FHEmem: A Processing In-Memory Accelerator for Fully Homomorphic Encryption

Fully Homomorphic Encryption (FHE) is a technique that allows arbitrary computations to be performed on encrypted data without the need for decryption, making it ideal for secure computation outsourcing. However, computation on FHE-encrypted data is significantly slower than that on plain data, primarily due to the explosive increases in data size and computation complexity after encryption. To enable real-world FHE applications, recent research has proposed several custom hardware accelerators that provide orders of magnitude speedup over conventional systems. However, the performance of existing FHE accelerators is severely bounded by memory bandwidth, even with expensive on-chip buffers. Processing In-Memory (PIM) is a promising technology that can accelerate data-intensive workloads with extensive internal bandwidth. Unfortunately, existing PIM accelerators cannot efficiently support FHE due to the limited throughput to support FHE’s complex computing and data movement operations. To tackle such challenges, we propose FHEmem, an FHE accelerator using a novel PIM architecture for high-throughput FHE acceleration. Furthermore, we present an optimized end-to-end processing flow with an automated mapping framework to maximize the hardware utilization of FHEmem. Our evaluation shows that FHEmem achieves at least 4.0× speedup and 6.9× energy-delay-area efficiency improvement over state-of-the-art FHE accelerators on popular FHE applications.