Presentation
Chimera: A Unified FHE Accelerator with Enhanced Compatibility for TFHE
DescriptionFully homomorphic encryption (FHE) allows direct computation on encrypted data and thus enables privacy-preserving computation in the cloud. Among FHE schemes, CKKS efficiently supports arithmetic computation, while TFHE excels in logic operations. Recent studies have attempted to develop unified FHE accelerators that support diverse computational tasks and leverage the complementary strengths of the two schemes. However, existing unified FHE accelerators are predominantly CKKS-centric. At the operator layer, TFHE is mapped onto CKKS-oriented operators, causing significant performance degradation. Furthermore, the invocation to functional units and memory is entirely dominated by CKKS, resulting in hardware underutilization for TFHE.
In this paper, we propose three coordinated co-optimizations to address these challenges. First, we unify the computation of Fast Fourier Transform (TFHE core operation) and Number Theoretic Transform (CKKS core operation), and design a dual-mode computational flow to efficiently support both computations. Second, we propose an aggressive strategy of bootstrapping key unrolling to maximize TFHE hardware utilization. Third, we design a hardware-oriented support for FFT Shrinking KeySwitch to mitigate the performance bottleneck of TFHE KeySwitch. Accordingly, we present Chimera, a unified accelerator that redesigns the functional units and memory organization for TFHE to efficiently support these optimizations. Lastly, we develop an error, memory, and bandwidth-constrained auto-tuning framework that derives optimal TFHE configurations to maximize TFHE hardware utilization. Compared with the state-of-the-art unified FHE designs, Chimera achieves an average performance improvement by 14.84x across TFHE workloads, while maintaining comparable performance on CKKS workloads, with only a 9.6% area increase.
In this paper, we propose three coordinated co-optimizations to address these challenges. First, we unify the computation of Fast Fourier Transform (TFHE core operation) and Number Theoretic Transform (CKKS core operation), and design a dual-mode computational flow to efficiently support both computations. Second, we propose an aggressive strategy of bootstrapping key unrolling to maximize TFHE hardware utilization. Third, we design a hardware-oriented support for FFT Shrinking KeySwitch to mitigate the performance bottleneck of TFHE KeySwitch. Accordingly, we present Chimera, a unified accelerator that redesigns the functional units and memory organization for TFHE to efficiently support these optimizations. Lastly, we develop an error, memory, and bandwidth-constrained auto-tuning framework that derives optimal TFHE configurations to maximize TFHE hardware utilization. Compared with the state-of-the-art unified FHE designs, Chimera achieves an average performance improvement by 14.84x across TFHE workloads, while maintaining comparable performance on CKKS workloads, with only a 9.6% area increase.
Event Type
Research Manuscript
TimeTuesday, July 283:54pm - 4:06pm PDT
LocationMtg Room 203C
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