ZigZag - Deep Learning Hardware Design Space Exploration
This repository presents the novel version of our tried-and-tested hardware Architecture-Mapping Design Space Exploration (DSE) Framework for Deep Learning (DL) accelerators. ZigZag bridges the gap between algorithmic DL decisions and their acceleration cost on specialized accelerators through a fast and accurate hardware cost estimation.
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Namespaces | |
zigzag.visualization.results.print_mapping | |
Functions | |
def | print_mapping (CostModelEvaluationABC cme, int offsets=2) |
Prints a structured representation of a CostModelEvaluation mapping. More... | |