Frontiers in Nanotechnology (Mar 2022)

In-Memory Computation Based Mapping of Keccak-f Hash Function

  • Sandeep Kaur Kingra,
  • Vivek Parmar,
  • Manan Suri

DOI
https://doi.org/10.3389/fnano.2022.841756
Journal volume & issue
Vol. 4

Abstract

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Cryptographic hash functions play a central role in data security for applications such as message authentication, data verification, and detecting malicious or illegal modification of data. However, such functions typically require intensive computations with high volume of memory accesses. Novel computing architectures such as logic-in-memory (LIM)/in-memory computing (IMC) have been investigated in the literature to address the limitations of intense compute and memory bottleneck. In this work, we present an implementation of Keccak-f (a state-of-the-art secure hash algorithm) using a variant of simultaneous logic-in-memory (SLIM) that utilizes emerging non-volatile memory (NVM) devices. Detailed operation and instruction mapping on SLIM-based digital gates is presented. Through simulations, we benchmark the proposed approach using LIM cells based on four different emerging NVM devices (OxRAM, CBRAM, PCM, and FeRAM). The proposed mapping strategy when used with state-of-the-art emerging NVM devices offers EDP savings of up to 300× compared to conventional methods.

Keywords