دانلود رایگان مقاله انگلیسی یک چارچوب تحلیل برای پیاده سازی سخت افزار و نرم افزار با برنامه های رمزنگاری - الزویر 2018

abstract

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.

7. Conclusion

Modern high-performance computers are hybrids of multi-core processors, GPUs, FPGAs, etc. In this paper, a statistical framework is developed to provide thorough analysis and evaluation of algorithms and their implementations on different processing systems. A generic benchmark model is created to present the framework with clarity. The framework categorizes processing subsystems into profiles, where each can be contextualized according to a specific application. The statistical framework is adopted to analyze and evaluate a set of cryptographic algorithms that are claimed to be small in size, tiny, and efficient. The proposed framework enabled the creation of several key indicators including the lightness, complexity, security strength, and speed indicators. The two main targeted high-performance computing devices are multi-core processors for software implementations and high-end FPGAs for hardware implementations. The developed lightness indicator ranks the 3-Way algorithm as the lightest among all with an LI of 2.52. Hight achieves the second best lightness with a score of 1.93. The lowest score of 0.79 was attained by KATAN-64. The case-study validates the statistical framework and leads to a successful classification of the targeted algorithms. The obtained results are based on a combination of three profiles including the algorithmic, software, and hardware profiles. The presented framework enjoys being scalable, upgradeable, and portable across-applications. Future work includes incorporating additional processing systems, targeting other areas of application, and embedding the framework within a co-design IDE and target partitioned implementations.