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Andrea Milanta (andrea.milanta@mail.polimi.it)
Guido Muscioni (guido.muscioni@mail.polimi.it)
Matteo Foglio (matteo.foglio@mail.polimi.it)
Computer vision implementing OpenCV on FPGA
1
Seminar Room (Politecnico di Milano)
19/04/2017
Introduction
2
AlphaData Kintex Ultrascale
FPGAIntel base board
Intel Atom E8000
Stitching algorithm
for biomedical application
VS
Implementation
on intel Atom
Implementation
on FPGA
Main tasks
3
Algorithm
Analysis
Implementation
on intel Atom
Implementation
on FPGA
Main tasks
3
Code profiling
Implementation
on intel Atom
Implementation
on FPGA
Main tasks
3
Code profiling
Implementation
Implementation
on intel Atom
Implementation
on FPGA
Kernel
implementation
Host
Implementation
Main tasks
3
Code profiling
Implementation
Implementation
on intel Atom
Implementation
on FPGA
Kernel
implementation
Host
Implementation
Main tasks
3
Code profiling
Implementation
Integration and
Testing
Implementation
on intel Atom
Implementation
on FPGA
Kernel
implementation
Host
Implementation
Main tasks
3
Code profiling
Implementation
Performance
analysis
Integration and
Testing
Performance
analysis
Tasks assignments
4
Code profiling
Implementation
Integration and
Testing
Performance
analysis
Tasks assignments
4
Code profiling
Implementation
Integration and
Testing
Matteo Foglio
Performance
analysis
Tasks assignments
4
Code profiling
Implementation
Integration and
Testing
Matteo Foglio
Andrea Milanta
Intel Atom
Performance
analysis
Tasks assignments
4
Code profiling
Implementation
Integration and
Testing
Matteo Foglio
Guido Muscioni
FPGA
Andrea Milanta
Intel Atom
SWOT
5
S
Strenght
• Execution
time
• Energy
efficiency
• Integration
with large
open-source
projects
SWOT
5
S
Strenght
• Execution
time
• Energy
efficiency
• Integration
with large
open-source
projects
Weaknesses
• Hardware
and tools
cost
• Niche
product
W
SWOT
5
S
Strenght
• Execution
time
• Energy
efficiency
• Integration
with large
open-source
projects
Weaknesses
• Hardware
and tools
cost
• Niche
product
W
Opportunities
• Computer
vision market
growth
• High
performance
embedded
application
market
growth
O
SWOT
5
S
Strenght
• Execution
time
• Energy
efficiency
• Integration
with large
open-source
projects
Weaknesses
• Hardware
and tools
cost
• Niche
product
W
Opportunities
• Computer
vision market
growth
• High
performance
embedded
application
market
growth
O T
Threats
• GPU
competition
• Research
from big
players in the
field
Questions?
Guido Muscioni
Bachelor in Computer Science
guido.muscioni@mail.polimi.it
Andrea Milanta
Bachelor in Computer Science
andrea.milanta@mail.polimi.it
FOCus at NECST
facebook.com/FOCusatNECST/
FOCusAtNECST
slideshare.net/FOCusAtNECST/
@FOCusAtNECST
twitter.com/FOCusAtNECST
6
Matteo Foglio
Bachelor in Computer Science
matteo.foglio@mail.polimi.it
Contact us
bitbucket.org/necst/xohw17_f
ocus_public

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