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- 1. Eugenio Culurciello © 2016 Eugenio Culurciello Purdue University e-Lab productions 1998 - 2013
- 2. Eugenio Culurciello © 2016 Image Sensors
- 3. Eugenio Culurciello © 2016 designed for mobile, ultra low-power, bio-inspired image sensors Custom Address-event Cameras Event-based Vision Algorithms ENALAB platform - YALE Target: vision with 10mW on embedded hardware Neuromorphic image sensors
- 4. Eugenio Culurciello © 2016 • Event-based image sensors • operate with the address-event representation • each pixel can generate events • pixel addresses encodes the position of the event Event: motion Events can be accumulated in a frame some events more events Address-event image sensors
- 5. Eugenio Culurciello © 2016 Address-event temporal contrast image sensor from Yale e-Lab AER temporal contrast sensors
- 6. Eugenio Culurciello © 2016 ISSCC 2001: Octopus retina Technology 0.6μm 3M CMOS Array Size 80 (H) x 60(V) Pixel Size 32μm x 30μm Fill Factor 14% Dynamic Range 200dB(Pix),120dB(Array) Bandwidth 8mHz – 40MHz (Pix.) 40Hz-40MHz (Array) Pixel Frequency Jitter (STD/Max) 6x10-4 % Sensitivity [Hz/mW/cm2] 2x106 (Array), 42 (Pix) FPN (STD/Mean pixel-pixel) 4% @ 0.1 mW/cm2 Max. FPS 8.3K (effective) Digital Power (@ 0.1mW/cm2) 3.4mW @ 2.9V Supply Analog Power (@ 0.1mW/cm2) < 10μW @ 2.7V Supply Unprocessed image: Raw Intensity Processed image: Logarithm of Intensity
- 7. Eugenio Culurciello © 2016 2004: ALOHA sensor Technology 0.6µm 3M CMOS Array Size 32 x 32, 4 quadrants Pixel Size 32.7µm x 29.7µm Fill Factor 6.5% Sensor Core Size 1.2 x 1.2mm/quadrant Dynamic Range 235dB (Pixel) 175dB (Array) Bandwidth 8.13μHz - 5MHz (Pixel) 8.33mHz – 5MHz (Array) Sensitivity [Hz/W/m2] 5.6x105 (Array) 9.1 x1011 (Pixel) Max. FPS 2.44K (effective) Digital Power 5.7μW at 2.35V, 3fps Analog Power 7.2nW at 2.35V, 3fps
- 8. Eugenio Culurciello © 2016 2004: ALOHA sensor
- 9. Eugenio Culurciello © 2016 2007: SOI 3D image sensor
- 10. Eugenio Culurciello © 2016 2008: T-mode sensor
- 11. Eugenio Culurciello © 2016 2008: T-mode sensor
- 12. Eugenio Culurciello © 2016 2008: T-mode sensor
- 13. Eugenio Culurciello © 2016 2011: neuFlow Intel 2Core neuFlow Virtex4 neuFlow Virtex 6 nVidia GT335m neuFlow IBM 45nm nVidia GTX480 Peak GOP/sec ~10 40 160 182 640 1350 Actual GOP/sec 1.1 37 147 54 632 294 FPS 1.4 46 182 67 684 374 Power (W) 30 10 10 30 2 220 Embed? 0.0366 66666 1.3363
- 14. Eugenio Culurciello © 2016 2011: neuFlow SoC • IBM 45 nm high-density technology, 2.5x5mm • 400MHz system clock, 200MHz CPU clock • 4 convolvers, combiners, mappers • Performance 12x better than FPGA (G- ops/Watt) Process IBM SOI 45nm Chip area 2.5 x 5 mm2 Supply Voltages 1V Vcore, 1.8V and 3.3V VI=O Target frequency 400MHz Estimated average power 570mW Peak performance 320 GOPS GOPS per Watt ~560 Number of transistors, memories, etc. 23.6M transistors, 75KB 2-port RAM Pin count 317 (299 I/Os and 18 P/Gs) Packaging Flip-chip
- 15. Eugenio Culurciello © 2016 2013: nn-X ARM Processors External memoryMemory controller Memory interconnect Memory router Router MAC f(x) Router MAC f(x) Router MAC f(x) nn-X
- 17. Eugenio Culurciello © 2016 2005: neuroView NV2, 2 x 2 pixel average NeuroCCD, 4 x 4 pixel average
- 18. Eugenio Culurciello © 2016 2015: neuralMapper
- 19. Eugenio Culurciello © 2016 Integrated Patch Clamp Die Size: 1.5 x 1.5mm Technology: 0.5μm CMOS Supply: 3.3V ADC: 12b Sigma-Delta Output Data: Serial Range: 1pA to 100nA Noise: 0.1pA RMS Bandwidth: 10kHz 2005: patch-clamp amplifier
- 20. Eugenio Culurciello © 2016 2006: SOI patch-clamp amplifier
- 21. Eugenio Culurciello © 2016 2009: 4-ch patch-clamp amplifier Item Value Remark Technology 1-Poly, 3-Metal, 0.5µm Silicon-on- Sapphire Number of channels 4 Expandable by daisy chaining multiple chips Silicon area per channel 6790µm × 768µm Total silicon area 8120 × 4092 Nominal power supply and consumption 30.1mW @ VDD=VDDD=3.3V Input referred noise Voltage clamp: 3.3pA RMS @ 5kHz BW Current clamp: 130µV RMS @ 5kHz BW With 100MΩ feedback resistance Dynamic range Voltage clamp: 80.0dB Current clamp: 88.1dB With 100MΩ feedback resistance Available feedback resistance 100MΩ, 50MΩ, 25MΩ, 12.5MΩ, 6.25MΩ, 3.125MΩ, 1.563MΩ, 81.250MΩ, 391kΩ, 195kΩ, 98kΩ, 49kΩ Both for the voltage and the current clamp
- 22. Eugenio Culurciello © 2016 2010: low-noise current amplifier
- 23. Eugenio Culurciello © 2016 2006: neural amplifiers channels 4 bandwidth 20KHz output digital gain 53dB power 25μW/ch. noise 2μV RMS
- 24. Eugenio Culurciello © 2016 2008: Ultra-Wide-Band Radios
- 25. Eugenio Culurciello © 2016 PECASE award 2010: most prestigious early career award in US
- 27. Eugenio Culurciello © 2016 Deep Learning
- 28. Eugenio Culurciello © 2016 Deep Learning from 2012 - present: another presentation…
- 30. Eugenio Culurciello © 2016 Thanksgiving E-Lab current members: Aysegul Dundas Vinayak Gokhale Jonhoon Jin Alfredo Canziani Abhishek Chaurasia SangPil Kim Andre Chang, Aliasger Zaidy Past members: Zhengming Fu Pujitha Weerakoon Shoushun Chen Farah Laiwalla Huang Chenxi Dongsoo Kim Andrew Kunil Choe Selcuk Talay Polina Askelrod Faye Zhao Ifigeneia Derekli Hazael Montanaro Darko Jelaca Jonathan McMillan Evan JoonHuyk Park Wei Tang Phi-Hung Pham Jordan Bates Giovanni Barbera Berin Martini Visitors: Jose Carrasco Angelo Rottigni Alejandro Linares-Barranco Rafael Paz TERADEEP