Hardware Reference
In-Depth Information
More formally, for our optimisation problem, we can define the operating point
of application
α
with the following tuple:
c
α
=
ρ
,
φ
,
π
,
τ
(5.1)
where:
ρ
is a scalar representing the
resources
associated with the operating point
c
α
.
We assume that there exists an application binary version which has been paral-
lelized over
ρ
cores. In our case,
ρ
maximum
number of available cores. Given the features of the interconnection bus, we
assume homogeneity among the cores and a fixed mapping for each of the threads.
∈
R
={
1
...ρ
max
}
, where
ρ
max
=
φ
corresponds
to
the
frequency
configuration
for
each
of
the
ρ
cores:
ρ
.
π
is the actual
cost
associated with the current operating point
c
α
. Here, we
consider the cost as the average power consumption of application
α
.
τ
is the average execution time needed by
α
for a single period
1
of an application
(e.g. encoding a single frame in a multi-media application) when on the current
operating point
c
α
.
In the following sections, we will use the notation
c
α
[
X
] to access the element
X
of
the tuple defined in Eq.
5.1
.
φ
1
...φ
ρ
,
φ
i
∈
∧
1
≤
i
≤
5.3.2
RRM Problem
We assume that for each application
α
, there is an available set of operating points
C
α
whose size is
N
α
. The run-time manager has to select exactly one point from each
active set
C
α
, according to the available platform resources, in order to minimize the
total power consumption of the platform, while respecting all application deadlines.
Given a set of required application deadlines
τ
max
, our problem definition is to
identify, at run-time, a comprehensive set of operating points:
γ
=
c
α
1
...
c
α
p
,
c
α
j
∈
C
α
j
∧
1
≤
j
≤
p
(5.2)
such that the following measure of power consumption is minimized:
c
α
[
π
]
(5.3)
α
∈
A
1
Note that in domains of multi-media and wireless applications, usually the applications are periodic
i.e., they do same task again and again but on different input data e.g. processing video frames or
wireless packets
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