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 ONNXModelParser, including all inherited members.
__init__(self, str|ModelProto onnx_model, str mapping_yaml_path) | ONNXModelParser | |
get_parser_class(self, NodeProto node) | ONNXModelParser | |
mapping_data | ONNXModelParser | |
mapping_yaml_path | ONNXModelParser | |
onnx_model | ONNXModelParser | |
parse_workload_from_onnx_model_and_mapping(self) | ONNXModelParser | |
run(self) | ONNXModelParser | |
workload | ONNXModelParser |