Modeling the temperature bias of power consumption for nanometer-scale CPUs in application processors

Abstract

Abstract-We introduce and experimentally validate a new macro-level model of the CPU temperature/power relationship within nanometer-scale application processors or system-onchips. By adopting a holistic view, this model is able to take into account many of the physical effects that occur within such systems. Together with two algorithms described in the paper, our results can be used, for instance by engineers designing power or thermal management units, to cancel the temperatureinduced bias on power measurements. This will help them gather temperature-neutral power data while running multiple instance of their benchmarks. Also power requirements and system failure rates can be decreased by controlling the CPU's thermal behavior.Even though it is usually assumed that the temperature/power relationship is exponentially related, there is however a lack of publicly available physical temperature/power measurements to back up this assumption, something our paper corrects. Via measurements on two pertinent platforms sporting nanometerscale application processors, we show that the power/temperature relationship is indeed very likely exponential over a 20• C to 85• C temperature range. Our data suggest that, for application processors operating between 20• C and 50• C, a quadratic model is still accurate and a linear approximation is acceptable.

P‐EdgeCoolingMode: an agent‐based performance aware thermal management unit for DVFS enabled heterogeneous MPSoCs

“…In the study [7], through experiments on real devices it was found that on heterogeneous MPSoCs such as Odroid platforms, power and temperature follows a relationship of quadratic function or exponential function based on various other dependable factors * . We also validate this relationship in Sec.…”

“…But in practical sense, majority of the published algorithms lack the flexibility for real world implementation because the usage and workload on similar devices by different users are different and hence, requires the resource management methodologies to be flexible to adapt over time. Elevated temperatures have adverse effects on Integrated Circuits (ICs) and reliability of electronic products can be heavily influenced by spatial or temporal gradients, or absolute temperatures [7]. To mitigate such reliability issues most mobile devices often come with thermal capping.…”

A Mobile Application Offloading Algorithm for Mobile Cloud Computing

“…The power consumed when the terminal is in the Active state is P active M = 3.351 Watt. The Tx/Rx capacity between the mobile handset and the server is B [25]. We assume that the server on which is activated a new VM for each application offloading is equipped with a X86 CPU operating 4 times faster than the CPU of the mobile terminal (F ).…”

DeadPool: Performance Deadline Based Frequency Pooling and Thermal Management Agent in DVFS Enabled MPSoCs

“…Elevated operating temperatures and thermal cycling on the device have adverse effects on Integrated Circuits (ICs) and reliability of electronic products can be heavily influenced by spatial or temporal gradients or absolute temperatures [8]- [10]. Here, thermal cycling is the phenomenon of the operating temperature increasing from an initial value and then decreasing to the starting value periodically, and each occurrence of the phenomenon is signified as one thermal cycle.…”