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 highend 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.
Reconfigurable devices, such as Field Programmable Gate Arrays (FPGAs), have been witnessing a considerable increase in density. State-of-the-art FPGAs are complex hybrid devices that contain up to several millions of gates. Recently, research effort has been going into higher-level parallelization and hardware synthesis methodologies that can exploit such a programmable technology. In this paper, we explore the effectiveness of one such formal methodology in the design of parallel versions of the Serpent cryptographic algorithm. The suggested methodology adopts a functional programming notation for specifying algorithms and for reasoning about them. The specifications are realized through the use of a combination of function decomposition strategies, data refinement techniques, and off-the-shelf refinements based upon higher-order functions. The refinements are inspired by the operators of Communicating Sequential Processes and map easily to programs in Handel-C (a hardware description language). In the presented research, we obtain several parallel Serpent implementations with different performance characteristics. The developed designs are tested under Celoxica's RC-1000 reconfigurable computer with its two million gates Virtex-E FPGA. Performance analysis and evaluation of these implementations are included.
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