  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.
