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End to end Deep Learning of Optimization Heuristics

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Figure

Figure 1: Building a predictive model. The model is originallytrained on performance data and features extracted from thesource code and the runtime behavior
Figure 1b shows our proposed methodology. Instead ofmanually extracting features from input programs to generate
Figure 4: DeepTune neural networks, configured for (a) het-erogeneous mapping, and (b) thread coarsening factor
Figure 4b shows the neural net-work configuration. We use the OpenCL kernel as input, and
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