Report ID
2006-02
Report Date
Abstract
Understanding the full-system power and energy behavior
of real, resource-constrained, battery-powered devices is vital
to accurately characterize, model, and develop
effective techniques for extending battery life.
Unfortunately, extant approaches to measuring and characterizing
power and energy
consumption focus on high-end processors,
do not consider the complete device, employ inaccurate (program-only)
simulation, rely on inaccurate, course-grained battery level
data from the device, or employ expensive power measurement
tools that are difficult to share across research groups and students.
In this paper, we present RPM, a remote performance monitoring system, that enables fine grained characterization of embedded computers. RPM consists of a tightly connected set of components which (1) control lab equipment for power measurements and analysis, (2) configure target system characteristics at run-time (such as CPU and memory bus speed), (3) collect target system data using on-board hardware performance monitors (HPMs) and (4) provide a remote access interface. Users of RPM can submit and configure experiments that execute programs on the RPM target device (currently a Stargate sensor platform that is very similar to an HP iPAQ) to collect very accurate power, energy, and CPU performance data with high resolution.
We use RPM to investigate whether CPU-based performance data in the form of HPM metrics or program phase behavior correlates well with full-system energy or power behavior. Prior work shows that both accurately estimate processor power consumption for high-end CPUs. In resource-constrained devices, such as the one we study, however, the processor consumes a much smaller portion of the total power in the system than for high-end processors. Our experimentation with RPM for the Stargate and set of embedded system benchmarks, show that CPU-based metrics do not correlate well with full-system energy and power consumption. Moreover, we find that full-system energy and power varies significantly with the type of memory device and file system.
In this paper, we present RPM, a remote performance monitoring system, that enables fine grained characterization of embedded computers. RPM consists of a tightly connected set of components which (1) control lab equipment for power measurements and analysis, (2) configure target system characteristics at run-time (such as CPU and memory bus speed), (3) collect target system data using on-board hardware performance monitors (HPMs) and (4) provide a remote access interface. Users of RPM can submit and configure experiments that execute programs on the RPM target device (currently a Stargate sensor platform that is very similar to an HP iPAQ) to collect very accurate power, energy, and CPU performance data with high resolution.
We use RPM to investigate whether CPU-based performance data in the form of HPM metrics or program phase behavior correlates well with full-system energy or power behavior. Prior work shows that both accurately estimate processor power consumption for high-end CPUs. In resource-constrained devices, such as the one we study, however, the processor consumes a much smaller portion of the total power in the system than for high-end processors. Our experimentation with RPM for the Stargate and set of embedded system benchmarks, show that CPU-based metrics do not correlate well with full-system energy and power consumption. Moreover, we find that full-system energy and power varies significantly with the type of memory device and file system.
Document
2006-02.pdf1.72 MB