Fully Homomorphic Encryption (FHE) enables computation over encrypted data, but it faces significant challenges in practical implementation due to its high computational costs, particularly in HMult, HRot, and Bootstrapping operations. This work presents Athena, an accelerated FH
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Fully Homomorphic Encryption (FHE) enables computation over encrypted data, but it faces significant challenges in practical implementation due to its high computational costs, particularly in HMult, HRot, and Bootstrapping operations. This work presents Athena, an accelerated FHE system built on GPUs with a new algorithm-hardware co-design approach. Specifically, to accelerate HMult, HRot, and Bootstrapping, we redesign their common and expensive operation KeySwitch, based on the KLSS method proposed by Kim et al. in CRYPTO’23, and accelerate its core operations, namely NTT, EBConv, and IP. We further optimize the dataflow of Bootstrapping by reducing redundant EBConv and (I)NTT operations, and by improving the global memory I/O in the double-hoisting-based C2S/S2C operation. Moreover, Athena is designed as a general-purpose system that supports various cryptographic parameters. Experimental results demonstrate that Athena significantly improves the performance of KeySwitch and Bootstrapping. In particular, Athena’s accelerated KeySwitch optimizes HMult 2.17\times \sim 4.40\times and HRot 1.89\times \sim 4.54\times compared to TensorFHE (HPCA’23), Poseidon (HPCA’23), and FAB (HPCA’23), respectively. Besides, Athena’s Bootstrapping outperforms TensorFHE by nearly 2.74\times .