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Abstract-With growing market pressures and rising system complexities, automated system-level communication design with efficient design space exploration capabilities is becoming increasingly important. At the same time, customized network-oriented communication architectures become necessary in enabling a high-performance communication among the system components. To this end, corresponding communication design flows that are supported by efficient design automation techniques need to be developed. In this paper, we present a system-level design environment for the generation of bus-based system-on-chip architectures. Our approach supports a two-stage design flow using automated model refinement toward custom heterogeneous communication networks. Starting from an abstract specification of the desired communication channels, our environment automatically generates tailored network models at various levels of abstraction. At its core, an automatic layer-based refinement approach is utilized. We have applied our approach to a set of industrial-strength examples with a wide range of target architectures. Our experimental results show significant productivity gains over a traditional communication design, allowing early and rapid design space exploration.Index Terms-Communication synthesis, embedded systems, heterogeneous multiprocessor system-on-chip (MPSoC), systemlevel design, transaction-level modeling (TLM).

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Abstract-Communication exploration has become a critical step during SoC design. Researchers in the CAD community have proposed fast and efficient techniques for comprehensive design space exploration to expedite this critical design step. Although these advances have been helpful in reducing the design time significantly, the overall design time of the system is still a bottleneck. All these techniques assume the availability of an initial SoC input model with explicit communication, whose quality significantly impacts the effectiveness of the communication exploration techniques. Today, these initial models need to be manually written by engineers, which is tedious, error-prone and time consuming. In fact, our studies on industrial-size examples have shown that about 50% of the communication exploration time is spent on coding and re-coding of the initial specification model. In this paper, we propose an efficient interactive approach to explicit communication creation by automating some of the common coding tasks in specification models for communication exploration. Our results show significant savings in designer time.

Transaction-level modeling has been touted to improve simulation performance and modeling efficiency for early design space exploration. But no tools are available to generate such transaction-level models from abstract input descriptions. Designers have to write such models manually, which is a tedious and error-prone task, and one of bottlenecks in improving designer's productivity. In this paper, we propose a method to generate transaction-level models from virtual architecture models where components communicate via abstract message-passing channels. We have applied our approach to a set of industrial-strength examples with a wide range of target architectures. Experimental results show that significant productivity gains can be achieved, demonstrating the effectiveness and benefits of our approach for rapid, early exploration of communication design space.

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Message-passing mechanism is commonly used to preserve data coherency in distributed systems. This paper presents an algorithm for insertion of minimal message-passing in system-level design to guarantee data coherency. The target architecture is a multi-component heterogeneous system, where some components have local memory (or they are memory components by themselves. The algorithm enables automatic insertion of message-passing during systemlevel design to relieve designers from tedious and error-prone manual work. The optimal solution given by the algorithm also ensures the quality of automatic insertion. Experiments show that the automatic approach achieves a productivity gain of 200X over manual refinement.

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