Speculative Dataflow Circuits

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Abstract

With FPGAs facing broader application domains, the conversion of imperative languages into dataflow circuits has been recently revamped as a way to overcome the conservatism of statically scheduled high-level synthesis. Apart from the ability to extract parallelism in irregular and control-dominated applications, dynamic scheduling opens a door to speculative execution, one of the most powerful ideas in computer architecture. Speculation allows executing certain operations before it is known whether they are correct or required: it can significantly increase fine-grain parallelism in loops where the condition takes many cycles to compute; it can also increase the performance of circuits limited by potential dependencies by assuming independence early on and by reverting to the correct execution if the prediction was wrong. In this work, we detail our methodology to enable tentative and reversible execution in dynamically scheduled dataflow circuits. We create a generic framework for handling speculation in dataflow circuits and show that our approach can achieve significant performance improvements over traditional circuit generation techniques.