement to consider both CPU and I/O effects in the power management strategies. Only scaling down the processor's frequency based on its busy/idle ratio cannot fully exploit opportunities of saving power. Our experiments show that besides the busy and idle status, each processor may also have I/O wait phases waiting for I/O operations to complete. During this period, the completion time is decided by the I/O subsystem rather than the CPU thus scaling the processor to a lower frequency will not affect the performance but save more power. In addition, the CPU's reaction to the I/O operations may be significantly affected by several factors, such as I/O type (sync or unsync), instruction/job level parallelism, it cannot be accurately modeled via physics laws like mechanical or chemical systems. In this paper, we propose a novel power management scheme called MAR (modeless, adaptive, rule-based) in multiprocessor systems to minimize the CPU power consumption under performance constraints. By using richer feedback factors, e.g. the I/O wait, MAR is able to accurately describe the relationships among core frequencies, performance and power consumption. We adopt a modeless control model to reduce the complexity of system modeling. MAR is designed for CMP (Chip Multi Processor) systems by employing multi-input/multi-output (MIMO) theory and per core level DVFS (Dynamic Voltage and Frequency Scaling). Our extensive experiments on a physical test bed demonstrate that, for the SPEC benchmark and data-intensive (TPC-C) benchmark, the efficiency of MAR is 93.6-96.2\% accurate to the ideal power saving strategy calculated off-line. Compared with baseline solutions, MAR could save 22.5-32.5\% more power while keeping the comparable performance loss of about 1.8-2.9\%. In addition, simulation results show the efficiency of our design for various CMP configurations.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.