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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This is the complete list of members for ServedMemDimensions, including all inherited members.
__contains__(self, OADimension other) | ServedMemDimensions | |
__eq__(self, Any other) | ServedMemDimensions | |
__init__(self, set[OADimension] data) | ServedMemDimensions | |
__iter__(self) | ServedMemDimensions | |
__len__(self) | ServedMemDimensions | |
__str__(self) | ServedMemDimensions | |
data | ServedMemDimensions | |
nb_dims(self) | ServedMemDimensions |