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
zigzag.cost_model.cost_model Namespace Reference

Classes

class  MemoryUtilization
 
class  CostModelEvaluationABC
 Superclass for CostModelEvaluation and CumulativeCME. More...
 
class  CumulativeCME
 Represents the sum of multiple CMEs. More...
 
class  CostModelEvaluation
 Class that stores inputs and runs them through the zigzag cost model. More...
 

Variables

 logger = logging.getLogger(__name__)
 

Variable Documentation

◆ logger

logger = logging.getLogger(__name__)