1Computer Science Department University of

Pittsburgh

Evaluating a DVS Scheme for Real-Time Embedded Systems

Ruibin Xu, Daniel Mossé and Rami Melhem

2Computer Science Department University of

Pittsburgh

Introduction

Energy conservation is important for real-time embedded systems

Dynamic Voltage Scaling (DVS) is effective in power management

A popular problem: minimizing energy consumption while meeting the deadlines

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Focus

Frame-based systems that execute variable workloads

The problem becomes minimizing the expected energy consumption while meeting the deadlines

……

timeFrame length

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A New DVS Scheme (MEEC)

simplified problem

original problem

optimal solution

practical solution

relax

fix

Evaluationsefficient algorithm

emsoft’05

parc’05

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Task and System Model

N periodic tasksT1, T2, …, TN to be executed consecutively in each frame

The power function is p(f) = c0+c1f α

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Review of Existing Schemes

slack

slack

slack

Proportional Scheme

Greedy Scheme

Statistical Scheme

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The MEEC Scheme

Incorporates the variability of the tasks into the speed schedule

The variability of the tasks are captured by the probability density function of the workload of the tasks

Aims to minimize the expected energy consumption in the system

workload

probability

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The MEEC Schemeslack

β1d (1-β1)d

d

β1 β2 β3 β4

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An Important PropertyThe optimal expected energy consumption

for

d d

…

are

Both are proportional to 1/d2

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Computing βi

β4=100%

β3=xx%

vs.

T1 T2 T3 T4

β2=xx%

vs.

vs.

β1=xx%

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Applying PACE

PACE is a technique in which the execution speed is gradually increased as the task progresses

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The MEEC Scheme

The β values (optimal) are computed based on the assumption of unrestricted continuous frequency

We need to deal with: Minimum and maximum speed restriction Discrete speed

We have solutions and will use simulation to test them

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Evaluations – Power models

Synthetic processor Strictly conforms to p(f)=f3

10 frequencies: 100MHz, 200MHz,…, 1000MHz

Intel Xscale Power numbers from Intel

datasheets p(f) = 80+1520(f/1000)3

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Evaluation – Synthetic Workload

We simulated systems that have 5,10,15,20 tasks

The WCEC of each task is randomly generated from 10M to 1G cycles

The probability distribution of each task is randomly chosen from 6 representative distributions

Frame length

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Evaluation – Synthetic Workload

We evaluated 8 schemes Proportional with and without PACE Greedy with and without PACE Statistical with and without PACE MEEC with and without PACE

We simulated 100,000 frames and computed the average energy consumption per frame for each scheme

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Results – Synthetic Workload

For synthetic CPU, the best scheme is always MEEC (with or without PACE), but MEEC with PACE is only better than MEEE without PACE 13.6% of the time with an average saving of 1.2%

For Intel Xscale, the best scheme is always MEEC without PACE

Conclusion: PACE is not recommended in the MEEC scheme

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Why PACE Is Not Good in MEEC scheme?

PACE (under the assumption of unrestricted continuous frequency)

PACE (discrete frequency)

fix

β values

compute

Can differ a lot

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Results – Synthetic Workload

0

10

20

30

40

50

60

70

80

90

Synthetic CPU,Max

Synthetic CPU,Average

XScale, Max XScale, Average

Power model

En

erg

y s

av

ing

(%)

vs . proportional

vs . greedy

vs . s tatis tical

19Computer Science Department University of

Pittsburgh

Evaluation – Automatic Target Recognition (ATR)

The ATR application does pattern matching of targets in images

The regions of interest (ROI) in the image are detected and each ROI is compared with all the templates

Image processing time is proportional to the number of ROIs

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Evaluation – Automatic Target Recognition (ATR)

A front-end is responsible for collecting images and send them to the back-end periodically for target recognition

This application can be modeled as a frame-based real-time system in which all the tasks have the same workload distribution

front-end

back-end ……

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Evaluation – Automatic Target Recognition (ATR)

Simulation setup Use Intel Xscale The period is 100ms The front-end sends 1 to 6 images to the

back-end The number of ROIs in an image varies

from 1 to 8 The back-end precomputes 6 speed

schedules

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Results - Automatic Target Recognition (ATR)

0

5

10

15

20

25

1 2 3 4 5 6 average

Number of images

En

erg

y sa

vin

g(%

)

vs. proportional

vs. greedy

vs. statistical

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Summary

In this paper, we demonstrate and evaluate a new DVS scheme that aims to minimize the expected energy consumption in the system

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Conclusions

The MEEC scheme achieves significant energy savings over the existing schemes

Using only static information or aggregating dynamic information, even with probabilistic techniques, will not produce as good results as when dynamic information for each task in considered separately

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Thank you

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Pittsburgh

A Simple Example

3 tasks, the frame length is 14 time units For the CPU, c0=0, c1=1, fmin=0, and fmax=1