Fully Homomorphic Encryption (FHE) enables privacy preserving computation but it suffers from high latency and memory consumption. The computations are secured with special keys called rotation keys which often take up the majority of memory. In complex FHE applications, these rotation keys can cause a large memory bottleneck limiting program throughput. Existing compilers make little effort to solve this problem, instead relying on systems with massive memory availability. This resource requirement is a barrier to FHE uptake because optimizing FHE programs by hand is challenging due to their scale, complexity and expertise required. In this work, we present KeyMemRT; an MLIR based compiler and runtime framework that individually manages rotation key lifetimes to lower memory utilization and to allow arbitrary number of rotation indices to be supported without memory bloating. KeyMemRT relies on dataflow analysis to determine key lifetimes and is the first FHE compiler to provide automatic key management, handle fine-grained key-mangement and manage boostrap keys. We implement frontends for Orion and HEIR and show improvements over state-of-the-art FHE compilers. KeyMemRT achieves memory reduction of 1.74x and a speedup of 1.20x over ANT-ACE, and memory reduction of 1.16x and a speedup of 1.73x over memory-optimized compiler Fhelipe. We provide KeyMemRT as a post-optimizing compiler that can be targeted by any FHE compiler.

翻译：全同态加密（Fully Homomorphic Encryption, FHE）能够实现隐私保护计算，但其存在高延迟和高内存消耗的问题。计算过程通过称为旋转密钥的特殊密钥进行保护，这些密钥通常占据内存的主要部分。在复杂的FHE应用中，旋转密钥可能导致巨大的内存瓶颈，从而限制程序吞吐量。现有编译器几乎未着力解决此问题，而是依赖于具有海量可用内存的系统。这种资源需求阻碍了FHE的普及，因为手动优化FHE程序因其规模庞大、复杂度高且需要专业知识而极具挑战性。本文提出KeyMemRT——一个基于MLIR的编译器与运行时框架，通过独立管理旋转密钥的生命周期来降低内存使用率，并支持任意数量的旋转索引而不会导致内存膨胀。KeyMemRT依赖数据流分析来确定密钥生命周期，是首个提供自动密钥管理、处理细粒度密钥管理并管理自举密钥的FHE编译器。我们为Orion和HEIR实现了前端，并展示了相对于最先进FHE编译器的改进。与ANT-ACE相比，KeyMemRT实现了1.74倍的内存缩减和1.20倍的加速；与内存优化编译器Fhelipe相比，实现了1.16倍的内存缩减和1.73倍的加速。我们将KeyMemRT作为一个后置优化编译器提供，可被任何FHE编译器集成使用。