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A streaming application, characterized by a kernel that can be broken down into independent tasks which can be executed in a pipelined fashion, inherently allows its implementation on a pipeline of Application Specific Instruction set Processors (ASIPs), called a pipelined MPSoC. The latency and throughput requirements of streaming applications put constraints on the design of such a pipelined MPSoC, where each ASIP has a number of available configurations differing by additional instructions, and instruction and data cache sizes. Thus, the design space of a pipelined MPSoC is all the possible combinations of ASIP configurations (design points). In this paper, a methodology is proposed to optimize the area of a pipelined MPSoC under a latency or a throughput constraint. The final design point is a set of ASIP configurations with one configuration for each ASIP. We proposed an Integer Linear Programming (ILP) based solution to the area optimization problem under a latency constraint, and an algorithm for optimization of pipelined MPSoC area under a throughput constraint. The proposed solutions were evaluated using four streaming applications: JPEG encoder; JPEG decoder; MP3 encoder; and H.264 decoder. The time to find the Pareto front of each pipelined MPSoC was less than 4 minutes where design spaces had up to 1016 design points, illustrating the applicability of our approach.
Date of Conference: 24-29 Oct. 2010