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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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General class for a unit that performs a certain operation. More...

Public Member Functions | |
| def | __init__ (self, float energy_cost, float area) |
| General class for a unit that performs a certain operation. More... | |
| def | __jsonrepr__ (self) |
| JSON Representation of this class to save it to a json file. More... | |
| bool | __eq__ (self, object other) |
Public Attributes | |
| energy_cost | |
| area | |
General class for a unit that performs a certain operation.
For example: a multiplier unit.
| def __init__ | ( | self, | |
| float | energy_cost, | ||
| float | area | ||
| ) |
General class for a unit that performs a certain operation.
For example: a multiplier unit.
| energy_cost | The energy cost of performing a single operation. |
| area | The area of a single operational unit. |
| bool __eq__ | ( | self, | |
| object | other | ||
| ) |
| def __jsonrepr__ | ( | self | ) |
JSON Representation of this class to save it to a json file.

| area |
| energy_cost |