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Application specific instruction set processors (ASIP) allow designers to optimize the architecture of an embedded processor to meet the specific demands of a particular application. A complementary form of customization is provided by domain-specific models of computation (MoCs), which can expose the high level structure of applications that is useful for various kinds of optimizing design transformations. One such MoC is Synchronous Dataflow (SDF), which is used increasingly in the design and implementation of signal processing applications. In this paper, we develop an integration of SDF- and ASIP-oriented design flows, and use this integrated design flow to explore trade-offs in the space of hardware/software implementations. We also explore an approach to ASIP implementation in terms of ldquocriticalrdquo and ldquonon-criticalrdquo applications, which allows designers to tune the degree of specialization for a targeted ASIP. Our results show that single ASIP processor tuned for pair of critical applications saves 26% to 50% of area required for implementations of two applications on separate ASIPs and non-critical applications runs on such processor with in worst case 4.5% overhead for our selection of benchmarks.