Manycores architectures consist of hundreds to thousands of embedded cores, distributed memories and a dedicated network on a single chip. In this context, and because of the scale of the processor, providing a shared memory system has to rely on efficient hardware and software mechanisms and data consistency protocols. Numerous works explored consistency mechanisms designed for highly parallel architectures. They lead to the conclusion that there won't exist one protocol that fits to all applications and hardware contexts. In order to deal with consistency issues for this kind of architectures, we propose in this work a multi-protocol compilation toolchain, in which shared data of the application can be managed by different protocols. Protocols are chosen and configured at compile time, following the application behaviour and the targeted architecture specifications. The application behaviour is characterized with a static analysis process that helps to guide the protocols assignment to each data access. The platform offers a protocol library where each protocol is characterized by one or more parameters. The range of possible values of each parameter depends on some constraints mainly related to the targeted platform. The protocols configuration relies on a genetic-based engine that allows to instantiate each protocol with appropriate parameters values according to multiple performance objectives. In order to evaluate the quality of each proposed solution, we use different evaluation models. We first use a traffic analytical model which gives some NoC communication statistics but no timing information. Therefore, we propose two cycle- based evaluation models that provide more accurate performance metrics while taking into account contention effect due to the consistency protocols communications.We also propose a cooperative cache consistency protocol improving the cache miss rate by sliding data to less stressed neighbours. An extension of this protocol is proposed in order to dynamically define the sliding radius assigned to each data migration. This extension is based on the mass-spring physical model. Experimental validation of different contributions uses the sliding based protocols versus a four-state directory-based protocol.
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