linux-kernel - [11/11] system 1: Saving energy using DVFS

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Message-Id: <1389111587-5923-12-git-send-email-morten.rasmussen@arm.com>
Date:	Tue,  7 Jan 2014 16:19:47 +0000
From:	Morten Rasmussen <morten.rasmussen@....com>
To:	peterz@...radead.org, mingo@...nel.org
Cc:	rjw@...ysocki.net, markgross@...gnar.org,
	vincent.guittot@...aro.org, catalin.marinas@....com,
	morten.rasmussen@....com, linux-pm@...r.kernel.org,
	linux-kernel@...r.kernel.org
Subject: [11/11] system 1: Saving energy using DVFS

Most modern systems use DVFS to save power by slowing down computation
throughput when less performance is necessary. The power/performance
relation is platform specific. Some platforms may have better energy
savings (energy per instruction) than others at low frequencies.

To have something to relate to, here is an anonymized example based on
a modern ARM platform:

Performance	Energy/instruction
1.0		1.0
1.3		1.6
1.7		1.8
2.0		1.9
2.3		2.1
2.7		2.4
3.0		2.7

Performance is frequency (~instruction issue rate) and
energy/instruction is the energy cost of executing one (or a fixed
number of instructions) at that level of performance (frequency). For
this example, it costs 2.7x more energy per instruction to increase the
performance from 1.0 to 3.0 (3x). That is, the amount of work
(instructions) that can be done on one battery charge is reduced by 2.7x
(~63%) if you run as fast as possible (3.0) compared to running at
slowest frequency (1.0).

A lot of things haven't been accounted for in this simplified example.
There is a number of factors that influence the energy efficiency
including whether the cpu is the only one awake in its frequency/power
domain or not. The numbers shown above won't be accurate for all
workloads. They are meant as a ballpark figures.

To save energy, the higher frequencies should be avoided and only used
when the application performance requirements can not be satisfied
otherwise (e.g. spread tasks across more cpus if possible).

When considering the total system power it may save energy in some
scenarios by running the cpu faster to allow other power hungry parts of
the system to be shut down faster. However, this is highly platform and
application dependent.

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