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BTS: An Accelerator for Bootstrappable Fully Homomorphic Encryption

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arxiv 2112.15479 v2 pith:EKCEQAZG submitted 2021-12-31 cs.CR cs.AR

classification cs.CRcs.AR
keywords acceleratorbootstrappingcomputationdataencryptionmemorynumberoperations
verification ladder T0 review T1 audit T2 compute T3 formal

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Homomorphic encryption (HE) enables the secure offloading of computations to the cloud by providing computation on encrypted data (ciphertexts). HE is based on noisy encryption schemes in which noise accumulates as more computations are applied to the data. The limited number of operations applicable to the data prevents practical applications from exploiting HE. Bootstrapping enables an unlimited number of operations or fully HE (FHE) by refreshing the ciphertext. Unfortunately, bootstrapping requires a significant amount of additional computation and memory bandwidth as well. Prior works have proposed hardware accelerators for computation primitives of FHE. However, to the best of our knowledge, this is the first to propose a hardware FHE accelerator that supports bootstrapping as a first-class citizen. In particular, we propose BTS - Bootstrappable, Technologydriven, Secure accelerator architecture for FHE. We identify the challenges of supporting bootstrapping in the accelerator and analyze the off-chip memory bandwidth and computation required. In particular, given the limitations of modern memory technology, we identify the HE parameter sets that are efficient for FHE acceleration. Based on the insights gained from our analysis, we propose BTS, which effectively exploits the parallelism innate in HE operations by arranging a massive number of processing elements in a grid. We present the design and microarchitecture of BTS, including a network-on-chip design that exploits a deterministic communication pattern. BTS shows 5,556x and 1,306x improved execution time on ResNet-20 and logistic regression over a CPU, with a chip area of 373.6mm^2 and up to 163.2W of power.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. EFFACT: A Highly Efficient Full-Stack FHE Acceleration Platform

    cs.CR 2025-04 conditional novelty 6.0 of 10

    EFFACT combines a streaming compiler, circuit-level function-unit reuse, and compact NTT and automorphism units to accelerate FHE workloads efficiently at small SRAM size.

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