An efficient exploration of multimedia architecture using weighted parameter dependency and sampled-data simulation
This paper proposes a system-level design methodology for efficient exploration of parameterized multimedia architecture. The purpose is to find a near-optimal configuration, as far as possible, without performing exhaustive analysis of the design space. This is done through synergistic integration of two independent methodologies, first of which is the multi-stage dynamic optimization based on parameters clustering and sparsing, while the second one being a quick performance estimation through sampled-data simulation of target multimedia application. The experimental results with mediabench show speedup ranging from 186.4 to 339.8, while the corresponding error-to-global optimum ranges from 14.8% to 16.4%.
parameter dependency sampled-data simulation design space exploration