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

• URL: http://arxiv.org/abs/2102.06960v1
• Date: Sat, 13 Feb 2021 17:08:06 GMT
• Title: CrossLight: A Cross-Layer Optimized Silicon Photonic Neural Network Accelerator
• Authors: Febin Sunny, Asif Mirza, Mahdi Nikdast, and Sudeep Pasricha
• Abstract summary: Domain-specific neural network accelerators have seen growing interest in recent years. We propose a novel cross-layer optimized neural network accelerator called CrossLight. On average, CrossLight offers 9.5x lower energy-per-bit and 15.9x higher performance-per-watt at 16-bit resolution than state-of-the-art photonic deep learning accelerators.
• Score: 3.49112071745966
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Domain-specific neural network accelerators have seen growing interest in recent years due to their improved energy efficiency and inference 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 optimization to enable higher resolution, better energy-efficiency, and improved throughput. On average, CrossLight offers 9.5x lower energy-per-bit and 15.9x higher performance-per-watt at 16-bit resolution than state-of-the-art photonic deep learning accelerators.

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