MEng Individual Project Aspect Oriented Design for Dataflow Engines
نویسنده
چکیده
Dataflow designs implemented on custom streaming architectures can be orders of magnitudes more efficient than traditional software, but they are developed with reduced productivity. We propose a novel design flow for generating dataflow designs based on Aspect-oriented programming and explain how the proposed approach can be used to decouple design optimisation from design specification by encapsulating optimisations in separate aspect descriptions, which leads to improved productivity and efficiency. To support this approach we introduce a novel dataflow language that facilitates integration with existing aspect weaving tools and simplifies design development by supporting embedded hardware/software co-design, flexible number representation and run-time reconfiguration. We introduce novel aspect descriptions that specify system-level and implementation level optimisations strategies as well as strategies for improving developer productivity. We evaluate our approach on a number of applications, including advanced high-performance applications, such as the Reverse Time Migration technique for seismic imaging, and show that efficient dataflow designs up to 100 times faster than equivalent software only implementations can be derived with improved productivity.
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تاریخ انتشار 2013