Inhale: Enabling High-Performance and Energy-Efficient In-SRAM Cryptographic Hash for IoT

TL;DR

Inhale is an innovative in-SRAM architecture designed to perform cryptographic hash computations efficiently, significantly improving throughput and energy efficiency for resource-constrained IoT devices.

Contribution

The paper introduces Inhale, a novel in-SRAM architecture with two variants, enabling high-performance, energy-efficient hash computations tailored for IoT edge devices.

Findings

Achieves 1.4x - 14.5x higher throughput-per-area

Provides about two-orders-of-magnitude higher throughput-per-area-per-energy

Demonstrates effectiveness on SRAM and ReRAM memories

Abstract

In the age of big data, information security has become a major issue of debate, especially with the rise of the Internet of Things (IoT), where attackers can effortlessly obtain physical access to edge devices. The hash algorithm is the current foundation for data integrity and authentication. However, it is challenging to provide a high-performance, high-throughput, and energy-efficient solution on resource-constrained edge devices. In this paper, we propose Inhale, an in-SRAM architecture to effectively compute hash algorithms with innovative data alignment and efficient read/write strategies to implicitly execute data shift operations through the in-situ controller. We present two variations of Inhale: Inhale-Opt, which is optimized for latency, throughput, and area-overhead; and Inhale-Flex, which offers flexibility in repurposing a part of last-level caches for hash computation. We thoroughly evaluate our proposed architectures on both SRAM and ReRAM memories and compare them with the state-of-the-art in-memory and ASIC accelerators. Our performance evaluation confirms that Inhale can achieve 1.4x - 14.5x higher throughput-per-area and about two-orders-of-magnitude higher throughput-per-area-per-energy compared to the state-of-the-art solutions.