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.
Classes | Namespaces | Variables
save.py File Reference

Classes

class  CompleteSaveStage
 Class that passes through all results yielded by substages, but saves the results as a json list to a file at the end of the iteration. More...
 
class  SimpleSaveStage
 Class that passes through results yielded by substages, but saves the results as a json list to a file at the end of the iteration. More...
 
class  PickleSaveStage
 Class that dumps all received CMEs into a list and saves that list to a pickle file. More...
 

Namespaces

 save
 

Variables

 logger = logging.getLogger(__name__)