Dataflow methods are widely used for the design and implementation of signal processing functionality in cyber-physical systems. Systematically integrating instrumentation methods into dataflow-based design processes is important to facilitate trade-off assessment and tuning of alternative scheduling strategies. Such instrumentation-driven scheduler development is particularly important for dynamically structured signal processing computations. In this talk, we will present methods developed in the targeted dataflow interchange format (TDIF) environment for rigorously supporting instrumentation throughout the scheduling process. TDIF, a software tool for design and implementation of signal processing systems, emphasizes processes for retargetable design, analysis, and optimization of hardware and software. We will present an internal representation used within TDIF called the instrumented generalized schedule tree (IGST), and demonstrate the utility of IGSTs for constructing, representing, and manipulating dataflow graph schedules in connection with diverse forms of instrumentation functionality, including monitoring associated with memory usage, performance and energy consumption. This talk is based on joint work with Chung-Ching Shen, Hsiang-Huang Wu, Nimish Sane, and William Plishker.
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