FHEmem: A Processing In-Memory Accelerator for Fully Homomorphic Encryption
CoRR(2023)
摘要
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 securing many emerging applications. However, FHE
computation is significantly slower than computation on plain data due to the
increase in data size after encryption. Processing In-Memory (PIM) is a
promising technology that can accelerate data-intensive workloads with
extensive parallelism. However, FHE is challenging for PIM acceleration due to
the long-bitwidth multiplications and complex data movements involved. We
propose a PIM-based FHE accelerator, FHEmem, which exploits a novel processing
in-memory architecture to achieve high-throughput and efficient acceleration
for FHE. We propose an optimized end-to-end processing flow, from low-level
hardware processing to high-level application mapping, that fully exploits the
high throughput of FHEmem hardware. Our evaluation shows FHEmem achieves
significant speedup and efficiency improvement over state-of-the-art FHE
accelerators.
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