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A novel electro-photonic accelerator architecture optimized for TFHE, featuring OPCM-based FFT units, a twiddle-stationary dataflow tailored for OPCM, and a scheduling mechanism to maximize the utilization of the FFT units is introduced.
Xamt uncovers critical API discrepancies across deep learning libraries, revealing that traditional testing methods may miss up to 72 significant issues.
