Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SmartWatts: Self-Calibrating Software-Defined Power Meter for Containers   Fine-grained power monitoring of software activities becomes unavoidable to
maximize the power usage efficiency of data centers. In particular, achieving
an optimal scheduling of containers requires the deployment of software-defined
power~meters to go beyond the granularity of hardware power monitoring sensors,
such as Power Distribution Units (PDU) or Intel's Running Average Power Limit
(RAPL), to deliver power estimations of activities at the granularity of
software~containers. However, the definition of the underlying power models
that estimate the power consumption remains a long and fragile process that is
tightly coupled to the host machine.
  To overcome these limitations, this paper introduces SmartWatts: a
lightweight power monitoring system that adopts online calibration to
automatically adjust the CPU and DRAM power models in order to maximize the
accuracy of runtime power estimations of containers. Unlike state-of-the-art
techniques, SmartWatts does not require any a priori training phase or hardware
equipment to configure the power models and can therefore be deployed on a wide
range of machines including the latest power optimizations, at no cost.

34
The categories of this paper are: chem-ph
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
23
The categories of this paper are: solv-int
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
7
The categories of this paper are: hep-th
15
The categories of this paper are: nucl-ex
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg