mobile, the driving force for tomorrow - arm architecture · pdf filemobile, the driving force...

Title 44pt Title Case

Affiliations 24pt sentence case

20pt sentence case

© ARM 2016

Mobile, The Driving Force for Tomorrow - Technologies for Greener, Faster, and Smarter

ARM Tech Forum 2016 – Taipei

July 1st 2016

Ivan H.P. Lin

Sr. Segment Marketing Manager, ARM

© ARM 2016 2


Bullets 24pt sentence case

Sub-bullets 20pt sentence case

3Bn ARM powered

smartphones in

use today

Smartphones: The World’s Primary Compute Device

The

smartphone

means so many

things to so

many people

© ARM 2016 3




Consumers Love Their Smartphone

and Want More From Their Next Smartphone

Battery-

life

Connectivity Multi-

media

Build and

Design

Camera

Trust and

Security

Fluid user

experience

© ARM 2016 4




Continuous Journey of Evolution and Revolution

Camera evolution,

capturing what you

see and want

Vulkan graphics API Computer vision

True wireless device

Never touches a wire

Cortex A72 big.LITTLE in

$200 smartphones

Security for your physical

and digital life

Path to 5G for

consistent connected

experience

Multiscreen support –

Desktop or TV

USB-C allowing you

to connect to all your

peripherals

Sustained compute for

virtual reality and

”AAA” Gaming

© ARM 2016 6




The “Mobile Envelope”

= fundamental constraints of a smartphone form factor

Power Budget

Thermal Budget

Memory Budget

© ARM 2016 7




Mobile Envelope Factors

Mechanics

Reduction in Z height

Shrinking of the bezel

Choice of materials

Battery size

Camera

More sensors

More demanding sensors

Complex multi channel ISP’s

Use cases

Full 4K features

Increased photography compute

CV

Memory

Use cases driving B/W usage

Bandwidth vs power

Modem

Nx Carrier aggregation = N live radios

Physical RF challenges

Computational complexity increasing

Data usage increasing

And more

Increased sensing

PMIC

Video

© ARM 2016 8




Evolution of The Premium Smartphone

Shrinking form factors

Increasing demand for

more efficient compute

More challenging heat dissipation

HTC

Nexus One

11.5mmç

New features

42% more screen

to body

since 2010

More

processing

2010 2012 2014 2016

Mate 8

7.9mm

Galaxy S3

8.6mm Lumia 1520

8.4mm

55%

screen to

body ratio

78%

screen to

body ratio

45% thinner

since 2010

© ARM 2016 9




Evolving Challenges of Premium Smartphones

Innovation continues to drive performance

AR/VR, Ultra-HD visualization, Object-based audio processing

Thinner designs with longer battery life

Challenge: Thermal constraints and limited battery capacity

User experience is the ultimate metric

Standard benchmarks paint a partial picture

3D/360°

Video LTE Advanced

5G

AR/VR >20MP

Camera

4k/8k

Display Need for Sustained Performance with High Efficiency

© ARM 2016 10




How Did We Meet Consumer’s Expectations ?

24x Higher screen

resolution

5x Increase in

environmental

sensors

100x Higher compute

performance

20x Increase in

connectivity

300x Higher GPU

performance

Today’s high-end phone compared to 2009

In order for smartphone innovation to continue

ARM needs to continue to delivering “more for less”

© ARM 2016 11




ARM® Cortex® -A Portfolio

ARMv8-A ARMv7-A

Cortex-A9

Well established mid-range

processor used in many markets

Cortex-A5 Smallest and lowest power

ARMv7-A CPU, optimized for single-core

Cortex-A32

Smallest and lowest power

ARMv8-A

High

Performance

High

Efficiency

Ultra High

Efficiency

Cortex-A15

High-performance with infrastructure

feature set

Cortex-A17 High-performance with lower power and smaller area

relative to Cortex-A15

Cortex-A7 Most efficient

ARMv7-A CPU, higher

performance than Cortex-A5

Cortex-A57

Proven high-performance

Cortex-A73

2017 Premium Mobile,

Consumer

Cortex-A53

Balanced performance and

efficiency

big.LITTLE compatible Key:

Cortex-A35

Highest efficiency

Cortex-A72

2016 Premium Mobile, Enterprise & Auto

64/32-bit 64/32-bit

64/32-bit

64/32-bit

32-bit 64/32-bit

Cortex-A8

First ARMv7-A processor

© ARM 2016 12




Thermal Throttling and the Impact on Performance

1550MHz

1229MHz

69°C

62°C

44

52

60

68

400

800

1200

1600

Tem

pera

ture

(°C

)

Fre

quency

(M

Hz)

big CPU Frequency LITTLE CPU Frequency SoC Temperature

-20% Frequency

impact

Normal Operation

Thermally Saturated

Measured on Cortex-A57/A53 device, Geekbench v3 ST

Device Temperature indicative only

Long-run thermal saturation impacts overall system performance

-25% System

Performance

Impact

Device

Temperature

© ARM 2016 13




0

1

2

3

4

5

6

0

1

2

3

4

5

6

More Performance, Less Power R

ela

tive

vs

Cort

ex-A

7

Power consumption measured in mW/unit performance

Performance measured as single thread at-speed

Cortex-A15 Cortex-A57 Cortex-A72 Cortex-A73

Accelerated growth in

Performance/Cycle

Delivered performance

Continuous reduction

in power consumption

and

Continuous

improvement

in power

efficiency

contributing

to a longer

battery life

Cortex-A15 Cortex-A57 Cortex-A72 Cortex-A73

© ARM 2016 15




Cortex-A57

20nm @ 1.9GHz

Cortex-A72

16nm @ 2.5GHz

Cortex-A73

10nm @ 2.8GHz

Rela

tive

Perf

orm

ance

Cortex-A73: Maximizes Performance

Cortex-A73 sustains peak performance within per-core power budget

Sust

ained ≈

Peak

2.1x

1.3x Sust

ained

Peak

Sust

ained

Peak

2015 2016 2017

Cortex-A57 20nm @ 1.9GHz



Sustained operation within 750mW per-core power budget

As measured on Spec2k

© ARM 2016 16




Cortex-A73: Power Efficiency Benefit

0.0x

0.5x

1.0x

Integer Floating Point L2 Cache Memory Copy

Power Relative to Cortex-A72

(ISO-process, ISO-frequency)

Cortex-A72 Cortex-A73

Giving additional thermal

headroom for the rest of the SOC

>20% Power Saved

© ARM 2016 18




1.0x

1.3x

1.9x

Octa-core

Cortex-A53 (4L+4L)

Hexa-core

Cortex-A73+Cortex-A53 (2b+4L)

1.0x 1.0x 1.0x

Cortex-A73: Boost your Mid-range Smartphone

Enhanced user experience

Best response time

≈

+30% Multi-core

Performance

+90% Single-thread

Performance

Implemented on the same process technology

Same area footprint

More performance, same footprint

© ARM 2016 19




Architecturally Identical Processors

High Performance ‘big’ and High Efficiency ‘LITTLE’ cores

big CPUs deliver higher single thread performance

LITTLE CPUs deliver higher energy efficiency

Seamless & Automatic Task Allocation

Assigns low intensity tasks to the LITTLE cores and high intensity

tasks to the big cores

Thread migration is typically faster than DVFS

Heterogeneous Computing

Efficient handling of single and multi-threaded applications

Scalable to multiple clusters with Cache Coherent Interconnect

big.LITTLE Technology

L2 Cache L2 Cache

Cache Coherent Interconnect

Interrupt Control

big Cluster LITTLE

Cluster

1 2

Relative big. LITTLE Power*

Cortex-A57

Cortex-A53

Cortex-A15

Cortex-A7

Further

power

reductions

* Measured average power across high and low intensity workloads on big.LITTLE-based smartphones

© ARM 2016 21




big.LITTLE MP

Delivers higher power efficiency

Extends battery life

Improves user experience

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

Cluster Migration

big.LITTLE MP

Power

Measured Power and Performance on big.LITTLE Devices

(big.LITTLE MP relative to Cluster Migration)

-29% -38% +20%

+60%

Performance

Web

Browsing

Intensive

Gaming

Web Browsing

Intensive

Gaming (Lower is Better) (Higher is Better)

© ARM 2016 22




High

Mid

Low

WFI / Power Down

Category 2

Sustained Performance

at Thermal Limit

Category 3

Long-use Low-Intensity

Workloads

Category 1

Burst High Intensity Workloads

Measured on a Quad Cortex-A7 Symmetric Multiprocessing platform

Applications require a mix of performance levels

Mobile users want a better user experience but not at a cost of reduced battery life

Example: Web Browsing

Example: Castlemaster

Example: Audio Playback

Mobile Application Workloads Perc

enta

ge o

f Tim

e S

pent

in

DV

FS S

tate

s

© ARM 2016 23




SoC

ARM Intelligent Power Allocation (IPA)

Tdie

Tskin Power to Heat

SoC

Device

IPA

Elements:

Proactive temperature control

big LITTLE GPU

Real time CPU & GPU

Real-time CPU & GPU

Performance requests

requests Performance Requests

Power estimation

Dynamic power allocation

big LITTLE GPU

Dynamic Allocation by:

Performance required

Thermal headroom ation by:

•Performance required

•Thermal headroom

Allocated Performance

© ARM 2016 24




Intelligent Power Allocation in Action

Device temperature is below threshold

There are no constraints on power / performance

Every actor runs at max required frequency

Median filtered chart for clarity

Runnin

g

Fre

quency

Three consecutive runs of GLB TRex

Time

Max “big” freq

“big” running freq

Max “LITTLE” freq

“LITTLE” running freq

Max GPU freq

GPU running freq

© ARM 2016 25





High load on GPU & low load on CPU

GPU gets allocated most of the power


Runnin

g

Fre

quency


Time

Max “big” freq




Max GPU freq

GPU running freq

© ARM 2016 26




Runnin

g

Fre

quency


Time

Max “big” freq




Max GPU freq

GPU running freq



High load on CPU & low load on GPU

CPU gets allocated most of the power

© ARM 2016 27




Runnin

g

Fre

quency


Time

Max “big” freq




Max GPU freq

GPU running freq



Device temperature gets hotter

IPA reduces available power to actors

This maintains temperature control

© ARM 2016 28





0

10

20

30

40

1st Run 2nd Run 3rd Run Average

IPA

vs. T

radit

ional

(Rela

tive

Perf

orm

ance

)

13% Improvement

34% Improvement

36% Improvement

28% Improvement


Runnin

g

Fre

quency


Time

Max “big” freq




Max GPU freq

GPU running freq

© ARM 2016 30




EAS – Energy Aware Scheduler

Compute capacity

(Performance)

Capacity Utilization

0 1 2 3

Max capacity big

Waking task

?

CPU

cluster little big

Current

capacity

Max capacity little

Placing task on cpu1:

P-state change for

cpu0 and cpu1.

Placing task on cpu3:

No P-state changes.

CPU 0, 1

CPU 2, 3

Little

core

Big core

Power

CONFIDENTIAL 31

LTE Global Market Through 2020

Source: GSMA

1.3 Billion LTE Connections by end of 2016

Strong WW growth of LTE expected, establishing it as the dominant access technology

FDD is prevalent, but TDD growing to 25% share by 2020

Huge backlog of new features in 3GPP, very strong LTE roadmap

© ARM 2016 32




The Demand for Faster Connectivity

© ARM 2016 33




Deployment

Deployment

5G Modem Development Timeline

5G Goals

Ultra reliable, low latency

Large scale IoT deployment

Enhanced mobile broadband

Showing specification freeze to first deployment

2014 2015 2016 2017 2018 2019 2020 2021 2022

LTE Advanced

Development

LTE Advanced

Pro

Development

5G wave 2

Development

5G wave 1

Development

Modem design

starts in 2016

600 Mbps

> 10 Gbps Deployment

Deployment

2023 2024

© ARM 2016 34




3GPP 4G Evolution…. the path to 5G

Higher levels of carrier aggregation leading to much higher aggregate throughputs

Complex MIMO and higher order modulation to increase spectral efficiencies

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Release 8 Release 9 Release 10 Release 11 Release 12 Release 13 Release 14

LTE LTE-Advanced LTE-A… the path to 5G

300 Mbps 450 Mbps 600 Mbps 1Gbps +

OFDMA / MIMO 256 QAM 5G mm Wave

Small Cell/ Femto Cell/Hetnet Single Cell Point to Multi-Point

2CA 21 new combinations up

to 2 CA

114 new combinations

up to 3CA

52 new (190 total)

combinations up to 4CA Up to 32CA in discussion

Multimedia Broadcast/Multicast Services (MBMS)

LTE-Unlicensed (Licensed Assisted Access) / Wi-Fi co-existence (LTE-H)

LTE-MTC Enhancements to LTE-MTC

Device to Device (D2D) D2D enhancements inc push to talk

2D Antenna Array MIMO Interference cancellation

Indoor Positioning Location Services

© ARM 2016 35




‘LTE-Advanced Pro’ – The Stepping Stone To 5G LTE

Unlicensed

Carriers are aggregated for increased throughput

WiFi LTE Carriers 5G Carriers

LTE

Unlicensed WiFi LTE Carriers LTE Carriers

LTE

Advanced LTE Advanced-Pro

5G

50x throughput*

From LTE to 5G

* ARM Estimate, LTE Rel 8 to 5G wave 2

© ARM 2016 36

CONFIDENTIAL

CONFIDENTIAL

CONFIDENTIAL

Supporting All Connectivity Standards

ARM cores enable all major wireless connectivity standards from Bluetooth-LE through LTE-A towards 5G

Cortex-R8 processor extends support to new performance points to Gbps LTE-A & 5G

802.11ah ‘HaLow’, LTE Cat-M and NB-IOT brings new ultra low power requirements to wide area networks

11a/b

11 g

11 n

11 ac

11 ad

10Mbps

100Mbps

1Gbps

10Gbps

1Mbps

100Kbps

ARM7TDMI®

Cortex-M0

Cortex-M3

Cortex-R4

Cortex-R5

Cortex-R4

Cortex-R5

Cortex-M7

3.5G

LTE-M &

NB-IOT

3G

3.9G

4G

ARM11 ™

Cortex-R4

Cortex-M

ARM9™

ARM11™

Cortex-R4

Cortex-R5

Cortex-R7

Established

Emerging

Cortex-M0+

Cortex-M3

Cortex-R8 4.5G & 5G

802.11ah

BT4.0

BT-LE

© ARM 2016 37




Sensor Hubs ..... Everywhere

With the explosion of sensors in devices coupled with always-on operation we are seeing an explosion of

sensor hub applications

Sensor Hub is rapidly establishing as a platform for innovation and differentiation

Healthcare Mobile

Tablet

Wearables

Fitness

TV

Sensor Hubs Enable....

Always on sensor monitoring

‘smart’ data fusion

Combined multi-data pattern recognition

New use cases such as contextual awareness

© ARM 2016 38




Always Sensing, Always On, Always Aware

API Application

Processor

Always Aware

Temperature

GPS

Magnetometer

Accelerometer

Gyroscope

Touch

Microphone

Luminance

Cortex-M

Sensor Hub

Smart Analog Sensor Fusion

© ARM 2016 40




Application

Processor

GSM / CDMA

Transceiver

GPS

Receiver

Touch Screen

Controller

Audio

Processor

PMIC

Mic

Sensor Hub

Image

Processor

Acc Gyr Mag

Cam

NFC

Transceiver

WiFi

Bluetooth

Bar ALS

Touch

Prox

24/7 in mobile – sensor hub

Wearable

Benefits:

• Ultra Low Power Consumption

• Always On Capability

Advanced Context

Awareness

Activity Monitoring

Pedestrian Dead Reckoning

Power Control, Etc …

Distributed Sensor Hub Bus will increase sensor fusion

innovation and the need for more intelligence at the sensor level

© ARM 2016 41




More Intelligence – The New Paradigm Shift

Speech recognition

Home security

Machine Translation

Face and Object Recognition

© ARM 2016 42




Smartphone: The Portal to Future Innovation

Machine

Learning &

Computer

Vision

Consumer

IOT / Smart

home

Virtual and

Augmented

Reality

Always-on

Digital

Assistants

© ARM 2016 43




Summary

Premium mobile user experience demands

Thinner devices + Lower power budgets + More performance

ARM Cortex-A73 delivers sustained peak performance in the mobile power budget

30% more performance, 30% more power efficiency

Delivers increased performance range for premium mobile and large screen devices

Cortex-A73 with big.LITTLE delivers improved scalable performance

Boost for the mid-range smartphone and a broad range of consumer applications

LTE-A and LTE-A Pro Paving the Path Toward 5G

Cortex-R8 Extends ARM’s Real-time Leadership for Future Connectivity

Connected Intelligence the Trends for Future Mobile

MEMS Sensor and Sensor Fusion the Fundamental Building Blocks for Contexture Awareness

Cortex-M provides saleable and first-in-class solution

ARM Provides Comprehensive System Solution for Future Mobiles

The trademarks featured in this presentation are registered and/or unregistered trademarks of ARM Limited

(or its subsidiaries) in the EU and/or elsewhere. All rights reserved. All other marks featured may be

trademarks of their respective owners.

Copyright © 2016 ARM Limited

© ARM 2016

mobile, the driving force for tomorrow - arm architecture · pdf filemobile, the driving force...

Documents