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
workload_abc.py File Reference

Classes

class  WorkloadABC
 Abstract Base Class for workloads, parameterizable with type T, which must be a (subclass from) LayerNodeABC. More...
 
class  WorkloadNoDummyABC
 

Namespaces

 zigzag.workload.workload_abc
 

Variables

 T = TypeVar("T", bound=LayerNodeABC)