Convolve presents the work organization till June, 30.

1. M AD D AL ENA AND REO L I – M AD D ALENA.ANDREOL I@MAIL.PO LIMI.IT
S TEFANO CAGNINELLI – S TEFANO .CAGNINELLI@ MAIL.PO LIMI.IT
AL ES S ANDRO PAP PAL ARDO – AL ES S ANDRO1 .PAPPALARD O@ MAIL .PO LIMI.IT
April 5, 2017 @ DEIB, Politecnico di Milano
Project Organization

2. What to achieve: Goals
1. Efficient block 3x3 Winograd FPGA convolution
2. High level APIs in reference deep learning framework
3. Apply it to (pseudo) compressed censing Camera as a test case
2

3. How to achieve it: Tasks
State of the art analysis
Naive convolution C implementation
Winograd C implementation
Winograd HLS implementation
Winograd FPGA Caffe' APIs
Compressed Camera
3

4. How to organize it: Task Dependencies
4
SoA
Naive
C
Winograd
C
Caffe'
APIs
Compressed
Camera
Winograd
HLS

5. How is it going: Progresses
5
SoA
Naive
C
Winograd
C
Caffe'
APIs
Compressed
Camera
Winograd
HLS
Done WIP TODO

6. How it may go: Pivoting
6
SoA
Naive
C
Winograd
C
Caffe'
APIs
Compressed
Camera
Winograd
HLS
Done WIP TODO
Simpler
Winograd
HLS
Pivot
Plain
Python
APIs
FPGA too
small
Caffe' not
working
Camera not working
Caffe' not
working

7. April 19, 2017 @ DEIB, Politecnico di Milano
Thank you for your time!
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