ZigZag - Deep Learning Hardware Design Space Exploration: /home/runner/work/zigzag/zigzag/zigzag/stages/results/reduce_stages.py File Reference

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
class	MinimalEnergyStage
	Class that keeps yields only the cost model evaluation that has minimal energy of all cost model evaluations generated by it's substages created by list_of_callables. More...

class	MinimalLatencyStage
	Class that keeps yields only the cost model evaluation that has minimal latency of all cost model evaluations generated by it's substages created by list_of_callables. More...

class	MinimalEDPStage
	Class that keeps yields only the cost model evaluation that has minimal EDP of all cost model evaluations generated by it's substages created by list_of_callables. More...

class	SumStage
	Class that keeps yields only the sum of all cost model evaluations generated by its substages created by list_of_callables. More...

Namespaces
	reduce_stages

Variables
	logger = logging.getLogger(__name__)