P-DAC: Power-Efficient Photonic Accelerators for LLM Inference

As traditional electronic hardware encounters the limitations of Moore's Law, optical computing is emerging as a promising alternative, delivering high data transmission rates, especially beneficial for big data and AI applications. Photonic accelerators, such as the Lightening-Transformer, utilize optical analog signals to accelerate Transformerbased models, achieving exceptional speed and low energy consumption. However, controlling modern optical intensity modulators (e.g., Mach-Zehnder Modulators) requires using electrical analog signals (e.g., voltage values) to adjust the optical signal intensity for realizing optical-based vector inner product calculations. Managing this modulation consumes significant power, as it involves selecting optimal electrical values through an electrical controller and converting digital signals to analog using digital-to-analog converters (DACs). In this work, we introduce P-DAC, a solution designed to reduce DAC power consumption, significantly enhancing the energy efficiency of optical accelerators for Transformer models.