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.
翻译:在海量数据时代,信息安全已成为辩论的一个主要问题,特别是随着物联网(IoT)的兴起,攻击者可以不遗余力地获得对边缘装置的实际访问。大麻算法是目前数据完整性和认证的基础。然而,提供高性能、高通量和节能的关于资源紧缺边缘装置的解决方案是具有挑战性的。在本文件中,我们提议Inhale是一个SRAM内部架构,以有效计算散货算法,使其具有创新的数据一致性和高效的读/写战略,通过实境控制器暗中执行数据转换操作。我们提出了Inhale-Opt两种变式:Inhale-Opt,它最优化于拉紧性、吞吐量和地区overhead;Inhale-Flex,它为重塑最后一级缓存部分供仓储量计算提供了灵活性。我们彻底评价了我们提议的关于SRAM和ReRAM记忆的架构,并将它们与最新科技中和ASICE-A-SIC-C-C-C-C-CE-C-CE-ATI-C-A-ATINS-SD-Sy-ATI-ATI-ATI-ATI-ATI-ATI-ATI-ATI-ATI-ATINS-ATI-A-ATINS-I-ATINS-ATINS-ATI-ATI-ATI-A-A-A-A-A-ATI-A-ATI-ATI-ATI-ATI-ATI-ATI-ATINS-ATI-ATI-ATI-ATI-ATI-ATI-ATI-A-ATI-A-A-A-ATI-A-A-A-A-S-S-A-A-A-A-A-ATI-ATI-A-S-ATI-ATI-ATI-ATI-ATI-A-A-A-A-A-A-A-A-A-A-A-A-A-A-ATI-A-A-A-A-A-ATI-A-A-A-A-A-A-A-A-A-A-A-A-A-A-A-A-