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Community works for

multi-core
embedded
image processing
Nov. 2, 2013 KELP
Jeong-pyo Kong / ntekLogic
jpkong@gmail.com
Agenda
1. Why we do this?
2. Technical backgrounds
3. Coworking with ETRI, KESSIA

4. Current our works
5. Future of our works
OpenSEED imageA 2
1. WHY WE DO THIS?

OpenSEED imageA 3
IT trends are changing
quite quickly

OpenSEED imageA 4
40 Gadgets

8 Imaging
6 Gaming
α

http://www.wired.com/magazine/2013/04/convergence/

Convergence
OpenSEED imageA 5
Connected world

Wearable

Big data

IoT/M2M
http://press.teleinteractive.net/media/blogs/tialife/InternetofThingsVector.svg

OpenSEED imageA 6
Computational world

UAV

Robot
Autonomous
Vehicle
OpenSEED imageA 7
http://www.slideshare.net/robman/divergence-what-happens-after-convergence

Divergence
OpenSEED imageA 8
Appropriate Technology
for IT business environment

OpenSEED imageA 9
Problem solving
•
•
•
•

Complex problem -> Complex solution
Complex problem -> Simple solution
Simple problem -> Complex solution
Simple problem -> Simple solution

OpenSEED imageA 10
http://www.youtube.com/watch?v=nrWfLAh2T3k

OpenSEED imageA 11
What we thought
• Interesting image processing and
connected world
• Let’s assume if we can do below things
– Using improved hardware
– Improving (for example)
• Response time to 30%
• Power saving to 15%
• Accurate rate to 10%

Isn’t it
a big deal?

OpenSEED imageA 12
Is it a chance for us?
• Many changes are
hidden from
ordinary people,
usually
• Next generation infra
• Eco system
OpenSEED imageA 13
So, what is the result of our
works?

OpenSEED imageA 14
1. why we do this?

2. TECHNICAL BACKGROUNDS

OpenSEED imageA 15
Requirements for
embedded image processing

OpenSEED imageA 16
System components
• Input

– Image sensor
– Video files on local storage
– Network streaming

• Processing

– ISP
– Low/high level image processing application

• Output

– Display, Signal
– Network streaming
OpenSEED imageA 17
Requirements
• Low power
• High performance

• Easy to release : Productivity
• Easy to use for user : UX/UI
• Compatibility
OpenSEED imageA 18
How can we meet
these requirements

OpenSEED imageA 19
Hardware based approach(1)
• Silicon gate length : e.g. 20nm
• Architecture : e.g. RISC
• Instruction processing : e.g. ARM NEON

OpenSEED imageA 20
Hardware based approach(2)
• CPU trend : Operating Frequency

OpenSEED imageA 21
Hardware based approach(3)
• Multi-core
Processor 1

Processor 3

Processor 2

General
Purpose
Processor 1

GPU

Processor 4

General
Purpose
Processor 2

DSP

Homogeneous

Heterogeneous

Architecture

Architecture

OpenSEED imageA 22
Software based approach
• Efficient algorithm
• Multi-core framework
– OpenMP
– OpenCL(WebCL)
– CUDA

• Efficient application design with multicore framework
OpenSEED imageA 23
Heterogeneous multi-core
system application

OpenSEED imageA 24
For desktop
• Games
• Web acceleration

• UHD video : 4K, 8K
• Computer graphics, 3D, authoring tools

• Financial

OpenSEED imageA 25
For embedded system
• General purpose
– Games
– Web acceleration
– UHD video : 4K, 8K

• Specialized purpose
–
–
–
–

Computer vision
Robot
Autonomous vehicles, UAV
Medical imaging
OpenSEED imageA 26
Embedded
multi-core image processing
application framework

OpenSEED imageA 27
•

Future

Current

Desktop, smart device application
HSA (Heterogeneous System Architecture)
http://www.tomshardware.com/reviews/fusion-hsa-opencl-history,3262-8.html

OpenSEED imageA 28
OpenCL(1)
• Low level hardware abstraction
• Supporting two parallelism methods
– Data parallelization
– Task parallelization

• User is in charge of optimization
– Engineer needs to know big picture
– Regression testing…
OpenSEED imageA 29
OpenCL(2)
• Programming Model

OpenSEED imageA 30
OpenCL(3)
• Memory
model

OpenSEED imageA 31
OpenCV
• Image processing library
• OpenCV is being worked on
supporting discrete GPU(nVidia, AMD)
with x86 only, currently
• OpenCV doesn’t support ARM OpenCL
(Planed to release in near future)
OpenSEED imageA 32
2. technical backgrounds

3. COWORKING WITH ETRI,
KESSIA
OpenSEED imageA 33
ETRI providing
• Platform hardware
– Target board

• Platform software
– Kernels
– Middleware
– Development tools

• Community base
– OpenSEED
OpenSEED imageA 34
ETRI roadmap

ETRI

OpenSEED imageA 35
KESSIA providing
• Making interconnection between ETRI
and community

• Community operation
– OpenSEED

OpenSEED imageA 36
3. coworking with ETRI, KESSIA

4. CURRENT OUR WORKS

OpenSEED imageA 37
imageA = 이미자?

OpenSEED imageA 38
imageA =
image processing Acceleration

OpenSEED imageA 39
First Trial(1)
• From ETRI

– Hardware : Exynos 4412 based development
board. Mali-400 GPU

(http://www.hardkernel.com/renewal_2011/products/prdt_info.php?g_c
ode=G133888637376)

– Kernel : high performance
resource management
kernel

• Long journey for the works
OpenSEED imageA 40
First Trial(2)
• Our activities
–
–
–
–

Referring user manuals in OpenSEED
Kernel porting
OpenCV library porting
OpenCV test application development

OpenSEED imageA 41
First Trial(3)
• How about now?

OpenSEED imageA 42
Second Trial
• From ETRI
– Hardware : x86 based AMD SBC
– Kernel

• Our activities (~2013.11)
– OpenCV library
– OpenCV test application development
– Performance test
OpenSEED imageA 43
4. current our woks

5. FUTURE OF OUR WORKS

OpenSEED imageA 44
First Trial
• From ETRI
– Hardware : x86 based AMD SBC
– Kernel
– Development tools

• Our activities
– OpenCV test application development
– OpenCL test application
– Performance test
OpenSEED imageA 45
Second Trial
• From ETRI
– Hardware : ARM based development board
– Kernel
– Development tools

• Our activities
– OpenCL test application
– OpenCV test application development
– Performance test
OpenSEED imageA 46
Further Trial
• From ETRI
– Hardware : ARM based development board
– Kernel
– Development tools

• Our activities
–
–
–
–

Existing activities
+ Specific application
+ For smart devices
+ Connected application : streaming and so on
OpenSEED imageA 47
Agenda, again
1. Why we do this?
2. Technical backgrounds
3. Co-working with ETRI, KESSIA

4. Current our works
5. Future of our works
OpenSEED imageA 48
Thank you!

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Community works for muli core embedded image processing