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 OperationalArray, including all inherited members.
__eq__(self, Any other) | OperationalArray | |
__init__(self, OperationalUnit operational_unit, dict[OADimension, int] dimension_sizes) | OperationalArray | |
architecture::operational_array::OperationalArrayABC.__init__(self, dict[OADimension, int] dimension_sizes) | OperationalArrayABC | |
__jsonrepr__(self) | OperationalArray | |
dimension_sizes | OperationalArray | |
total_area | OperationalArray | |
total_unit_count | OperationalArray | |
unit | OperationalArray |