FALCON: A framework for hierarchical computation of metrics for component-based parameterized SoCs

In this paper, we focus on systematic and efficient computation (accurate value or an estimate) of metrics such as performance, power, energy, etc. of a component-based parameterized system-on-chip (SoC). Traditionally, given models of SoC components (such as cycle-accurate simulator of a processor, trace-based simulator of a cache/memory), a designer manually determines an execution schedule of these models (such as execute processor simulator, followed by cache/memory simulator) to combine/propagate their individual results for computation of a SoC metric. To reduce designer's effort, we propose FALCON, a framework where the execution schedule of component models is generated automatically, and a minimal number of model executions is used to compute values of a SoC metric for the given component models and design space (resulting from component parameter values). FALCON is semi-automated, is applicable to a wide range of SoC platforms with ease, and works with existing design space exploration algorithms. In three case studies (uniprocessor system, multiprocessor pipeline system and multiprocessor mesh network-on-chip system), FALCON reduced designer's effort (measured in minutes) by at least two orders of magnitude.