Post on 07-Jun-2020
What Users Want and What Hardware Provides: Bridging the Gap Between User Quality of Experience (QoE) and Mobile Device Trends
Vijay Janapa ReddiThe University of Texas at Austin
Academia Sinica — Sep. 10, 2015
2
3
4
Call
Text
4
Call
Text
4
Call
Text
Email The (in)famous “snake game”
4
5
Mob
ile A
pplic
atio
ns
0
500,000
1,000,000
1,500,000
2,000,000
Years
2009 2010 2011 2012 2013Data source: Mobilewalla
6
“I want desktop-level performance on my mobile device.”
7
“I want desktop-level performance on my mobile device.”
7
Responsiveness
8
Responsiveness
▸100 ms latency is the limit for having users feel the system is reacting responsively [Miller 1968; Card et al. 1991]
8
Responsiveness
▸100 ms latency is the limit for having users feel the system is reacting responsively [Miller 1968; Card et al. 1991]
▸64% of mobile users will not revisit a slow Web app [Source: Akamai]
8
Responsiveness
▸100 ms latency is the limit for having users feel the system is reacting responsively [Miller 1968; Card et al. 1991]
▸64% of mobile users will not revisit a slow Web app [Source: Akamai]
▸Amazon found every 100 ms of latency costs them 1% in sales per year [Source: Amazon]
8
Responsiveness Energy-Efficiency
8
Responsiveness Energy-EfficiencyConflicting requirements
8
9
The Mobile Device Virtuous Cycle
9
The Mobile Device Virtuous Cycle
Architecture
9
The Mobile Device Virtuous Cycle
ArchitectureApplications
9
The Mobile Device Virtuous Cycle
ArchitectureApplications
Perfo
rman
ce
9
The Mobile Device Virtuous Cycle
ArchitectureApplications
Perfo
rman
ce
Capabilities
9
The Mobile Device Virtuous Cycle
ArchitectureApplications
Perfo
rman
ce
Capabilities
Our conventional research focus
9
The Mobile Device Virtuous Cycle
Mobile DeviceArchitectureApplicationsEnd
Users
Perfo
rman
ce
Capabilities
Our conventional research focus
9
The Mobile Device Virtuous Cycle
Mobile DeviceArchitectureApplicationsEnd
Users
Perfo
rman
ce
Capabilities
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Our conventional research focus
9
The Mobile Device Virtuous Cycle
Mobile DeviceArchitectureApplicationsEnd
Users
Perfo
rman
ce
Feat
ures
Capabilities
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Our conventional research focus
9
The Mobile Device Virtuous Cycle
Mobile DeviceArchitectureApplicationsEnd
Users
Satisfaction
Perfo
rman
ce
Feat
ures
Capabilities
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Our conventional research focus
9
The Mobile Device Virtuous Cycle
Mobile DeviceArchitectureApplicationsEnd
Users
Satisfaction Power Consumption
Perfo
rman
ce
Feat
ures
Capabilities
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Our conventional research focus
9
The Mobile Device Virtuous Cycle
Mobile DeviceArchitectureApplicationsEnd
Users
Satisfaction Power Consumption
Perfo
rman
ce
Feat
ures
Capabilities
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Our conventional research focus
10
The Mobile Device Virtuous Cycle
Mobile DeviceArchitectureApplicationsEnd
Users
Satisfaction Power Consumption
Perfo
rman
ce
Feat
ures
Capabilities
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Mobile Device Power Consumption Trends
11
8000
6000
4000
2000
0
Peak
Sus
tain
ed P
ower
(m
W)
Droid(2009)
Galaxy S(2010)
Galaxy N(2011)
Galaxy S3(2012)
Galaxy S4(2013)
Smartphone Model 11
Mobile Device Power Consumption Trends
12
8000
6000
4000
2000
0
Peak
Sus
tain
ed P
ower
(m
W)
Droid(2009)
Galaxy S(2010)
Galaxy N(2011)
Galaxy S3(2012)
Galaxy S4(2013)
Smartphone Model
Screen
12
Mobile Device Power Consumption Trends
13
8000
6000
4000
2000
0
Peak
Sus
tain
ed P
ower
(m
W)
Droid(2009)
Galaxy S(2010)
Galaxy N(2011)
Galaxy S3(2012)
Galaxy S4(2013)
Smartphone Model
Screen Radio
13
Mobile Device Power Consumption Trends
14
8000
6000
4000
2000
0
Peak
Sus
tain
ed P
ower
(m
W)
Droid(2009)
Galaxy S(2010)
Galaxy N(2011)
Galaxy S3(2012)
Galaxy S4(2013)
Smartphone Model
Screen Radio CPU
14
Mobile Device Power Consumption Trends
14
8000
6000
4000
2000
0
Peak
Sus
tain
ed P
ower
(m
W)
Droid(2009)
Galaxy S(2010)
Galaxy N(2011)
Galaxy S3(2012)
Galaxy S4(2013)
Smartphone Model
Screen Radio CPU
14
Mobile Device Power Consumption Trends
14
8000
6000
4000
2000
0
Peak
Sus
tain
ed P
ower
(m
W)
Droid(2009)
Galaxy S(2010)
Galaxy N(2011)
Galaxy S3(2012)
Galaxy S4(2013)
Smartphone Model
Screen Radio CPU
An order of magnitude increase in total CPU power consumption
14
Pow
er
Performance
20092010
2011
2012
2013 ~ Present
finc
Out-of-order
Multi-core
Asymmetric Multi-core
15
Pow
er
Performance
20092010
2011
2012
2013 ~ Present
finc
Out-of-order
Multi-core
Asymmetric Multi-core
15
Pow
er
Performance
20092010
2011
2012
2013 ~ Present
finc
Out-of-order
Multi-core
Asymmetric Multi-core
15
Question #1: Is the significant increase in processor power consumption justified?
Question #2: Does mobile CPU performance matter to user satisfaction?
Question #3: Can future mobile CPUs be energy-efficient and deliver performance?
16
The Mobile Device Virtuous Cycle
Mobile DeviceArchitectureApplicationsEnd
Users
Satisfaction Power Consumption
Perfo
rman
ce
Feat
ures
Capabilities
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Question #1: Is the significant increase in processor power consumption justified?
The Mobile Device Virtuous Cycle
17
Mobile DeviceArchitectureApplicationsEnd
Users
Satisfaction Power Consumption
Perfo
rman
ce
Feat
ures
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Capabilities
Question #1: Is the significant increase in processor power consumption justified?
Benchmarking Mobile CPU Performance
18
Benchmarking Mobile CPU Performance
18
Orders of Magnitude Increase in Performance
19
7
5
3
1
Norm
aliz
ed S
peed
up
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPEC Coremark
7
5
3
1
Norm
aliz
ed S
peed
up
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPEC Coremark
Orders of Magnitude Increase in Performance
19
7
5
3
1
Norm
aliz
ed S
peed
up
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPEC Coremark
7
5
3
1
Norm
aliz
ed S
peed
up
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPEC Coremark
However, Power Consumption is Steadily Rising
20
2.0
1.5
1.0
0.5
0.0Dyna
mic
Pow
er (
W)
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPECCoremark
7
5
3
1
Norm
aliz
ed S
peed
up
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPEC Coremark
However, Power Consumption is Steadily Rising
20
2.0
1.5
1.0
0.5
0.0Dyna
mic
Pow
er (
W)
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPECCoremark
7
5
3
1
Norm
aliz
ed S
peed
up
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPEC Coremark
However, Power Consumption is Steadily Rising
20
2.0
1.5
1.0
0.5
0.0Dyna
mic
Pow
er (
W)
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPECCoremark
“Good fortune” byprocess technology
7
5
3
1
Norm
aliz
ed S
peed
up
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPEC Coremark
Process scaling is getting costlier, no free ride!
21
CPU Power Consumption and Energy Trends
▸ Power consumption has risen steadily over the years
▸ Energy efficiency trends appear to be plateauing
▸ Process technology is key for low-power execution22
1.0
0.8
0.6
0.4
0.2
0.0Norm
aliz
ed E
nerg
y
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPEC Coremark
CPU Power Consumption and Energy Trends
▸ Power consumption has risen steadily over the years
▸ Energy efficiency trends appear to be plateauing
▸ Process technology is key for low-power execution22
1.0
0.8
0.6
0.4
0.2
0.0Norm
aliz
ed E
nerg
y
D S N
S3S
S3E
S4S
S4E
S5S
S5E
Smartphone Model
SPEC Coremark
?
The Mobile Device Virtuous Cycle
23
Mobile DeviceArchitectureApplicationsEnd
Users
Satisfaction Power Consumption
Perfo
rman
ce
Feat
ures
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Capabilities
The Mobile Device Virtuous Cycle
23
Mobile DeviceArchitectureApplicationsEnd
Users
Satisfaction Power Consumption
Perfo
rman
ce
Feat
ures
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Capabilities
The Mobile Device Virtuous Cycle
24
Mobile DeviceArchitectureApplicationsEnd
Users
Satisfaction Power Consumption
Perfo
rman
ce
Feat
ures
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Capabilities
Question #2: Does mobile CPU performance matter to user satisfaction?
Peak CPU Frequency
Max CPU Cores Enabled
Peak GPU Frequency
CPUFrequency
CPU CoreCount
GPUFrequency
Record User Interaction Parameterized Replay Publish Replay Crowdsourced User Survey
SurveyAnalysis
YouTubeHosting
Survey MonkeyA/B Testing
ScreenRecording
RERAN Replay Tool
User InteractionEvent Stream
AmazonMechanical Turk
Crowdsourced-based User Satisfaction Study
25
Peak CPU Frequency
Max CPU Cores Enabled
Peak GPU Frequency
CPUFrequency
CPU CoreCount
GPUFrequency
Record User Interaction Parameterized Replay Publish Replay Crowdsourced User Survey
SurveyAnalysis
YouTubeHosting
Survey MonkeyA/B Testing
ScreenRecording
RERAN Replay Tool
User InteractionEvent Stream
AmazonMechanical Turk
Crowdsourced-based User Satisfaction Study
Over 20,000 “end-users”
25
Peak CPU Frequency
Max CPU Cores Enabled
Peak GPU Frequency
CPUFrequency
CPU CoreCount
GPUFrequency
Record User Interaction Parameterized Replay Publish Replay Crowdsourced User Survey
SurveyAnalysis
YouTubeHosting
Survey MonkeyA/B Testing
ScreenRecording
RERAN Replay Tool
User InteractionEvent Stream
AmazonMechanical Turk
Crowdsourced-based User Satisfaction Study
Over 20,000 “end-users”
$0.10 a task
25
Peak CPU Frequency
Max CPU Cores Enabled
Peak GPU Frequency
CPUFrequency
CPU CoreCount
GPUFrequency
Record User Interaction Parameterized Replay Publish Replay Crowdsourced User Survey
SurveyAnalysis
YouTubeHosting
Survey MonkeyA/B Testing
ScreenRecording
RERAN Replay Tool
User InteractionEvent Stream
AmazonMechanical Turk
Crowdsourced-based User Satisfaction Study
Over 20,000 “end-users”
$0.10 a task
1 day25
Crowdsourced-based User Satisfaction Study
26
Crowdsourced-based User Satisfaction Study
1. Very dissatisfied
2. Dissatisfied
3. Neutral
4. Satisfied
5. Very satisfied
26
Crowdsourced-based User Satisfaction Study
1. Very dissatisfied
2. Dissatisfied
3. Neutral
4. Satisfied
5. Very satisfied
26
Crowdsourced-based User Satisfaction Study
1. Very dissatisfied
2. Dissatisfied
3. Neutral
4. Satisfied
5. Very satisfied
26
Bridging the Long-standing Void Between CPU Design Decisions and End-user Satisfaction
27
“Is High Single-Thread Performance Required?”
28
“Is High Single-Thread Performance Required?”
▸ Bursty behavior in mobile applications can impact end-user satisfaction
28
“Is High Single-Thread Performance Required?”
▸ Bursty behavior in mobile applications can impact end-user satisfaction
28
“Is High Single-Thread Performance Required?”
▸ Bursty behavior in mobile applications can impact end-user satisfaction
28
“Is High Single-Thread Performance Required?”
▸ Bursty behavior in mobile applications can impact end-user satisfaction
28
▸ Slow login results in abandonment of app service
“Does Multi-core Performance Matter?”
▸ Angry Birds needs very little performance from the hardware
29
Angry Birds (2009)
“Does Multi-core Performance Matter?”
▸ Angry Birds needs very little performance from the hardware
29
Angry Birds (2009) Photoshop (2014)
▸ Photoshop benefits from having multiple cores for performance
“Does Multi-core Performance Matter?”
▸ Angry Birds needs very little performance from the hardware
29
Angry Birds (2009) Photoshop (2014)
▸ Photoshop benefits from having multiple cores for performance
“Does Multi-core Performance Matter?”
▸ Angry Birds needs very little performance from the hardware
29
Angry Birds (2009) Photoshop (2014)
▸ Photoshop benefits from having multiple cores for performance
“Isn’t Mobile GUI Based (i.e., GPU Heavy)?”
30
“Isn’t Mobile GUI Based (i.e., GPU Heavy)?”
▸ Yes and No, it depends
▸ User satisfaction indicates that GPUs are heavily over provisioned
31
Back to Benchmarking Mobile CPU Performance
32
?What’s the Next Killer App?
Looking Beyond Current Generation Workloads
▸ Low user satisfaction
▸ High core count, high frequency degrades satisfaction
33
Face detection (e.g. NameTag)
▸ Was using dual-core ARM Cortex A9 processors based on 45nm
Looking Beyond Current Generation Workloads
▸ Low user satisfaction
▸ High core count, high frequency degrades satisfaction
33
Face detection (e.g. NameTag)
▸ Was using dual-core ARM Cortex A9 processors based on 45nm
Considering the Mobile Device Virtuous Cycle
34
Mobile DeviceArchitectureApplicationsEnd
Users
Satisfaction Power Consumption
Perfo
rman
ce
Feat
ures
Pow
er, E
nerg
y &
Ther
mal
Budg
ets
Capabilities
Question #3: Can future mobile CPUs be energy-efficient and deliver performance?
Power and Cooling Impose Severe Limitations
▸ Mobile system TDP is around 3.5 ~ 5 Watts
▸ Full utilization of CPU cores can lead to excessive power consumption
▸ Offloading computation to GPU can lead to additional power consumption
35
10x103
8
6
4
2
0
Pow
er (m
W)
SoCComponents
System TDP
Others500 mW
A7796 mW
A156268 mW
GPU2770 mW
Emerging Programming Paradigms are Likely to Force Us to Hit those Peak Functionalities
36
10x103
8
6
4
2
0
Pow
er (m
W)
SoCComponents
System TDP
Others500 mW
A7796 mW
A156268 mW
GPU2770 mW
Emerging Programming Paradigms are Likely to Force Us to Hit those Peak Functionalities
36
10x103
8
6
4
2
0
Pow
er (m
W)
SoCComponents
System TDP
Others500 mW
A7796 mW
A156268 mW
GPU2770 mW
RenderScript
MARE Runtime
SIMD.js
Battery Imposes Severe Energy Constraints
37
3500
3000
2500
2000
1500
1000
Batt
ery
Capa
city
(mAh
)
6.56.05.55.04.54.03.53.02.52.01.5
Screen Size (inches)
Battery Imposes Severe Energy Constraints
38
3500
3000
2500
2000
1500
1000
Batt
ery
Capa
city
(mAh
)
6.56.05.55.04.54.03.53.02.52.01.5
Screen Size (inches)
2006-2009
Battery Imposes Severe Energy Constraints
39
3500
3000
2500
2000
1500
1000
Batt
ery
Capa
city
(mAh
)
6.56.05.55.04.54.03.53.02.52.01.5
Screen Size (inches)
2006-2009 2010-2011
Battery Imposes Severe Energy Constraints
40
3500
3000
2500
2000
1500
1000
Batt
ery
Capa
city
(mAh
)
6.56.05.55.04.54.03.53.02.52.01.5
Screen Size (inches)
2006-2009 2010-2011 2012-2013
3500
3000
2500
2000
1500
1000
Batt
ery
Capa
city
(m
Ah)
6.56.05.55.04.54.03.53.02.52.01.5
Screen Size (inches)
2006-2009 2010-2011 2012-2013
Droid (2009)
Galaxy S (2010)
Galaxy N (2011)
Galaxy S3 (2012)
Galaxy S4 (2013)
Battery Imposes Severe Energy Constraints
41
3500
3000
2500
2000
1500
1000
Batt
ery
Capa
city
(m
Ah)
6.56.05.55.04.54.03.53.02.52.01.5
Screen Size (inches)
2006-2009 2010-2011 2012-2013
Droid (2009)
Galaxy S (2010)
Galaxy N (2011)
Galaxy S3 (2012)
Galaxy S4 (2013)
Battery Imposes Severe Energy Constraints
41
3500
3000
2500
2000
1500
1000
Batt
ery
Capa
city
(m
Ah)
6.56.05.55.04.54.03.53.02.52.01.5
Screen Size (inches)
2006-2009 2010-2011 2012-2013
Droid (2009)
Galaxy S (2010)
Galaxy N (2011)
Galaxy S3 (2012)
Galaxy S4 (2013)
Battery Imposes Severe Energy Constraints
41
3500
3000
2500
2000
1500
1000
Batt
ery
Capa
city
(m
Ah)
6.56.05.55.04.54.03.53.02.52.01.5
Screen Size (inches)
2006-2009 2010-2011 2012-2013
Droid (2009)
Galaxy S (2010)
Galaxy N (2011)
Galaxy S3 (2012)
Galaxy S4 (2013)
Battery Imposes Severe Energy Constraints
41
3500
3000
2500
2000
1500
1000
Batt
ery
Capa
city
(m
Ah)
6.56.05.55.04.54.03.53.02.52.01.5
Screen Size (inches)
2006-2009 2010-2011 2012-2013
Droid (2009)
Galaxy S (2010)
Galaxy N (2011)
Galaxy S3 (2012)
Galaxy S4 (2013)
Battery Imposes Severe Energy Constraints
41
3500
3000
2500
2000
1500
1000
Batt
ery
Capa
city
(m
Ah)
6.56.05.55.04.54.03.53.02.52.01.5
Screen Size (inches)
2006-2009 2010-2011 2012-2013
Droid (2009)
Galaxy S (2010)
Galaxy N (2011)
Galaxy S3 (2012)
Galaxy S4 (2013)
Battery Imposes Severe Energy Constraints
41
54% of end users preferred size
Unsustainable Desktop Processor Techniques
▸ Mobile CPUs have been borrowing desktop techniques over the recent several years
▸ Mobile CPUs are far from delivering desktop-level performance because of stringent power, thermal and energy constraints
4
3
2
1
0
Cloc
k Fr
eque
ncy
(GHz
)
2006
2007
2008
2009
2010
2011
2012
2013
2014
Year
Desktop Mobile
213
29
25
21Cach
e Si
ze (
KB)
2006
2007
2008
2009
2010
2011
2012
2013
2014
Year
L1: Both L2: Mobile L2: Desktop L3: Desktop
8
6
4
2
0
Core
Cou
nt
2006
2007
2008
2009
2010
2011
2012
2013
2014
Year
Desktop Mobile
100
101
102
103
104
SPEC
Sco
re
2006
2007
2008
2009
2010
2011
2012
2013
2014
Year
Desktop
Mobile
bzip2 gcc libquantum omnetpp
Comparing against data from Stanford’sCPU DB: http://cpudb.stanford.edu/
How Do We Design the Next Mobile CPU?
Homogenous CMP Simple cores
Homogenous CMP Complex cores
Heterogenous CMP Specialized Accelerators
?X XX X
43
44
Solutions
44
Utilization
Solutions
44
Utilization
Heterogeneity Heterogeneous
Hardware
EventQueue H3 … H2 … H1 Dispatch
<Core, Freq>
PI, PU
Detector
QoSMonitor
ModelConstructor
Recalibrate
Event-Based Scheduler
Event Info
Models
onkeyup=“H1 () {…}”
keyup
onchange=“H2 () {…}”
change
Event execution feedback
onclick=“H3 () {…}”
click
Solutions
44
Utilization
Heterogeneity Heterogeneous
Hardware
EventQueue H3 … H2 … H1 Dispatch
<Core, Freq>
PI, PU
Detector
QoSMonitor
ModelConstructor
Recalibrate
Event-Based Scheduler
Event Info
Models
onkeyup=“H1 () {…}”
keyup
onchange=“H2 () {…}”
change
Event execution feedback
onclick=“H3 () {…}”
click
Customization
Solutions
44
Utilization
Heterogeneity Heterogeneous
Hardware
EventQueue H3 … H2 … H1 Dispatch
<Core, Freq>
PI, PU
Detector
QoSMonitor
ModelConstructor
Recalibrate
Event-Based Scheduler
Event Info
Models
onkeyup=“H1 () {…}”
keyup
onchange=“H2 () {…}”
change
Event execution feedback
onclick=“H3 () {…}”
click
Specialization... ... Rule j
... ...
Prop l
... ...
scratchpad mem(input)
Rule i.id
... Prop m ... Prop k ...
Rule j.id
...
...
... ... ...scratchpad mem(output)
start end start end
Rule i
Prop kProp m Prop mProp l
computelanes
Style l Style m Style k
conflictresolution
Customization
Solutions
44
Utilization
Heterogeneity Heterogeneous
Hardware
EventQueue H3 … H2 … H1 Dispatch
<Core, Freq>
PI, PU
Detector
QoSMonitor
ModelConstructor
Recalibrate
Event-Based Scheduler
Event Info
Models
onkeyup=“H1 () {…}”
keyup
onchange=“H2 () {…}”
change
Event execution feedback
onclick=“H3 () {…}”
click
Specialization... ... Rule j
... ...
Prop l
... ...
scratchpad mem(input)
Rule i.id
... Prop m ... Prop k ...
Rule j.id
...
...
... ... ...scratchpad mem(output)
start end start end
Rule i
Prop kProp m Prop mProp l
computelanes
Style l Style m Style k
conflictresolution
Customization
Solutions
Utilization
45
Workload Characterization
Performance/Energy Analysis and Prediction
Resource Allocation and Mapping
Taking Web Browsing as an Example
46
A Case for Heterogeneity
47
A9 1.2GHz
A9 920MHz
A9 700MHz
A9 350MHz
A8 800MHz
A8 600MHz A8 300MHz
www.autoblog.comDifferent operating frequencies
47
A Case for Heterogeneity
47
A9 1.2GHz
A9 920MHz
A9 700MHz
A9 350MHz
A8 800MHz
A8 600MHz A8 300MHz
www.autoblog.comDifferent operating frequencies
47
A Case for Heterogeneity
47
A9 1.2GHzwww.autoblog.com
Different operating frequencies
47
A Case for Heterogeneity
47
A9 1.2GHzwww.autoblog.com
Different operating frequencies
47
A Case for Heterogeneity
47
A9 1.2GHzwww.autoblog.com
www.newegg.com Different operating frequencies
47
A Case for Heterogeneity
47
A9 1.2GHzwww.autoblog.com
www.newegg.com Different operating frequencies
47
A Case for Heterogeneity
47
A9 1.2GHzwww.autoblog.com
www.newegg.com
A9 700MHz
Different operating frequencies
47
A Case for Heterogeneity
47
A9 1.2GHzwww.autoblog.com
www.newegg.com
A9 700MHz
~40%
Different operating frequencies
47
A Case for Heterogeneity
48
www.adobe.com
Different operating frequencies
A Case for Heterogeneity
48
www.adobe.com
Different operating frequencies
A8 600MHz
A Case for Heterogeneity
48
www.adobe.com
Different operating frequencies
Different uarchitectures
A8 600MHz
A Case for Heterogeneity
49
Different operating frequencies
Different uarchitectures
www.adobe.com
www.newegg.com
www.autoblog.com
A Case for Heterogeneity
49
“Webpages variance” in load time and energy
Different operating frequencies
Different uarchitectures
www.adobe.com
www.newegg.com
www.autoblog.com
Scheduling Results
50
Cut-o
ff Vi
olat
ions
(%)
Ener
gy S
aving
s (%
)
Scheduling Results
50
0
25
50
75
100
0
10
20
30
40
OS (Big) OS (Little) WS
Cut-o
ff Vi
olat
ions
(%)
Ener
gy S
aving
s (%
)
Using a performance strategy as the baseline
(Big+Little)
Thank You
51