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TensorFHE: Achieving Practical Computation on Encrypted Data Using GPGPU. (arXiv:2212.14191v1 [cs.AR])
cs.CR updates on arXiv.org arxiv.org
In this paper, we propose TensorFHE, an FHE acceleration solution based on
GPGPU for real applications on encrypted data. TensorFHE utilizes Tensor Core
Units (TCUs) to boost the computation of Number Theoretic Transform (NTT),
which is the part of FHE with highest time-cost. Moreover, TensorFHE focuses on
performing as many FHE operations as possible in a certain time period rather
than reducing the latency of one operation. Based on such an idea, TensorFHE
introduces operation-level batching to fully utilize the …
applications computation cost data encrypted encrypted data fhe ntt performing solution tensor