Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T....
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![Page 1: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/1.jpg)
Energy-Efficient Mapping and Scheduling for DVS Enabled
Distributed Embedded Systems
Marcus T. Schmitz and Bashir M. Al-HashimiUniversity of Southampton, United Kingdom
Petru ElesLinköping University, Sweden
![Page 2: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/2.jpg)
2Marcus T. SchmitzUniversity of Southampton
Contents• Motivation & Introduction
• Dynamic Voltage Scaling
• Co-Synthesis with DVS Consideration
• DVS optimised Scheduling
• DVS optimised Mapping
• Experimental Results
• Conclusions
![Page 3: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/3.jpg)
3Marcus T. SchmitzUniversity of Southampton
MotivationLow Energy:
• Portable Applications
• Autonomous Systems
• Feasibilty Issues (SoC - heat)
• Operational Cost and Environmental Reasons
System Level Co-Design:
• Shrinking Time-To-Market Windows
• Reducing Production Cost
• High Degree of Optimisation Freedom
![Page 4: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/4.jpg)
4Marcus T. SchmitzUniversity of Southampton
Introduction
Dynamic Voltage Scaling
System Level Co-Synthesis
Energy-Efficient Co-Synthesis for
DVS Sytems
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5Marcus T. SchmitzUniversity of Southampton
Dynamic Voltage Scaling (DVS)
f Reg.
DVS Processor
0
0.2
0.4
0.6
0.8
1
1.2
1 1.5 2 2.5 3 3.5 4 4.5 5
Energy vs. Speed
Voltage/Frequency
Frequency
VR
Available from: Transmeta, AMD, Intel
1/Speed
En
erg
y
2ddVkE
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6Marcus T. SchmitzUniversity of Southampton
Co-Synthesis for DVS Systems
Allocation
Mapping
Scheduling
Voltage Scaling
Evaluation
EE
-GL
SA
EE
-GM
A
De
sig
ne
r d
riv
en
System Specification, Technology Lib.
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7Marcus T. SchmitzUniversity of Southampton
DVS in Distributed Systems [23]
PE0
PE1
CL0
P
td
PE0
PE1
CL0
P
td
@ Vmax @ dyn. V
Input:Scheduling (mapping)Power profile
Output:scaled voltage for each DVS task
Emax Esc < Emax
Slack
2.3V 2.4V3.3V
Voltage Scaling
![Page 8: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/8.jpg)
8Marcus T. SchmitzUniversity of Southampton
Energy-Efficient Scheduling
Two objectives:
• Timing feasibility
• Garantee deadlines
• Low energy dissipation
• Optimisation DVS usability – Slack time
Problem due to power variations:
• Simply increase deadline slack leads to sub-optimal solutions!
Traditional scheduling technique focus mainly on timing feasibility!
![Page 9: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/9.jpg)
9Marcus T. SchmitzUniversity of Southampton
Energy-Efficient Scheduling
0
4 5
12
36
E=71J
4 5
01 2
36
4 5
01 2
3 6
012
36
4 5
E=71J
E=53.9J
E=65.6J
Slack Savings
Slack Savings
S1:
S2:
DVS
DVS
Slack
Slack
PE0
PE1
PE2
PE0
PE1
PE2
P
t t
tt
P
P
P
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10Marcus T. SchmitzUniversity of Southampton
Energy-Efficient Scheduling• Based on Genetic List Scheduling Algorithm [6,10]
• Task priorities are encoded into priorities strings
List Scheduler
4 3 9 7 2
PS
Duties of the Scheduler:1. Select ready task with highest
priority2. Schedule selected task3. Update schedule and ready list4. Repeat until no un-scheduled
task is left
Schedule
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11Marcus T. SchmitzUniversity of Southampton
EE-GLSA
List Scheduler DVS
Assign fitness
Rank individuals
Selection
Mutation
Mating
InsertionIniti
al P
opul
atio
n
Opt
imis
ed P
opul
atio
n
GA
low high
Timing, Energy
3
7
8
1
2
3
2
1
3
2
No Hole Filling!No Mapping!
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12Marcus T. SchmitzUniversity of Southampton
Advantages
• Optimisation can be based on an arbitrary complex
fitness function, including:
• Timing
• Energy (DVS technique)
• Enlarged search space (|T+C|! different schedules)
• Trade-off freedom: Synthesis time <-> quality
• Easily adaptable to computing clusters
• Multiple populations with immigration scheme
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13Marcus T. SchmitzUniversity of Southampton
Hole Filling Problem
d2
d4
d3
7
6
4
4
1
d2 d3,4
Hole filling
Therefore, priorities decide solely upon execution order!
PE0
PE1
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14Marcus T. SchmitzUniversity of Southampton
Task Mapping
Why seperation from the list scheduling?• Regardless of priorties, greedy mapping
LS
d2
7
4
5
d1
d1,2
PE0
PE1
P
t
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15Marcus T. SchmitzUniversity of Southampton
Task Mapping
Make greedy mapping decision based on:• Timing• Energy
LS
d2
7
4
5
d1
d1,2
?
?PE0
PE1
P
t
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16Marcus T. SchmitzUniversity of Southampton
Task Mapping
Make mapping decision based on:• Timing• Energy
LS
d2
7
4
5
d1
d1,2
PE0
PE1
P
t
![Page 17: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/17.jpg)
17Marcus T. SchmitzUniversity of Southampton
Task Mapping
Make mapping decision based on:• Timing• Energy
LS
d2
7
4
5
d1
d1,2
?
?
PE0
PE1
P
t
![Page 18: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/18.jpg)
18Marcus T. SchmitzUniversity of Southampton
Task Mapping
Make mapping decision based on:• Timing• Energy
LS
d2
7
4
5
d1
d1,2
PE0
PE1
P
t
![Page 19: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/19.jpg)
19Marcus T. SchmitzUniversity of Southampton
Task Mapping
Make mapping decision based on:• Timing• Energy
LS
d2
7
4
5
d1
d1,2
PE0
PE1
P
t
![Page 20: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/20.jpg)
20Marcus T. SchmitzUniversity of Southampton
Task Mapping
Make mapping decision based on:• Timing• Energy
LS
d2
7
4
5
d1
d1,2
PE0
PE1
P
t
![Page 21: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/21.jpg)
21Marcus T. SchmitzUniversity of Southampton
Task Mapping
Make mapping decision based on:• Timing• Energy
LS
d2
7
4
5
d1
d1,2
PE0
PE1
P
t
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22Marcus T. SchmitzUniversity of Southampton
Genetic Mapping Algorithm [8]
CPU DVS-CPU
ASIC
01
2d
d
5
3
6
4
0
1 2
task PE
0 1
1 0
2 2
3 1
4 1
5 0
6 0
Chromosome
Task mapping are encoded into mapping strings
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23Marcus T. SchmitzUniversity of Southampton
EE-GMA
EE-GLSA
Assign fitness
Rank individuals
Selection
Mutation
Mating
Insertion
Initi
al P
opul
atio
n
Opt
imis
ed P
opul
atio
n
GA
low high
Timing, Energy + Area
Including DVS
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24Marcus T. SchmitzUniversity of Southampton
Experimental Results• 4 Benchmark Sets:
• 27 generated by TGFF [7]
– 8 to 100 tasks: Power variations 2.6
• 2 Hou examples taken from [13]
– 8 to 20 tasks: Power variations 11
• TG1 and TG2 taken from [11]
– 60 examples with 30 tasks, each: No power variations
• Measurement application taken from [3]
– 12 tasks: No power profile is provided
• Power and time overhead for DVS is neglected
• Average results of 5 optimisation runs
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25Marcus T. SchmitzUniversity of Southampton
Schedule Optimisation
0
10
20
30
40
50
60
70
80
Tgff1 Tgff2 Tgff3 Tgff4 Tgff5 Tgff6 Tgff7 Tgff8 Tgff9 Tgff10
Example
Red
uct
ion
(%
)
EVEN-DVS[18]
GLSA+EVEN
EE-GLSA
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26Marcus T. SchmitzUniversity of Southampton
Schedule Optimisation
0
5
10
15
20
25
30
35
40
TG1 TG2
Benchmark set
Re
du
cti
on
(%
)
LEneS [11]
EE-GLSA
![Page 27: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/27.jpg)
27Marcus T. SchmitzUniversity of Southampton
Mapping Optimisation
0
10
20
30
40
50
60
70
80
90
Tgff1 Tgff2 Tgff3 Tgff4 Tgff5 Tgff6 Tgff7 Tgff8 Tgff9 Tgff10
Example
Red
uct
ion
(%
)
EVEN-DVS
EE-GMA
![Page 28: Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems Marcus T. Schmitz and Bashir M. Al-Hashimi University of Southampton,](https://reader035.fdocuments.in/reader035/viewer/2022062404/5516043b55034694308b4d51/html5/thumbnails/28.jpg)
28Marcus T. SchmitzUniversity of Southampton
Conclusions
• DVS capability can achieve high energy savings in distributed embedded systems
• Proposed a new energy-efficient two-step mapping and scheduling approach
• Iterative improvement provides high savings / ad hoc constructive techniques are not suitable
• Optimisation times are reasonable
• Additional objectives can be easily included
• Consideration of power profile information leads to further energy reductions