FHEIns: Fully Homomorphic Encryption Acceleration for Large Data Applications with In-Storage Processing

Recently, the significance of data privacy protection has been growing rapidly. Homomorphic encryption (HE) enables computation directly on ciphertexts, making it attractive for privacy-sensitive databases in cloud datacenters. Although FHE enables privacy-preserving compute, ciphertext expansion and long-latency primitives drive up memory footprint and delay, worsening compute and memory pressure for database search. In practice, encrypted databases span hundreds of gigabytes to terabytes, making the storage I/O the dominant bottleneck. However, most prior FHE accelerators optimize on-chip computation and the main memory traffic while assuming working sets fit in HBM. Therefore, in this work, we present FHEIns, an in-storage processing architecture that executes FHE kernels close to data inside the NAND flash-based solid-state drives (SSDs) to exploit the internal bandwidth of the SSD. FHEIns achieves up to 24.7× and 2.67× speedup compared to the state-of-the-art FHE ASIC accelerators on trending FHE-based database benchmarks.