MeNTT: A Compact and Efficient Processing-in-Memory Number Theoretic Transform (NTT) Accelerator
February 17, 2022 Β· Declared Dead Β· π IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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Authors
Dai Li, Akhil Pakala, Kaiyuan Yang
arXiv ID
2202.08446
Category
cs.CR: Cryptography & Security
Cross-listed
eess.SY
Citations
38
Venue
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Last Checked
6 months ago
Abstract
Lattice-based cryptography (LBC) exploiting Learning with Errors (LWE) problems is a promising candidate for post-quantum cryptography. Number theoretic transform (NTT) is the latency- and energy- dominant process in the computation of LWE problems. This paper presents a compact and efficient in-MEmory NTT accelerator, named MeNTT, which explores optimized computation in and near a 6T SRAM array. Specifically-designed peripherals enable fast and efficient modular operations. Moreover, a novel mapping strategy reduces the data flow between NTT stages into a unique pattern, which greatly simplifies the routing among processing units (i.e., SRAM column in this work), reducing energy and area overheads. The accelerator achieves significant latency and energy reductions over prior arts.
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