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 AccessEnergy, including all inherited members.
__add__(self, "FourWayDataMoving[float]" other) | AccessEnergy | |
zigzag::mapping::data_movement::FourWayDataMoving.__add__(self, "FourWayDataMoving[T]" other) | FourWayDataMoving | |
__init__(self, dict[DataDirection, T]|None data=None) | FourWayDataMoving | |
__jsonrepr__(self) | FourWayDataMoving | |
__mul__(self, float scalar) | AccessEnergy | |
zigzag::mapping::data_movement::FourWayDataMoving.__mul__(self, T scalar) | FourWayDataMoving | |
__repr__(self) | FourWayDataMoving | |
get(self, DataDirection direction) | FourWayDataMoving | |
set(self, DataDirection direction, T value) | FourWayDataMoving |