Mobile CPU's Rise to Power: Quantifying the Impact of Generational Mobile CPU Design
Trends on Performance, Energy, and User Satisfaction
Matthew Halpern Yuhao Zhu Vijay Janapa ReddiDept. of Electrical and Computer Engineering
The University of Texas at Austin 1
2
2
Snake 2000
2
Snake 2000
Snake Simulator 2016
2
3
Mobile Device
Touchscreen
3
Mobile Device
Touchscreen Cellular WiFI Bluetooth
3
Mobile Device
Touchscreen Cellular WiFI Bluetooth
Camera
3
Mobile Device
Touchscreen Cellular WiFI Bluetooth
GPSCamera Sensors Battery
3
Mobile Device
System-On-A-Chip
Touchscreen Cellular WiFI Bluetooth
GPSCamera Sensors Battery
3
Mobile Device
System-On-A-Chip
4
System-On-A-Chip
4
System-On-A-Chip
CPU
4
System-On-A-Chip
CPU
GPU
4
System-On-A-Chip
CPU
GPU
Accelerators
4
System-On-A-Chip
CPU
Network-On-ChipGPU
Accelerators
4
System-On-A-Chip
CPU
Network-On-ChipGPU
Accelerators
CPU
4
Nor
mal
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ARM
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hare
(%)
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60
80
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Year2009 2010 2011 2012 2013 2014 2015
ARM11 A8 A5 A9 A15 A7 A53 A57
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Nor
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ARM
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hare
(%)
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20
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60
80
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Year2009 2010 2011 2012 2013 2014 2015
ARM11 A8 A5 A9 A15 A7 A53 A57
5
Nor
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ARM
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hare
(%)
0
20
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60
80
100
Year2009 2010 2011 2012 2013 2014 2015
ARM11 A8 A5 A9 A15 A7 A53 A57
5
Nor
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ARM
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(%)
0
20
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Year2009 2010 2011 2012 2013 2014 2015
ARM11 A8 A5 A9 A15 A7 A53 A57
5
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ARM
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(%)
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20
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Year2009 2010 2011 2012 2013 2014 2015
ARM11 A8 A5 A9 A15 A7 A53 A57
5
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hare
(%)
0
20
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60
80
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Year2009 2010 2011 2012 2013 2014 2015
ARM11 A8 A5 A9 A15 A7 A53 A57
5
Nor
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ARM
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hare
(%)
0
20
40
60
80
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Year2009 2010 2011 2012 2013 2014 2015
ARM11 A8 A5 A9 A15 A7 A53 A57
5
Nor
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ARM
Mar
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hare
(%)
0
20
40
60
80
100
Year2009 2010 2011 2012 2013 2014 2015
ARM11 A8 A5 A9 A15 A7 A53 A57
5
Nor
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ARM
Mar
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hare
(%)
0
20
40
60
80
100
Year2009 2010 2011 2012 2013 2014 2015
ARM11 A8 A5 A9 A15 A7 A53 A57
5
Nor
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ARM
Mar
kets
hare
(%)
0
20
40
60
80
100
Year2009 2010 2011 2012 2013 2014 2015
ARM11 A8 A5 A9 A15 A7 A53 A57
Mobile CPU design is fast-paced.
5
Conventional Research Scope
6
HardwareSoftware
Conventional Research Scope
6
HardwareSoftware
Bottlenecks
Conventional Research Scope
6
HardwareSoftware
Performance
Bottlenecks
Conventional Research Scope
6
HardwareSoftware
Performance
Bottlenecks
Conventional Research Scope
6
HardwareSoftware
Performance
Bottlenecks
Conventional Research Scope
6
HardwareSoftware
Perf
orm
ance
Bottlenecks
Expanding the Research Scope
7
HardwareSoftware ProcessorApplications
Perf
orm
ance
Bottlenecks
Expanding the Research Scope
7
HardwareSoftware ProcessorApplications
Perf
orm
ance
Bottlenecks
Expanding the Research Scope
Conventional Research Scope
7
HardwareSoftware ProcessorApplicationsEnd-Users
Perf
orm
ance
Bottlenecks
Expanding the Research Scope
Conventional Research Scope
7
HardwareSoftware ProcessorApplicationsEnd-Users
Perf
orm
ance
BottlenecksFe
atur
es
Expanding the Research Scope
Conventional Research Scope
7
HardwareSoftware ProcessorApplicationsEnd-Users
SatisfactionPe
rfor
man
ce
BottlenecksFe
atur
es
Expanding the Research Scope
Conventional Research Scope
7
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
SatisfactionPe
rfor
man
ce
BottlenecksFe
atur
es
Expanding the Research Scope
Conventional Research Scope
7
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
SatisfactionPe
rfor
man
ce
Pow
er B
udge
ts
BottlenecksFe
atur
es
Expanding the Research Scope
Conventional Research Scope
7
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
SatisfactionPe
rfor
man
cePower Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
Expanding the Research Scope
Conventional Research Scope
7
Our Scope
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
SatisfactionPe
rfor
man
cePower Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
Expanding the Research Scope
7
Characterize how the interactions between mobile CPU, end-user, and
mobile device have changed over time through real-world measurement
8
Characterize how the interactions between mobile CPU, end-user, and
mobile device have changed over time through real-world measurement
1. Has mobile CPU efficiency improved?
8
Characterize how the interactions between mobile CPU, end-user, and
mobile device have changed over time through real-world measurement
1. Has mobile CPU efficiency improved?2. Have mobile CPU advancements
improved end-user satisfaction?
8
Characterize how the interactions between mobile CPU, end-user, and
mobile device have changed over time through real-world measurement
1. Has mobile CPU efficiency improved?2. Have mobile CPU advancements
improved end-user satisfaction?3. How has the rest of the mobile device
evolved around the CPU?8
Characterize how the interactions between mobile CPU, end-user, and
mobile device have changed over time through real-world measurement
9
Characterize how the interactions between mobile CPU, end-user, and
mobile device have changed over time through real-world measurement
9
Capturing Real-world Mobile CPU Trends from Off-the-Shelf Smartphones
10
Samsung Galaxy
S6
Samsung Galaxy
S5
Samsung Galaxy
S4
Samsung Galaxy
S3
Samsung Galaxy Nexus
Samsung Galaxy
S
2015201420132012201120102009
Motorola Droid
Capturing Real-world Mobile CPU Trends from Off-the-Shelf Smartphones
10
11
Capturing Real-world Mobile CPU Trends from Off-the-Shelf Smartphones
Year 2009 2010 2011 2012 2013 2014 2015
11
Capturing Real-world Mobile CPU Trends from Off-the-Shelf Smartphones
Year 2009 2010 2011 2012 2013 2014 2015uArch A8 A8 A9 A9 A15 A15 A57
11
Capturing Real-world Mobile CPU Trends from Off-the-Shelf Smartphones
Year 2009 2010 2011 2012 2013 2014 2015uArch A8 A8 A9 A9 A15 A15 A57
Process 65 nm 45 nm 32 nm 28 nm 28 nm 28 nm 14 nm
11
Capturing Real-world Mobile CPU Trends from Off-the-Shelf Smartphones
Year 2009 2010 2011 2012 2013 2014 2015uArch A8 A8 A9 A9 A15 A15 A57
Process 65 nm 45 nm 32 nm 28 nm 28 nm 28 nm 14 nmFreq 0.6 GHz
GHz1 GHz 1.2 GHz
GHGHz1.4 GHz
GHz1.6 GHz
GHz2.1 GHz
GHz2.1 GHz
GHz
11
Capturing Real-world Mobile CPU Trends from Off-the-Shelf Smartphones
Year 2009 2010 2011 2012 2013 2014 2015uArch A8 A8 A9 A9 A15 A15 A57
Process 65 nm 45 nm 32 nm 28 nm 28 nm 28 nm 14 nmFreq 0.6 GHz
GHz1 GHz 1.2 GHz
GHGHz1.4 GHz
GHz1.6 GHz
GHz2.1 GHz
GHz2.1 GHz
GHzCores 1 1 2 4 4 (+4) 4 (+4) 4 (+4)
11
Capturing Real-world Mobile CPU Trends from Off-the-Shelf Smartphones
Year 2009 2010 2011 2012 2013 2014 2015uArch A8 A8 A9 A9 A15 A15 A57
Process 65 nm 45 nm 32 nm 28 nm 28 nm 28 nm 14 nmFreq 0.6 GHz
GHz1 GHz 1.2 GHz
GHGHz1.4 GHz
GHz1.6 GHz
GHz2.1 GHz
GHz2.1 GHz
GHzCores 1 1 2 4 4 (+4) 4 (+4) 4 (+4)L1 I$ 32 KB 32 KB 32 KB 32 KB 32 KB 32 KB 48 KBL1 D$ 32 KB 32 KB 32 KB 32 KB 32 KB 32 KB 32 KBLLC 256 KB 512 KB 1 MB 2 MB 2 MB 2 MB 2 MB
DRAM 256 MB 512 MB MB
1 GB 1 GB 2 GB 2 GB 3 GB11
Capturing Real-world Mobile CPU Trends from Off-the-Shelf Smartphones
Has mobile CPU efficiency improved?
12
Performance
Power
Energy
Has mobile CPU efficiency improved?
12
Substantial Performance Improvements
13
Spee
dup
1
3
5
7
9
11
13
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC
Substantial Performance Improvements
13
Spee
dup
1
3
5
7
9
11
13
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC
Substantial Performance Improvements
13
Spee
dup
1
3
5
7
9
11
13
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC
Substantial Performance Improvements
13
Spee
dup
1
3
5
7
9
11
13
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC
Substantial Performance Improvements
What are the key architectural contributors?
13
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
A8
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
A832-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-Issue
A832-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-IssueIn-Order
A832-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-IssueIn-Order
A8 A932-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-IssueIn-Order Out-of-Order
A8 A932-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-IssueIn-Order Out-of-Order
A8 A9 A1532-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-Issue Triple-IssueIn-Order Out-of-Order
A8 A9 A1532-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-Issue Triple-IssueIn-Order Out-of-Order Aggressive Out-of-Order
A8 A9 A1532-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-Issue Triple-IssueIn-Order Out-of-Order Aggressive Out-of-Order
A8 A9 A15
Aggressive Mem Hierarchy
32-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-Issue Triple-IssueIn-Order Out-of-Order Aggressive Out-of-Order
A8 A9 A15 A57
Aggressive Mem Hierarchy
32-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-Issue Triple-IssueIn-Order Out-of-Order Aggressive Out-of-Order
A8 A9 A15 A57
Aggressive Mem Hierarchy
32-bit 64-bit
Speedup = IPC Speedup x Clock Speedup
14
Spee
dup
1
2
3
4
5
Year2009 2010 2011 2012 2013 2014 2015
Frequency IPC
Dual-Issue Triple-IssueIn-Order Out-of-Order Aggressive Out-of-Order
A8 A9 A15 A57
Aggressive Mem Hierarchy
32-bit 64-bit
Aggressive core scaling techniques have provided mobile CPUs substantial performance improvements.
Speedup = IPC Speedup x Clock Speedup
14
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
65 nm
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
65 nm 45 nm
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
65 nm 45 nm
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
65 nm 45 nm 32 nm
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
65 nm 45 nm 32 nm
HKMG
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
65 nm 45 nm 28 nm32 nm
HKMG
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
65 nm 45 nm 28 nm 14nm32 nm
HKMG
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
65 nm 45 nm 28 nm 14nm32 nm
HKMG
Memory Activity
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
65 nm 45 nm 28 nm 14nm32 nm
HKMG
Single-core Thermal Design Point
Memory Activity
Excessive Power Consumption
15
Pow
er (m
W)
0
500
1000
1500
2000
2500
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
In-Order Out-of-Order Aggressive Out-of-OrderA8 A9 A15 A57
65 nm 45 nm 28 nm 14nm32 nm
HKMG
Single-core Thermal Design Point
Memory Activity
Mobile CPUs designs are beginning to approach a power wall.
Excessive Power Consumption
15
16
Nor
mal
ized
Ener
gy
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
16
Nor
mal
ized
Ener
gy
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
16
Nor
mal
ized
Ener
gy
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
16
Nor
mal
ized
Ener
gy
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
Peak Energy Efficiency
16
Nor
mal
ized
Ener
gy
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Year2009 2010 2011 2012 2013 2014 2015
Coremark SPEC Bleh
Peak Energy Efficiency
Mobile CPU performance improvements are in an era of energy efficiency stagnation.
16
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
SatisfactionPe
rfor
man
cePower Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
Incorporating the End-User
17
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
Satisfaction Perf
orm
ance
Power Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
Incorporating the End-User
17
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
Satisfaction Perf
orm
ance
Power Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
Incorporating the End-User
17
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
Satisfaction Perf
orm
ance
Power Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
Incorporating the End-User
?17
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
Satisfaction Perf
orm
ance
Power Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
Incorporating the End-User
17
Have mobile CPU advancements improved end-user satisfaction?
18
Have mobile CPU advancements improved end-user satisfaction?
1. Is single-core performance necessary?
18
Have mobile CPU advancements improved end-user satisfaction?
1. Is single-core performance necessary?2. Is multi-core performance necessary?
18
Have mobile CPU advancements improved end-user satisfaction?
1. Is single-core performance necessary?2. Is multi-core performance necessary?3. Does graphics performance matter more
than CPU performance?
18
Studying user satisfaction requires users
19
Studying user satisfaction requires users
19
LOTS^
Leveraging the Crowd to Achieve Scale
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Leveraging the Crowd to Achieve Scale
Over 25,000 participants!
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Survey Design
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Survey Design
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Survey Design
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Survey Design
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Emulating the Mobile CPU Evolution
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Emulating the Mobile CPU Evolution
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Emulating the Mobile CPU Evolution
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422 729 1036 1497 1958 2457
S5 Clock Frequency
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Emulating the Mobile CPU Evolution
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S5 Clock Frequency
S5 C
ores
Ena
bled
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Putting the Pieces TogetherRecord User Parametrized Replay Post Survey Crowdsource
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Putting the Pieces TogetherRecord User Parametrized Replay Post Survey Crowdsource
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Putting the Pieces TogetherRecord User Parametrized Replay Post Survey Crowdsource
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Putting the Pieces Together
CPU Frequency
CPU Cores
GPU Frequency
Record User Parametrized Replay Post Survey Crowdsource
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Putting the Pieces TogetherRecord User Parametrized Replay Post Survey Crowdsource
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Putting the Pieces TogetherRecord User Parametrized Replay Post Survey Crowdsource
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Putting the Pieces TogetherRecord User Parametrized Replay Post Survey Crowdsource
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Putting the Pieces TogetherRecord User Parametrized Replay Post Survey Crowdsource
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Putting the Pieces TogetherRecord User Parametrized Replay Post Survey Crowdsource
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Putting the Pieces TogetherRecord User Parametrized Replay Post Survey Crowdsource
23
Do we need single-core performance?
24
Do we need single-core performance?
24
Do we need single-core performance?
24
Do we need single-core performance?
24
Do we need single-core performance?
24
Do we need single-core performance?
24
Do we need single-core performance?
24
Do we need single-core performance?
24
Do we need single-core performance?
24
Do we need single-core performance?
24
Do we need single-core performance?
24
User satisfaction is latency-critical. Single-core CPU performance enhancements have been crucial to the end-user.
Do we need multi-core performance?
25
Do we need multi-core performance?
25
Do we need multi-core performance?
25
Do we need multi-core performance?
25
Do we need multi-core performance?
25
Do we need multi-core performance?
25
Do we need multi-core performance?
25
Do we need multi-core performance?
25
Do we need multi-core performance?
25
Do we need multi-core performance?
25
Do we need multi-core performance?
25
Multi-threading is being used for user-critical functionalities. Multiple CPU cores can provide benefit to the end user.
Does graphics performance matter more than CPU performance?
26
Does graphics performance matter more than CPU performance?
26
Does graphics performance matter more than CPU performance?
26
Does graphics performance matter more than CPU performance?
26
Does graphics performance matter more than CPU performance?
26
Does graphics performance matter more than CPU performance?
26
Does graphics performance matter more than CPU performance?
26
Does graphics performance matter more than CPU performance?
26
Does graphics performance matter more than CPU performance?
Even amongst applications that make use of the GPU and other accelerators, end-users are sensitive to CPU performance.
26
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
SatisfactionPe
rfor
man
cePower Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
At the Mercy of Power Constraints
27
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
Satisfaction Perf
orm
ance
Power Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
At the Mercy of Power Constraints
27
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
Satisfaction Perf
orm
ance
Power Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
At the Mercy of Power Constraints
27
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
Satisfaction Perf
orm
ance
Power Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
At the Mercy of Power Constraints
27
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
Satisfaction Perf
orm
ance
Power Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
At the Mercy of Power Constraints
27
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
Satisfaction Perf
orm
ance
Power Consumption
Pow
er B
udge
ts
BottlenecksFe
atur
es
At the Mercy of Power Constraints
27
How has the rest of the mobile device evolved around the CPU?
28
Sharing the Power Budget: Device-level
29
Pow
er (w
atts
)
0
2
4
6
8
Year
2009 2010 2011 2012 2013 2014 2015
Display RadioCPU: Single-core CPU: Multi-core
Sharing the Power Budget: Device-level
29
Pow
er (w
atts
)
0
2
4
6
8
Year
2009 2010 2011 2012 2013 2014 2015
Display RadioCPU: Single-core CPU: Multi-core
Sharing the Power Budget: Device-level
29
Pow
er (w
atts
)
0
2
4
6
8
Year
2009 2010 2011 2012 2013 2014 2015
Display RadioCPU: Single-core CPU: Multi-core
Sharing the Power Budget: Device-level
29
Pow
er (w
atts
)
0
2
4
6
8
Year
2009 2010 2011 2012 2013 2014 2015
Display RadioCPU: Single-core CPU: Multi-core
Sharing the Power Budget: Device-level
29
Pow
er (w
atts
)
0
2
4
6
8
Year
2009 2010 2011 2012 2013 2014 2015
Display RadioCPU: Single-core CPU: Multi-core
Sharing the Power Budget: Device-level
29
Pow
er (w
atts
)
0
2
4
6
8
Year
2009 2010 2011 2012 2013 2014 2015
Display RadioCPU: Single-core CPU: Multi-core
Thermal Throttling
Sharing the Power Budget: Device-level
29
Mobile SoC: Unsustainable By Design
30
Repo
rted
TDP
(wat
ts)
0
3
6
9
12
Phone
Galaxy S5 Galaxy S6
CPU: A15 CPU: A7 GPU Other
Mobile SoC: Unsustainable By Design
30
Repo
rted
TDP
(wat
ts)
0
3
6
9
12
Phone
Galaxy S5 Galaxy S6
CPU: A15 CPU: A7 GPU Other
Mobile SoC: Unsustainable By Design
30
Repo
rted
TDP
(wat
ts)
0
3
6
9
12
Phone
Galaxy S5 Galaxy S6
CPU: A15 CPU: A7 GPU Other
Mobile SoC: Unsustainable By Design
30
Repo
rted
TDP
(wat
ts)
0
3
6
9
12
Phone
Galaxy S5 Galaxy S6
CPU: A15 CPU: A7 GPU Other
Mobile SoC: Unsustainable By Design
30
Repo
rted
TDP
(wat
ts)
0
3
6
9
12
Phone
Galaxy S5 Galaxy S6
CPU: A15 CPU: A7 GPU Other
Mobile SoC: Unsustainable By Design
30
Repo
rted
TDP
(wat
ts)
0
3
6
9
12
Phone
Galaxy S5 Galaxy S6
CPU: A15 CPU: A7 GPU Other
3.5 W TDP Budget
Mobile SoC: Unsustainable By Design
30
HardwareSoftware Mobile DeviceProcessorApplicationsEnd-Users
SatisfactionPe
rfor
man
cePower Consumption
Pow
er B
udge
ts
CapabilitiesFe
atur
es
Tying It All Together
31
A Call to Action
Mobile Device
Processor
Applications
End-Users
32
A Call to ActionUse metrics that incorporate end-user
Mobile Device
Processor
Applications
End-Users
32
A Call to ActionUse metrics that incorporate end-user
Mobile Device
Processor
Applications
End-Users
Identify user-critical application segments
32
A Call to ActionUse metrics that incorporate end-user
Understand application characteristics
Mobile Device
Processor
Applications
End-Users
Identify user-critical application segments
32
A Call to ActionUse metrics that incorporate end-user
Understand application characteristics
Deviate from desktop scaling and embrace the era specialization
Mobile Device
Processor
Applications
End-Users
Identify user-critical application segments
32
A Call to ActionUse metrics that incorporate end-user
Understand application characteristics
Deviate from desktop scaling and embrace the era specialization
Consider thermal and energy constraints at the mobile-device level
Mobile Device
Processor
Applications
End-Users
Identify user-critical application segments
32
Thank You!
33
8
6
4
2
0
Cor
e C
ount
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Year
213
29
25
21
Cac
he S
ize
(KB)
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Year
L1: Both L2: Mobile L2: Desktop L3: Desktop
5
4
3
2
1
0Clo
ck F
requ
ency
(GH
z)
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Year
Desktop-like CPU Scaling
Clock Scaling Resource Scaling Core Scaling
34
Other Applications
Application Selection Criteria
http://www.anandtech.com/show/9780/taking-notes-with-ipad-pro/2
Apple SoCs
http://www.anandtech.com/show/9686/the-apple-iphone-6s-and-iphone-6s-plus-review/4
Apple CPUs
http://techreport.com/r.x/2014_8_11_Nvidia_claims_Haswellclass_performance_for_Denver_CPU_core/denver-block.jpg
Crowdsourcing Considerations
Crowdsourcing Considerations
Crowdsourcing Considerations
Task Design
Crowdsourcing Considerations
Task Design▹ Open-ended question
Crowdsourcing Considerations
Task Design▹ Open-ended question
▹ Well-defined answers
Crowdsourcing Considerations
Task Design▹ Open-ended question
▹ Well-defined answers Worker Recruitment and Incentive
Crowdsourcing Considerations
Task Design▹ Open-ended question
▹ Well-defined answers Worker Recruitment and Incentive▹ $0.10 / task
Crowdsourcing Considerations
Task Design▹ Open-ended question
▹ Well-defined answers Worker Recruitment and Incentive▹ $0.10 / task
▹ $8.00 / hour wage
Crowdsourcing Considerations
Task Design▹ Open-ended question
▹ Well-defined answers Worker Recruitment and Incentive▹ $0.10 / task
▹ $8.00 / hour wageData Integrity
Crowdsourcing Considerations
Task Design▹ Open-ended question
▹ Well-defined answers Worker Recruitment and Incentive▹ $0.10 / task
▹ $8.00 / hour wageData Integrity▹ Scale of trials (> 50 trials / configuration)
Crowdsourcing Considerations
Task Design▹ Open-ended question
▹ Well-defined answers Worker Recruitment and Incentive▹ $0.10 / task
▹ $8.00 / hour wageData Integrity▹ Scale of trials (> 50 trials / configuration)
▹ Validation keyword prevents scripters
Phone Mapping
Other CPUs and Benchmarks: Perf
11
9
7
5
3
1
Nor
mal
ized
Spe
edup
D S N S3 S4 S5 S6Smartphone Model
SPEC Coremark Sunspider Geekbench Stream
Stock IP Custom IP
Other CPUs and Benchmarks: Power
2.5
2.0
1.5
1.0
0.5
0.0
Dyn
amic
Pow
er (W
)
D S N S3 S4 S5 S6Smartphone Model
Other CPUs and Benchmarks: Energy
1.0
0.8
0.6
0.4
0.2
0.0
Nor
mal
ized
Ene
rgy
D S N S3 S4 S5 S6Smartphone Model