Openbar Leuven // Edge-Computing: On-device AI // Nick Destrycker

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AI is increasingly being implemented on-device instead of an implementation in the cloud. What is edge computing, Edge AI, why should we care and how to benefit from it? Expect an in-dept explanation, possible technical solutions and use cases to the current edge computing trend in the AI landscape.

Why Edge Computing?
Where is it used?
How AI works?
AI Hardware
Edgise
Table of contents
Edgise

Why edge computing ?
Edgise
H o w m u c h d a t a ?
1 2 8 0 x 7 2 0
= 9 2 1 6 0 0 P i xe l s

Why edge computing ?
Edgise
H o w m u c h d a t a ?
1 2 8 0 x 7 2 0
= 9 2 1 6 0 0 P i xe l s
1 P i xe l = 2 4 b i t s

Why edge computing ?
Edgise
H o w m u c h d a t a ?
1 2 8 0 x 7 2 0
= 9 2 1 6 0 0 P i xe l s
1 P i xe l = 2 4 b i t s
= 2 2 1 1 8 4 0 0 b i t s

Why edge computing ?
Edgise
H o w m u c h d a t a ?
1 2 8 0 x 7 2 0
= 9 2 1 6 0 0 P i xe l s
1 P i xe l = 2 4 b i t s
= 2 2 1 1 8 4 0 0 b i t s
Wh a t d o we l o o k f o r ?
2 s e a t s a r e t a ke n
- > r e p r e s e n t a b l e b y :
2 b i t s

Reliability
Low latency
Privacy
Efficient use of bandwidth
Networking cost reduction
Edge approach
High bandwidth use
No connection, no decision
High and unpredictable latency
Classic approach
Why edge computing ?
Edgise

Smart City
MonitoringGai n val uabl e i nsi ghts usi ng edge computi ng camera anal ysi s
cl assi fyi ng several objects and scenes throughout the ci ty
S M A R T O B J E C T / S C E N E D E T E C T I O N
L O W P O W E R / N E T W O R K T R A F F I C
D ATA P R I VA C Y M A I N TA I N E D

Factory Automation
Recogni ze features of products on conveyer bel ts and actuate the
producti on l i ne accordi ngl y
A I V I S I O N S Y S T E M
D E T E C T / C L A S S I F Y P R O D U C T F E AT U R E S
H I G H S P E E D O F F L I N E P R O C E S S I N G

Human Presence
Detection
make sure autonomous vehi cl es stop when humans wal k i n front of
them
R E A C T I O N I N M I L L I S E C O N D S
L O W P O W E R / N E T W O R K T R A F F I C
N O H I G H S P E E D C O N N E C T I O N N E C E S S A R Y

Sound anomaly
detection
Detect sound anomal i es, not onl y rel ated to vol ume, but al so to the
nature of the sounds.
I N H E R E N T P R I VA C Y – S O U N D N O T R E C O R D E D
C O M P L E X A N A LY S I S
L O W P O W E R / N E T W O R K T R A F F I C

How neural networks work
Edgise
Output = F(X0.W0 + X1.W1 + X2.W2 + X3.W3 … + Xn.Wn)
4 multiplications
3 summations
It’s all about MACs !

Performance
1 FPS
Power consumption
4,6mW
Edgise
Performance example
Low power
Performance
9000 FPS
Power consumption
11.7W
Hight performance
VGG-3, 32x32 images
2.15 x 2.55 mm
VGG-6, 32x32 images
17.0 x 17.0 mm

Bug FixingExpensive Time-To-Market
Hardware Development
Edgise

Idea to prototype
Full Package
Flexible development path
No vendor lock-in
Tailored Hardware
Adopt the software
way of working
Agile Development
The Edgise Way
Edgise

Optimal performance
Low unit cost
ASIC
Short Time-To-Market
Low development cost
Off-the-shelf
Increased reusability
Increased flexibility
Reconfigurable FPGA
Tailored Hardware
Edgise

WORK
FLOW
BACKLOG
REFINEMENT
SPRINT PLANNING
Using this approach we can address complex
adaptive problems, while productively and
creatively delivering products of the highest
possible value.
SHIPPABLE PRODUCT
DAILY
STANDUP
Edgise
DAILY STANDUP
• Review progress from last day
• Define stakeholder contact points
SPRINT REVIEW
• Discuss project progress
• Finetune scope
• Discuss issues
• still on budget ?
Every 2 weeks (or when needed)
Sprint Approach

Get Connected
https://www.edgise.com
Gaston Geenslaan 11B4, Leuven
hello@edgise.com
+32 472 43 95 42
+32 477 33 24 63
3000 Leuven
België
Gaston Geenslaan 11B4
Sam Sterckval
sam@edgise.com
+32 477 33 24 63
Nick Destrycker
nick@edgise.com
+32 472 43 95 42

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