February 22nd, 2017 l JIN KIM l Samsung Electronics

Memory innovation for embedded vision systems

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Disclaimer

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Contents

• Vision IoT, divergence

• Embedded vision memory

‒ Auto/VR/Mobile

• Innovative memory solutions

• Summary

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Vision IoT, divergence

5/20

To divergence

DIVERGENCE CONVERGENCE

• Better smartphone UX with vision IoTs

• Need divergence of vision IoT

6/20

Changing role, enriching mobile eco

Service

Intelligent Hub

Data Explosion

6 10 15

22

31

'15 '16 '17 '18 '19 '20

10X

Data Generation

& Distribution Personalization

Cloud

Data Analytics, Deep Learning

Source: Global Mobile Data Traffic, CISCO’16

Active Interaction

7/20

For artificial intelligence, On-device • On-device service expansion

‒ Privacy/security/picture quality On-device A.I.(deep learning)

‒ Energy-efficiency/high-bandwidth/low-latency

Accuracy(# of layers)

Coverage

(10 layers)

(8 layers)

Object detect Medical

Natural Language

Audio

Translation

Self-Drive

Face pay

Number

Recognition

Cloud service

On-device service

Recommend

Super resolution

4-layer 5-layer 6-layer

8/20

Embedded vision memory : Auto/VR/Mobile

9/20

Vision IoT, more memory

Influence level

on memory Imaging

(CIS+memory)

Recognition (SoC+memory)

A.I. (Cloud+memory)

Wearable ★ ★

Automotive ★★ ★★ ★★★★

Camera ADAS ★★ ★★★

IP camera ★★ ★★

Robot/Drone ★ ★★ ★★★

Gateway/Edge ★ ★★

Cellular IoT/M2M ★

Smart Home ★ ★ ★

Retail ★ ★

Automotive

ADAS

Tele-

matics

Info/

Cluster

IP CAM

Smart

Gateway

Robotics

Drone

Smart Home

Thermo

-stat

Appliance Wearable

IoT (50B unit)

100M

C-IoT/

M2M

Retail

• Vision for Imaging Vision for Sensing and A.I.

• Top 10 IoT applications, driving memory consumption

Imaging: improved picture quality/high speed shooting/continuous shooting Recognition: 3D mapping/multi-camera/object/motion/biometrics/face recognition A.I.: autonomous/emotion recognition/disease diagnosis/VR

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Automotive, evolving fast

0

20

40

60

'12 13 '14 15 '16 17

Mobile

Auto

0

2

4

6

8

10

'12 13 '14 15 '16 17

Mobile

Auto

DRAM Bandwidth DRAM Capacity

GB/s GB

Vision

Sensor

D/L Data

Processing

100

50

200

[GB/s]

300

‘21 ‘17 ‘19

OS , Apps

D/L Weight

8x

Number of objects to recognize

40ea(’13) ▶ 1,000ea (’18)

Bandwidth for Compute ADAS

• Autonomous driving adoption, faster than expected

• Compute ADAS drives high B/W (object detection/scene seg./depth extraction)

Source: Samsung

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VR, high-performance & low-power • VR now : FHD 90fps, MTP* latency(~50ms), 2D audio VR sickness

• Immersive VR : 160FoV, 8K120fps, MTP(~20ms), 360 audio

Enthusiastic Game

Professional/Industrial

Military/Health Care

Education/Retail

VR Cinema

360 Video Streaming

Casual Game

8K120 streaming, ~51.2GB/s

4GB+

8K120 commercial, ~150GB/s

8GB+

8K120 gaming, 1TB+/s

16GB+

Teth

ere

d

All

In

On

e

Dro

p I

n

4K65 4K75 4K120 8K60 4K90

Display

17 13 9 11 Latency

’16 ’17 ’18 ’19 ’20

ms

TDP

[Watt]

100 300 200

All-in-One

Tethered

LP4/5(~34GB/s)

HBM2/GD6(~500GB/s)

LP5/WIO(~60GB/s)

GP

U [T

FL

OP

S]

8

3

1

∬

Drop-In

fps

Performance

Low

Power

10

<9

*MTP: Motion To Photon

Type & DRAM Requirements VR Ecosystem Readiness

Source: Samsung

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Mobile, overcoming technology barrier

SOC Performance DRAM Performance

0.1

1

10

100

‘10 ‘12 ‘14 ‘16

(log)

‘18

Be

nch

ma

rk S

co

re (

3D

gra

ph

ic)

0

1.6

3.2

4.8

'10 '12 '14 '16 '18

Gbps

Time

‘12 ‘14 ‘16

• Need performance, but can’t increase it

Source: Samsung

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Memory technology trend

Power Efficiency

[mW/GBps]

100%

80%

60%

40%

20%

2020 2016 2018

Performance

[Gbps/pin] 15

12

6

3

LP5

LP4X LP4

2016 2018 2020

DDR4

9

DDR5

GDDR5

LP4

• GDDR6 with over 14Gbps, beyond 10Gbps GDDR5

• LP5, 20% more power-efficient than LP4X

LP5

GDDR6

DDR5

LP4X

GDDR5

DDR4

LP3

DDR3

Source: Hotchips2016, Samsung

GDDR6

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Innovative memory solutions

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High Bandwidth Memory: HBM

PCB

DRAM

Buffer Logic Processor

Si Interposer

HBM

TSV Technology

1,024 I/O Architecture

Benefits

Microbump

8H stacked 20nm 8GB HBM

HBM

GDDR5

X 0.8

Power Efficiency

High Bandwidth 1TB/s

X 2.7

Performance

HBM

GDDR5

Source: Samsung

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3D/2.5D SiP memory PKG • Mobile, small F/F, high-speed, low-power requirement 3D/2.5D SiP PKG

• Close collaboration with SoC

Stacked FBGA

FOPLP

Dual Flip Chip

2.5D Si Interposer

3D SiP

Performance

Form Factor

time

SiP

PoP

Wire Bump FOPLP TSV

Mobile Memory SVR/Gfx Memory

time

TSV

Wire

/FPGA

Wire/FBGA FC/TSV High-IO Interposer

High IO TSV (HBM)

Interposer Based Platform

DDR TSV

FC-CSP

Stacked FBGA

BOC

interposer Performance

Source: Samsung

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A.I. mobile memory

[ source : ISSCC]

DDR Main Memory (DDR4/5)

PCIeGen-Z/CCIX/CAPI

Accelerator (GPU/FPGA/ASIC)

CPU

NPU

HBMs

LPDDR Main Memory (LP4/5)

AMBA/AHB

Accelerator (DSP/VPU/NPU)

AP

A.I . mem

iGPU iGPU

Inference (DSP/NPU/VPU) Training

(GPU/FPGA/ASIC) Trained

model

Output

Energy efficient solution requirement

Dedicated H/W (accelerator + memory)

• Vision IoT requires A.I. specific memory

‒ Deep-learning/parallel/inference processing

Deep-learning on IoT device

Source: Samsung

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Memory-stacked Photography • Require DSLR-level performance (dual camera/pixel and high-speed shooting)

• Chance to processing in stacked memory

‒ Low power, thermal spread, super resolution, real time HDR and slow motion control

Source: ISSCC 2017, Sony

e.g. data rate control, high speed read-out, multi stream output, high speed binning

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PIM for embedded vision IoT • Added value from reduced power consumption

‒ Reduce the unnecessary data transfer and frame rate control

• Possible collaboration with SoC/AP

AP CIS Display

AMBA AHB

Display

CIS AP

Added Value Memory B/W Traffic

VPU

Recognition Distortion FRC Correction

Pre/Post Processing In Memory

Source: Samsung

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Summary

• Smartphone as a Intelligent Hub will continue to enrich mobile ecosystem

‒ Performance never be enough in mobile. The more we have, the better we use

‒ Mobile challenges with power optimization and continued innovation

• High performance, more memory are needed in embedded vision IoT

‒ Automotive ADAS drives high bandwidth memory

‒ Immersive VR requires high-performance and low-power

‒ Mobile memory is getting more power-efficient

• Close collaboration is essential

‒ Keeps innovating technology to correspond to the requirements

‒ Artificial Intelligent memory, CIS stacked memory, Vision processing in memory