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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Directories | |
directory | cacti |
directory | cost_model |
directory | hardware |
directory | mapping |
directory | opt |
directory | parser |
directory | stages |
directory | visualization |
directory | workload |
Files | |
file | __init__.py |
file | __main__.py |
file | api.py |
file | datatypes.py |
file | utils.py |