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1.9.1
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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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Class that stores a single for-loop's information. More...
Public Member Functions | |
| def | __init__ (self, LayerDim layer_dim, UnrollFactor size, str loop_type="temporal") |
| Initialize the loop with the given layer_dim string and size. More... | |
| def | __str__ (self) |
| def | __repr__ (self) |
| bool | __eq__ (self, object other) |
Public Attributes | |
| layer_dim | |
| size | |
| loop_type | |
Class that stores a single for-loop's information.
| def __init__ | ( | self, | |
| LayerDim | layer_dim, | ||
| UnrollFactor | size, | ||
| str | loop_type = "temporal" |
||
| ) |
Initialize the loop with the given layer_dim string and size.
| bool __eq__ | ( | self, | |
| object | other | ||
| ) |
| def __repr__ | ( | self | ) |
| def __str__ | ( | self | ) |
| layer_dim |
| loop_type |
| size |
1.9.1