论文标题

方舟:具有运行时数据生成和互操作键重复使用的完全同型加密加速器

ARK: Fully Homomorphic Encryption Accelerator with Runtime Data Generation and Inter-Operation Key Reuse

论文作者

Kim, Jongmin, Lee, Gwangho, Kim, Sangpyo, Sohn, Gina, Kim, John, Rhu, Minsoo, Ahn, Jung Ho

论文摘要

同态加密(HE)是最有前途的量子后加密方案之一,可在服务器上实现隐私计算。但是,噪声在我们对He-Conted的数据进行操作时会累积,从而限制了可能的操作数量。他(FHE)完全通过引入引导操作来消除这一限制,从而刷新数据;但是,FHE方案是高度记忆的。尤其是引导程序需要从芯片内存储器内加载评估键和明文的GB,这使得通过芯片内存储器带宽从根本上加速了加速度。 在本文中,我们提出了ARK,ARK是运行时数据生成和互操作密钥重复使用的FHE的加速器。 ARK可以通过新颖的算法 - 架构共同设计进行实用的工作量,以加速自举。我们首先通过运行时数据生成和操作键重复使用来消除芯片内存带宽瓶颈。这种方法使ARK能够通过大大减少工作集的大小来完全利用片上内存。除了这样的算法增强功能之外,我们构建了ARK微结构结构,该结构通过基于数据访问模式的高效,交替的数据分配策略和精简功能单元的流线数据流组织(包括基本基础转换,数字理论变换和自动形状部门)来最大程度地减少芯片数据流动。总体而言,我们的共同设计有效地处理了FHE的大量计算和数据运动开销,从而大大降低了HE操作的成本,包括自举。

Homomorphic Encryption (HE) is one of the most promising post-quantum cryptographic schemes that enable privacy-preserving computation on servers. However, noise accumulates as we perform operations on HE-encrypted data, restricting the number of possible operations. Fully HE (FHE) removes this restriction by introducing the bootstrapping operation, which refreshes the data; however, FHE schemes are highly memory-bound. Bootstrapping, in particular, requires loading GBs of evaluation keys and plaintexts from off-chip memory, which makes FHE acceleration fundamentally bottlenecked by the off-chip memory bandwidth. In this paper, we propose ARK, an Accelerator for FHE with Runtime data generation and inter-operation Key reuse. ARK enables practical FHE workloads with a novel algorithm-architecture co-design to accelerate bootstrapping. We first eliminate the off-chip memory bandwidth bottleneck through runtime data generation and inter-operation key reuse. This approach enables ARK to fully exploit on-chip memory by substantially reducing the size of the working set. On top of such algorithmic enhancements, we build ARK microarchitecture that minimizes on-chip data movement through an efficient, alternating data distribution policy based on the data access patterns and a streamlined dataflow organization of the tailored functional units -- including base conversion, number-theoretic transform, and automorphism units. Overall, our co-design effectively handles the heavy computation and data movement overheads of FHE, drastically reducing the cost of HE operations, including bootstrapping.

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