The document discusses ARM's Intelligent Power Allocation (IPA) technology, which aims to maximize performance within thermal limits. It describes three types of power consumption scenarios and the limitations of the current Linux thermal framework. IPA uses a closed-loop control system to dynamically allocate power between components like the CPU and GPU based on temperature, power estimates, and performance requests. Test results show IPA achieving up to 31% higher FPS in games compared to static thermal policies, with more consistent temperature control.

1. 1
ARM
Intelligent Power Allocation

2. Agenda
 Background and Motivation
 What is ARM Intelligent Power Allocation?
 Results
 Status and Conclusions
2

3. Power Consumption Scenarios
1. Short term responsiveness
3
 Power consumption allowed to significantly
exceed sustainable max power of the SoC for
relatively short periods
 E.g. Web Browsing, UI update, HDR processing
(first few shots)
2. Sustained workload
 Goal is to maximise performance at, or within,
the sustainable power envelope
 Adapt performance allocation to major power
consuming entities
 E.g. Gaming, long benchmarks, video processing
Power/Performance
3. Energy constrained use cases
Max Sustainable Power
 Operates ‘under the radar’ of intelligent power allocation
 E.g. low power audio
The illustration to the right depicts 3
distinct types of power consumption:
A successful thermal management scheme will
maximize the user experience for types1 and 2.
Time
Burst for
responsiveness
Sustained
performance
Power Optimised
Low End
T >= Tjmax, Tskin
1 2 3

4. Power Consumption Scenarios
1. Short term responsiveness
4
 Power consumption allowed to significantly
exceed sustainable max power of the SoC for
relatively short periods
 E.g. Web Browsing, UI update, HDR processing
(first few shots)
2. Sustained workload
 Goal is to maximise performance at, or within,
the sustainable power envelope
 Adapt performance allocation to major power
consuming entities
 E.g. Gaming, long benchmarks, video processing
Power/Performance
3. Energy constrained use cases
Max Sustainable Power
 Operates ‘under the radar’ of intelligent power allocation
 E.g. low power audio
The illustration to the right depicts 3
distinct types of power consumption:
A successful thermal management scheme will
maximize the user experience for types1 and 2.
Time
Burst for
responsiveness
Sustained
performance
Power Optimised
Low End
T >= Tjmax, Tskin
1 2 3

5. Power Consumption Scenarios
1. Short term responsiveness
5
 Power consumption allowed to significantly
exceed sustainable max power of the SoC for
relatively short periods
 E.g. Web Browsing, UI update, HDR processing
(first few shots)
2. Sustained workload
 Goal is to maximise performance at, or within,
the sustainable power envelope
 Adapt performance allocation to major power
consuming entities
 E.g. Gaming, long benchmarks, video processing
Power/Performance
3. Energy constrained use cases
Max Sustainable Power
 Operates ‘under the radar’ of intelligent power allocation
 E.g. low power audio
The illustration to the right depicts 3
distinct types of power consumption:
A successful thermal management scheme will
maximize the user experience for types1 and 2.
Time
Burst for
responsiveness
Sustained
performance
Power Optimised
Low End
T >= Tjmax, Tskin
1 2 3

6. Power Consumption Scenarios
1. Short term responsiveness
6
 Power consumption allowed to significantly
exceed sustainable max power of the SoC for
relatively short periods
 E.g. Web Browsing, UI update, HDR processing
(first few shots)
2. Sustained workload
 Goal is to maximise performance at, or within,
the sustainable power envelope
 Adapt performance allocation to major power
consuming entities
 E.g. Gaming, long benchmarks, video processing
Power/Performance
3. Energy constrained use cases
Max Sustainable Power
 Operates ‘under the radar’ of intelligent power allocation
 E.g. low power audio
The illustration to the right depicts 3
distinct types of power consumption:
A successful thermal management scheme will
maximize the user experience for types1 and 2.
Time
Burst for
responsiveness
Sustained
performance
Power Optimised
Low End
T >= Tjmax, Tskin
1 2 3

7. Power Consumption Scenarios
1. Short term responsiveness
7
 Power consumption allowed to significantly
exceed sustainable max power of the SoC for
relatively short periods
 E.g. Web Browsing, UI update, HDR processing
(first few shots)
2. Sustained workload
 Goal is to maximise performance at, or within,
the sustainable power envelope
 Adapt performance allocation to major power
consuming entities
 E.g. Gaming, long benchmarks, video processing
Power/Performance
3. Energy constrained use cases
Max Sustainable Power
 Operates ‘under the radar’ of intelligent power allocation
 E.g. low power audio
The illustration to the right depicts 3
distinct types of power consumption:
A successful thermal management scheme will
maximize the user experience for types1 and 2.
Time
Burst for
responsiveness
Sustained
performance
Power Optimised
Low End
T >= Tjmax, Tskin
1 2 3

8. Current Linux Thermal Framework
 Thermal ‘trip’ mechanism
 Designed to turn on fans, and/or reduce operating
frequency
 Activates on temperature overshoot
 Does not accommodate power partitioning
between different parts of SoC: GPU, CPU, DSP, video
 Reactive and static
8
Trip2
Trip1

9. IPA Thermal Management technology
 Proactive vs. Reactive Thermal Management
9
 Fixed response to temperature crossing a threshold (Reactive) vs. continuously adapting response
based on power consumption and thermal headroom (Proactive)
 Static vs. Dynamic Partitioning
 A fixed policy for each component based on prior knowledge of its power consumption vs. a
dynamic policy that takes into account component behaviour over time
 Maximising performance within thermal limits is critical
 Closed-loop control to dynamically allocate power budget, taking into
account:
 Thermal headroom
 Real-time performance requirements

10. Agenda
 Background and Motivation
 What is ARM Intelligent Power Allocation?
 Results
 Status and Conclusions
10

11. ARM Intelligent Power Allocation
11
SoC
SoC
big LITTLE GPU
IPA
Tdie
Tskin
Performance Requests
big LITTLE GPU
Allocated Performance
Power to Heat
Real-time CPU & GPU
Performance requests
Elements:
•Temperature control
• Power estimation
• Performance allocation
Dynamic Allocation by:
•Performance required
•Thermal headroom

12. Thermal Management Approach
12
Actors
Power
Arbiter
Perf
metrics
CPU
Power model
Power
Estimate
Perf
request
Delta
Power
Estimate
Granted Performance
Perf
metrics
GPU
Power model
Power
Estimate
Perf
request
Delta
Power
Estimate
Granted Performance
Perf
metrics
…
Power model
Power
Estimate
Perf
request
Delta
Power
Estimate
Granted Performance
Policy
Config
Temp.
Monitor
Central Arbiter performs two
tasks:
1.Keeps system within thermal envelope
 Proactive power budget via closed loop
control
 Exploits thermal headroom
2.Dynamic power allocation per actor
based on
 Performance demand
 Power models
PID
Power
arbitration

13. PID Controller and Power Allocation
13
control_temp
∂e
∂t x
K_po/pu
S
tdp
-Temp
Performance Requests
Power
Allocation
Pmax
Performance Granted
e
x
K_i
x S
Actor 1 … Actor N
I
P
-rest_of_soc_power
∫e
K_d
D
S Actor1..N weight
Actor1..N maxpower
Actor 1 … Actor N
PID – Controller
Provides a power budget, based
on current and control temp

14. PID Controller and Power Allocation
14
control_temp
∂e
∂t x
K_po/pu
S
tdp
-Temp
Performance Requests
Power
Allocation
Pmax
Performance Granted
e
x
K_i
x S
Actor 1 … Actor N
I
P
-rest_of_soc_power
∫e
K_d
D
S Actor1..N weight
Actor1..N maxpower
Actor 1 … Actor N
Power Allocation based on:
 Requested performance
 Power budget
 Policy
Produces final output power

15. Agenda
 Background and Motivation
 What is ARM Intelligent Power Allocation?
 Results
 Status and Conclusions
17

16. Configuration
 Platform: Odroid XU3: 4xA15, 4xA7 ARM Mali-T628
 Aims:
18
 Target control temperature 65oC
 Critical temperature 69oC
Static policy:
 GPU:
 4 Trip points, one for each frequency
 At each trip point, max frequency is reduced
 Trips at 56, 57, 58, 59 oC
 A15/A7:
 3 trip points at 60, 62, 64 oC
IPA:
 Control temp = 65 oC
 Hotplug actioned if reached 69oC
 Higher priority for A7

17. Intelligent Power Allocation on Games
19
31% higher FPS
with IPA
Unity the Chase:
Enlighten Transporter:
8% higher FPS
with IPA
T/˚C
T/˚C
Time
Time

18. Intelligent Power Allocation SOLID Temperature Control
Unity the Chase:
T/˚C
Enlighten Transporter:
T/˚C
20

19. % Improvement on Consecutive Benchmark Runs IPA vs. Static
21

20. Intelligent Power Allocation in Action
 IPA dynamically allocates power to CPU clusters or GPU, based on load
 Temperature determines available power
22
 You set Temperature, IPA caps Frequencies
 Load determines how power is divided between CPUs (big and LITTLE) and GPU
Median filtered chart for clarity
Max OPP big
Max OPP LITTLE
Max OPP GPU
Running Frequency
Time (s)
GLB Trex HD [3 Runs] 
big

LITTLE

GPU

21. Intelligent Power Allocation in Action
 IPA dynamically allocates power to CPU clusters or GPU, based on load
 Temperature determines available power
 Load determines how power is divided between CPUs (big and LITTLE) and GPU
23
 You set Temperature, IPA caps Frequencies
Median filtered chart for clarity
Max OPP big
Max OPP LITTLE
Max OPP GPU
Device is still cool
There are no constraints on frequency
Every actor runs at max frequency
Running Frequency
Time (s)
GLB Trex HD [3 Runs]

big

LITTLE

GPU

22. Intelligent Power Allocation in Action
 IPA dynamically allocates power to CPU clusters or GPU, based on load
 Temperature determines available power
 Load determines how power is divided between CPUs (big and LITTLE) and GPU
24
 You set Temperature, IPA caps Frequencies
Median filtered chart for clarity
High load on GPU
Low load on CPU
GPU gets most of the power
Max OPP big
Max OPP LITTLE
Max OPP GPU
Running Frequency
Time (s)
GLB Trex HD [3 Runs]

big

LITTLE

GPU

23. Intelligent Power Allocation in Action
 IPA dynamically allocates power to CPU clusters or GPU, based on load
 Temperature determines available power
 Load determines how power is divided between CPUs (big and LITTLE) and GPU
25
 You set Temperature, IPA caps Frequencies
Median filtered chart for clarity
Max OPP big
Max OPP LITTLE
Max OPP GPU
High load on CPU
Low load on GPU
CPU gets most of the power
Running Frequency
Time (s)

big

LITTLE

GPU
GLB Trex HD [3 Runs]

24. Intelligent Power Allocation in Action
 IPA dynamically allocates power to CPU clusters or GPU, based on load
 Temperature determines available power
 Load determines how power is divided between CPUs (big and LITTLE) and GPU
26
 You set Temperature, IPA caps Frequencies
Median filtered chart for clarity
Max OPP big
Max OPP LITTLE
Max OPP GPU
As the device gets hotter
IPA reduces available power to actors
to maintain temperature control
Running Frequency
Time (s)
GLB Trex HD [3 Runs]

big

LITTLE

GPU

25. Agenda
 Background and Motivation
 What is ARM Intelligent Power Allocation?
 Results
 Status and Conclusions
27

26. IPA upstreaming – Status
 ARM has produced a Linux OS implementation of IPA
28
 Demonstrates key concepts and shows benefit on real workloads
 ARM contributing IPA to Linux kernel
 RFCs have been sent to linux-pm
 Latest: v5 RFC: https://lkml.org/lkml/2014/7/10/365
 Supported by Mali DDK
 Check out IPA code for ARM Juno release (includes GPU integration)
 https://git.linaro.org/landing-teams/working/arm/kernel-release.git
(tag ‘lsk-3.10-armlt-juno-20140924’)
 http://releases.linaro.org/14.09/members/arm/android/images/armv8-android-juno-lsk
 Upstream timescales are subject to variation, depending on community feedback
 ARM, Linaro, ARM partners all contributing & reviewing

27. Conclusions
 ARM Intelligent Power Allocation is designed to maximise performance in the
thermal envelope:
29
 Proactively adjusts available power budget, based on device temperature
 Allocates power dynamically among actors, based on performance demand
 ARM Intelligent Power Allocation shows solid thermal control and better
performance than existing Linux thermal framework
 We are providing Intelligent Power Allocation to the community to as baseline for
best-in-class thermal management

28. 30
Thank You
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