DCCRPFMar 30, 2019

An Analysis Framework for Hardware and Software Implementations with Applications from Cryptography

arXiv:1904.01000v122 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the need for unified analysis in hardware-software co-design, particularly for cryptographic algorithms, but it appears incremental as it builds on existing frameworks and focuses on a specific domain.

The paper tackles the problem of classifying algorithms based on hardware and software implementation characteristics by proposing a unified statistical framework, which is applied to develop the Lightness Indicator System (LIS) for evaluating cryptographic algorithms on multi-core processors and FPGAs, with extensive performance analysis included.

With the richness of present-day hardware architectures, tightening the synergy between hardware and software has attracted a great attention. The interest in unified approaches paved the way for newborn frameworks that target hardware and software co-design. This paper confirms that a unified statistical framework can successfully classify algorithms based on a combination of the heterogeneous characteristics of their hardware and software implementations. The proposed framework produces customizable indicators for any hybridization of processing systems and can be contextualized for any area of application. The framework is used to develop the Lightness Indicator System (LIS) as a case-study that targets a set of cryptographic algorithms that are known in the literature to be tiny and light. The LIS targets state-of-the-art multi-core processors and high-end Field Programmable Gate Arrays (FPGAs). The presented work includes a generic benchmark model that aids the clear presentation of the framework and extensive performance analysis and evaluation.

Foundations

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