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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 MemoryOperandLinks, including all inherited members.
| __contains__(self, Any key) | LayerAttribute | |
| __eq__(self, object other) | LayerAttribute | |
| __getitem__(self, Any key) | LayerAttribute | |
| __hash__(self) | LayerAttribute | |
| __init__(self, dict[LayerOperand, MemoryOperand] data) | MemoryOperandLinks | |
| zigzag::workload::layer_attribute::LayerAttribute.__init__(self, Any data) | LayerAttribute | |
| __iter__(self) | LayerAttribute | |
| __jsonrepr__(self) | LayerAttribute | |
| __len__(self) | LayerAttribute | |
| __repr__(self) | LayerAttribute | |
| __str__(self) | MemoryOperandLinks | |
| contains_layer_op(self, LayerOperand layer_op) | MemoryOperandLinks | |
| contains_mem_op(self, MemoryOperand mem_op) | MemoryOperandLinks | |
| copy(self) | MemoryOperandLinks | |
| data | MemoryOperandLinks | |
| layer_and_mem_ops(self) | MemoryOperandLinks | |
| layer_operands | MemoryOperandLinks | |
| layer_to_mem_op(self, LayerOperand layer_op) | MemoryOperandLinks | |
| mem_operands | MemoryOperandLinks | |
| mem_to_layer_op(self, MemoryOperand mem_op) | MemoryOperandLinks |