JeremieMelo/M3ICRO-MOMMI
Machine Learning-Enabled Compact Photonic Tensor Core based on Programmable Multi-Operand Multimode Interference
This project helps researchers and engineers design and optimize next-generation optical computing hardware. It provides tools to model and simulate photonic tensor cores, which are specialized optical processors for machine learning. You input simulation data for multimode interference (MMI) devices and neural network configurations, and it outputs optimized control signals for these optical components, along with performance predictions for their use in AI tasks. This is for photonic hardware designers, optical engineers, and AI hardware researchers working on integrated photonics for high-performance computing.
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Use this if you are designing compact photonic tensor cores and need to integrate machine learning optimization to precisely control their optical behavior for efficient matrix multiplication.
Not ideal if you are looking for a general-purpose machine learning library or a tool for simulating large-scale optical networks or traditional electronic hardware.
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13
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Language
Python
License
MIT
Category
Last pushed
Sep 23, 2024
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