A first analysis framework to handle dynamic application behavior in dataflow applications


At the Chair for Compiler Construction cfaed members affiliated with the orchestration path have devised a series of approaches to analyse and efficiently cope with dynamic software application behaviors. The problem addressed is that current approaches for mapping and scheduling applications described as Kahn Process Networks (KPN) and Dynamic Data Flow (DDF) rely on assumptions on the program behavior specific to an execution. Thus, a near-optimal mapping, computed for a given input data set, may become sub-optimal at run-time. This happens when a different data set induces a significantly different behavior.

The approach to analyse and handle this leverages inherent mathematical structures of the dataflow models of computation and the hardware architectures. On the side of the dataflow models, it relies on the monoid structure of histories and traces. This structure helps formalize the behavior of multiple executions of a given dynamic application. It uses metrics to define a formal framework for comparing the executions. On the side of the the hardware, the approach takes advantage of symmetries in the architecture to reduce the search space for the mapping problem. (Download paper.)


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