1,755 research outputs found
PCNNA: A Photonic Convolutional Neural Network Accelerator
Convolutional Neural Networks (CNN) have been the centerpiece of many
applications including but not limited to computer vision, speech processing,
and Natural Language Processing (NLP). However, the computationally expensive
convolution operations impose many challenges to the performance and
scalability of CNNs. In parallel, photonic systems, which are traditionally
employed for data communication, have enjoyed recent popularity for data
processing due to their high bandwidth, low power consumption, and
reconfigurability. Here we propose a Photonic Convolutional Neural Network
Accelerator (PCNNA) as a proof of concept design to speedup the convolution
operation for CNNs. Our design is based on the recently introduced silicon
photonic microring weight banks, which use broadcast-and-weight protocol to
perform Multiply And Accumulate (MAC) operation and move data through layers of
a neural network. Here, we aim to exploit the synergy between the inherent
parallelism of photonics in the form of Wavelength Division Multiplexing (WDM)
and sparsity of connections between input feature maps and kernels in CNNs.
While our full system design offers up to more than 3 orders of magnitude
speedup in execution time, its optical core potentially offers more than 5
order of magnitude speedup compared to state-of-the-art electronic
counterparts.Comment: 5 Pages, 6 Figures, IEEE SOCC 201
Simpleweb/University of Twente Traffic Traces Data Repository
The computer networks research community lacks of shared measurement information. As a consequence, most researchers need to expend a considerable part of their time planning and executing measurements before being able to perform their studies. The lack of shared data also makes it hard to compare and validate results. This report describes our efforts to distribute a portion of our network data through the Simpleweb/University of Twente Traffic Traces Data Repository
Energy-efficiency improvements for optical access
This article discusses novel approaches to improve energy efficiency of different optical access technologies, including time division multiplexing passive optical network (TDM-PON), time and wavelength division multiplexing PON (TWDM-PON), point-to-point (PTP) access network, wavelength division multiplexing PON (WDM-PON), and orthogonal frequency division multiple access PON (OFDMA-PON). These approaches include cyclic sleep mode, energy-efficient bit interleaving protocol, power reduction at component level, or frequency band selection. Depending on the target optical access technology, one or a combination of different approaches can be applied
ASIC Design to Support Low Power High Voltage Power Supply for Radiation Monitoring Applications
A low power high voltage power supply is designed for use in a long duration radiation monitoring system. The supply employs a flexible pulse frequency modulation switching controller implemented in a 0.35 m CMOS technology. The controller drives and regulates a flyback transformer driven 12-stage Cockroft-Walton voltage multiplier chain. The chain provides bias for the dynodes of a photomultiplier tube. The supply voltage is selectable via a 12-bit on-chip digital to analog converter. The system is designed for low power operation and immunity to supply voltage variation as the application is battery-powered.
Advisors: Sina Balkir and Michael Hoffma
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