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.
workload Directory Reference

Files

file  __init__.py
 
file  dnn_workload.py
 
file  dummy_node.py
 
file  layer_attribute.py
 
file  layer_attributes.py
 
file  layer_node.py
 
file  layer_node_abc.py
 
file  onnx_workload.py
 
file  workload_abc.py