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.
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This is the complete list of members for LoopRelevancyInfo, including all inherited members.
__init__(self) | LoopRelevancyInfo | |
create_pr_decoupled_relevancy_info(self) | LoopRelevancyInfo | |
extract_relevancy_info(LayerEquation equation, LayerDimSizes layer_dim_sizes, PrLoop pr_loop, LoopList pr_loop_list) | LoopRelevancyInfo | static |
get_ir_layer_dims(self, LayerOperand layer_operand) | LoopRelevancyInfo | |
get_pr_layer_dims(self, LayerOperand layer_operand) | LoopRelevancyInfo | |
get_r_layer_dims(self, LayerOperand layer_operand) | LoopRelevancyInfo | |
get_r_or_pr_layer_dims(self, LayerOperand layer_operand) | LoopRelevancyInfo | |
orig_pr_loop | LoopRelevancyInfo |