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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Abstract Base Class for workloads, parameterizable with type T, which must be a (subclass from) LayerNodeABC. More...
Public Member Functions | |
"WorkloadNoDummyABC" | get_copy_no_dummy (self) |
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list[tuple[T, T]] | in_edges (self, T node, Literal[False] data) |
list[tuple[T, T, dict[str, Any]]] | in_edges (self, T node, Literal[True] data) |
list[tuple[T, T]] | in_edges (self, T node) |
list[tuple[T, T]]|list[tuple[T, T, dict[str, Any]]] | in_edges (self, T node, bool data=False) |
list[tuple[T, T, dict[str, Any]]] | out_edges (self, T node, Literal[True] data) |
list[tuple[T, T]] | out_edges (self, T node, Literal[False] data) |
list[tuple[T, T]] | out_edges (self, T node) |
list[tuple[T, T]]|list[tuple[T, T, dict[str, Any]]] | out_edges (self, T node, bool data=False) |
Iterator[tuple[T, int]] | in_degree (self) |
Iterator[tuple[T, int]] | out_degree (self, Literal[None] node) |
Iterator[tuple[T, int]] | out_degree (self) |
int | out_degree (self, T node) |
int|Iterator[tuple[T, int]] | out_degree (self, T|None node=None) |
Iterator[T] | successors (self, T node) |
Iterator[T] | predecessors (self, T node) |
Iterator[T] | topological_sort (self) |
None | add_node (self, T node) |
None | add_nodes_from (self, Sequence[T] node) |
None | remove_nodes_from (self, Iterator[T] nodes) |
None | add_edge (self, T edge_from, T edge_to) |
None | add_edges_from (self, Sequence[tuple[T, T]|tuple[T, T, Any]] edges) |
Iterator[list[T]] | all_simple_paths (self, T producer, T consumer) |
list[T] | shortest_path (self, T producer, T consumer) |
list[T] | node_list (self) |
T | get_node_with_id (self, int node_id) |
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def | __init__ (self, int node_id, str node_name) |
str | __repr__ (self) |
str | __str__ (self) |
def | __jsonrepr__ (self) |
JSON representation used for saving this object to a json file. More... | |
Additional Inherited Members | |
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Abstract Base Class for workloads, parameterizable with type T, which must be a (subclass from) LayerNodeABC.
"WorkloadNoDummyABC" get_copy_no_dummy | ( | self | ) |
Reimplemented in ONNXWorkload.