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 | Variables
spatial_mapping_conversion Namespace Reference

Classes

class  SpatialMappingConversionStage
 Pipeline stage that converts the spatial mapping from a user-provided spatial mapping across operational array dimensions to the internal spatial mapping representation used in the cost model. More...
 

Variables

 logger = logging.getLogger(__name__)
 

Variable Documentation

◆ logger

logger = logging.getLogger(__name__)