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Sairam Sri Vatsavai

Publications and source records attributed to Sairam Sri Vatsavai.

22 records · Page 2Linked to original sources

Silicon Photonic Microring Based Chip-Scale Accelerator for Delayed Feedback Reservoir Computing

To perform temporal and sequential machine learning tasks, the use of conventional Recurrent Neural Networks (RNNs) has been dwindling due to the training complexities of RNNs. To this end, accelerators for delayed feedback reservoir computing (DFRC) have attracted attention in lieu of RNNs, due to their simple hardware implementations. A typical implementation of a DFRC accelerator consists of a delay loop and a single nonlinear neuron, together acting as multiple virtual nodes for computing. In prior work, photonic DFRC accelerators have shown an undisputed advantage of fast computation over their electronic counterparts. In this paper, we propose a more energy-efficient chip-scale DFRC accelerator that employs a silicon photonic microring (MR) based nonlinear neuron along with on-chip photonic waveguides-based delayed feedback loop. Our evaluations show that, compared to a well-known photonic DFRC accelerator from prior work, our proposed MR-based DFRC accelerator achieves 35% and 98.7% lower normalized root mean square error (NRMSE), respectively, for the prediction tasks of NARMA10 and Santa Fe time series. In addition, our MR-based DFRC accelerator achieves 58.8% lower symbol error rate (SER) for the Non-Linear Channel Equalization task. Moreover, our MR-based DFRC accelerator has 98% and 93% faster training time, respectively, compared to an electronic and a photonic DFRC accelerators from prior work.

cs.AR↗

PROTEUS: Rule-Based Self-Adaptation in Photonic NoCs for Loss-Aware Co-Management of Laser Power and Performance

The performance of on-chip communication in the state-of-the-art multi-core processors that use the traditional electron-ic NoCs has already become severely energy-constrained. To that end, emerging photonic NoCs (PNoC) are seen as a po-tential solution to improve the energy-efficiency (performance per watt) of on-chip communication. However, existing PNoC designs cannot realize their full potential due to their exces-sive laser power consumption. Prior works that attempt to improve laser power efficiency in PNoCs do not consider all key factors that affect the laser power requirement of PNoCs. Therefore, they cannot yield the desired balance between the reduction in laser power, achieved performance and energy-efficiency in PNoCs. In this paper, we present PROTEUS framework that employs rule-based self-adaptation in PNoCs. Our approach not only reduces the laser power consumption, but also minimizes the average packet latency by opportunis-tically increasing the communication data rate in PNoCs, and thus, yields the desired balance between the laser power re-duction, performance, and energy-efficiency in PNoCs. Our evaluation with PARSEC benchmarks shows that our PROTEUS framework can achieve up to 24.5% less laser power consumption, up to 31% less average packet latency, and up to 20% less energy-per-bit, compared to another laser power management technique from prior work.

cs.ET↗

Exploiting Process Variations to Secure Photonic NoC Architectures from Snooping Attacks

The compact size and high wavelength-selectivity of microring resonators (MRs) enable photonic networks-on-chip (PNoCs) to utilize dense-wavelength-division-multiplexing (DWDM) in their photonic waveguides, and as a result, attain high bandwidth on-chip data transfers. Unfortunately, a Hardware Trojan in a PNoC can manipulate the electrical driving circuit of its MRs to cause the MRs to snoop data from the neighboring wavelength channels in a shared photonic waveguide, which introduces a serious security threat. This paper presents a framework that utilizes process variation-based authentication signatures along with architecture-level enhancements to protect against data-snooping Hardware Trojans during unicast as well as multicast transfers in PNoCs. Evaluation results indicate that our framework can improve hardware security across various PNoC architectures with minimal overheads of up to 14.2% in average latency and of up to 14.6% in energy-delay-product (EDP).

cs.AR↗

Redesigning Photonic Interconnects with Silicon-on-Sapphire Device Platform for Ultra-Low-Energy On-Chip Communication

Traditional silicon-on-insulator (SOI) platform based on-chip photonic interconnects have limited energy-bandwidth scalability due to the optical non-linearity induced power constraints of the constituent photonic devices. In this paper, we propose to break this scalability barrier using a new silicon-on-sapphire (SOS) based photonic device platform. Our physical-layer characterization results show that SOS-based photonic devices have negligible optical non-linearity effects in the mid-infrared region near 4μm, which drastically alleviates their power constraints. Our link-level analysis shows that SOS-based photonic devices can be used to realize photonic links with aggregated data rate of more than 1 Tb/s, which recently has been deemed unattainable for the SOI-based photonic on-chip links. We also show that such high-throughput SOS-based photonic links can significantly improve the energy-efficiency of on-chip photonic communication architectures. Our system-level analysis results position SOS-based photonic interconnects to pave the way for realizing ultra-low-energy (< 1 pJ/bit) on-chip data transfers.

physics.app-ph↗