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 DataMovePattern, including all inherited members.
__init__(self, LayerOperand operand, int mem_level) | DataMovePattern | |
__repr__(self) | DataMovePattern | |
__str__(self) | DataMovePattern | |
get_attribute(self, DataMoveAttr attr) | DataMovePattern | |
name | DataMovePattern | |
set_attribute(self, DataMoveAttr attr, dict[DataDirection, int] values) | DataMovePattern | |
update_single_dir_data(self, DataDirection direction, int new_value) | DataMovePattern |