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1 [email protected] mi.it CNN 2 ECST Andrea Solazzo Matteo De Silvestri Irene De Rose [email protected] t [email protected]. Thursday, March 17, 2016 XOHW16 Meeting

2. Cnnecst-Why the use of FPGA?

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Page 1: 2. Cnnecst-Why the use of FPGA?

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[email protected]

CNN2ECST

Andrea SolazzoMatteo De SilvestriIrene De Rose

[email protected]@mail.polimi.it

Thursday, March 17, 2016XOHW16 Meeting

mailto:[email protected]
mailto:[email protected]
mailto:[email protected]
Page 2: 2. Cnnecst-Why the use of FPGA?

2

HW acceleration

Convolutional Neural Networks have a data-flow computation pattern that results to be highly suitable for hardware acceleration

Zhang, Chen, et al. "Optimizing fpga-based accelerator design for deep convolutional neural networks." Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays. ACM, 2015.

Page 3: 2. Cnnecst-Why the use of FPGA?

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Why FPGA?● CNNs have a huge design space

● Finding the “optimal” model requires some tuning

● Many “degrees of freedom” (#layers, #neurons, …)

Page 4: 2. Cnnecst-Why the use of FPGA?

3

Why FPGA?

✓ Reconfigurability allows to implement different models and select the best one directly in hardware

● CNNs have a huge design space

● Finding the “optimal” model requires some tuning

● Many “degrees of freedom” (#layers, #neurons, …)

Page 5: 2. Cnnecst-Why the use of FPGA?

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A. Dundar, J. Jin, V. Gokhale, B. Krishnamurthy, A. Canziani, B. Martini, and E. Culurciello. Accelerating Deep Neural Networks on MobileProcessor with Embedded Programmable Logic. In Proc. NIPS’13, 2013.

Why FPGA?

Page 6: 2. Cnnecst-Why the use of FPGA?

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A. Dundar, J. Jin, V. Gokhale, B. Krishnamurthy, A. Canziani, B. Martini, and E. Culurciello. Accelerating Deep Neural Networks on MobileProcessor with Embedded Programmable Logic. In Proc. NIPS’13, 2013.

The proper trade-off

between performances

and power consumption

reflects on a high

embeddable factor,

calculated as

performance over Watt

(GOP/s /W)

Why FPGA?

Page 7: 2. Cnnecst-Why the use of FPGA?

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CNN2ECST

CNNECST-Convolutional Neural Network(www.facebook.com/cnn2ecst)

@cnn2ecst(www.twitter.com/cnn2ecst)

https://www.facebook.com/CNNECST-Convolutional-Neural-Network-1067181939971957/
https://twitter.com/cnn2ecst

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