Inference analysis of optical transformers
Xianxin Guo · Chenchen Wang · Djamshid Damry
2023 Poster
in
Workshop: Machine Learning with New Compute Paradigms
in
Workshop: Machine Learning with New Compute Paradigms
Abstract
This paper explores the utilization of optical computing for accelerating inference in transformer models, which have demonstrated substantial success in various applications. Optical computing offers ultra-fast computation and ultra-high energy efficiency compared to conventional electronics. Our findings suggest that optical implementation has the potential to achieve a significant 10-100 times improvement in the inference throughput of compute-limited transformer models.
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