CrossLight: A Cross-Layer Optimized Silicon Photonic Neural Network Accelerator

Domain-specific neural network accelerators have seen growing interest in recent years due to their improved energy efficiency and performance compared to CPUs and GPUs. In this paper, we propose a novel cross-layer optimized neural network accelerator called CrossLight that leverages silicon photon...

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Bibliographic Details
Published in2021 58th ACM/IEEE Design Automation Conference (DAC) pp. 1069 - 1074
Main Authors Sunny, Febin, Mirza, Asif, Nikdast, Mahdi, Pasricha, Sudeep
Format Conference Proceeding
LanguageEnglish
Published IEEE 05.12.2021
Subjects
Crosstalk
deep learning
Neural networks
Performance evaluation
Power lasers
Silicon photonics
Thermal engineering
Throughput
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DOI10.1109/DAC18074.2021.9586161

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Summary:Domain-specific neural network accelerators have seen growing interest in recent years due to their improved energy efficiency and performance compared to CPUs and GPUs. In this paper, we propose a novel cross-layer optimized neural network accelerator called CrossLight that leverages silicon photonics. CrossLight includes device-level engineering for resilience to process variations and thermal crosstalk, circuit-level tuning enhancements for inference latency reduction, and architecture-level optimizations to enable better resolution, energy-efficiency, and throughput. On average, CrossLight offers 9.5x lower energy-per-bit and 15.9x higher performance-per-watt than state-of-the-art photonic deep learning accelerators.
DOI:10.1109/DAC18074.2021.9586161