FHE-Booster: Accelerating Fully Homomorphic Execution with Fine-tuned Bootstrapping Scheduling

Tommy White, Charles Gouert, Chengmo Yang, N. G. Tsoutsos
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Abstract

Fully homomorphic encryption (FHE) allows a user to outsource computation-intensive tasks to a cloud server witheut providing plaintext values or decryption heys to the server. A major drawback of these encrypted operations, however, is that they can be orders of magnitude slower than their plalintext counterparts. Moreover, because each ciphertext can only tolerate a llmited number of operatlons before the accumulated nole renders decryption impossible, an operation known as bootsirapping is needed to reduce such nolse and allow for unilimited computations. Notably, bootstrapping is signincantly slower than encrypted arithmetic operatlons, thus becoming a main performance bottleneck while evaluating FHE programs So far, the allocatlon and scheduling of bootstrapping operations has not been well Investigated, In part due to the complexity of the probkem and the difinculty in finding an optimal solution. To bridge thls gap, in thls work we formulate the bootstrapping scheduling problem and develop two Integer Programming (IP) modek. The first minimlies the number of bootstrapplng operations in an FHE program, while the second optimines the evecution time of the FHE program. We further develop two heurlstics for mapplng a target FHE program to a multi. core system in polynomial time. Our evaluation with a reallstic benchmark shows that our heuristic provides a 1.86x speedup compared to the baselline method.
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FHE-Booster:通过微调引导调度加速完全同态执行
完全同态加密(FHE)允许用户将计算密集型任务外包给云服务器,而无需向服务器提供明文值或解密密钥。然而,这些加密操作的一个主要缺点是,它们可能比对应的明文操作慢几个数量级。此外,由于每个密文只能容忍有限数量的操作,在累积的作用导致无法解密之前,需要一种称为自举的操作来减少这种损失并允许无限的计算。值得注意的是,自举比加密算术操作要慢得多,因此成为评估FHE程序的主要性能瓶颈。迄今为止,自举操作的分配和调度尚未得到很好的研究,部分原因是问题的复杂性和寻找最优解的难度。为了解决这一问题,本文提出了自举调度问题,并建立了双整数规划模型。第一个最小化了FHE程序中的自启动操作的数量,而第二个优化了FHE程序的执行时间。我们进一步开发了两种启发式方法,用于将目标FHE程序映射到多个。核心系统在多项式时间。我们对实际基准的评估表明,与基线方法相比,我们的启发式方法提供了1.86倍的加速。
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