US 11,694,075 B2
Partitioning control dependency edge in computation graph
Xinli Cai, San Mateo, CA (US)
Assigned to Alibaba Group Holding Limited, Grand Cayman (KY)
Filed by ALIBABA GROUP HOLDING LIMITED, Grand Cayman (KY)
Filed on Sep. 5, 2019, as Appl. No. 16/562,393.
Prior Publication US 2021/0073625 A1, Mar. 11, 2021
Int. Cl. G06N 3/08 (2023.01); G06N 3/04 (2023.01)
CPC G06N 3/08 (2013.01) [G06N 3/04 (2013.01)] 12 Claims
OG exemplary drawing
 
1. A method for adapting a computation graph of a machine learning model, comprising:
partitioning the computation graph into a first subgraph and a second subgraph at an edge between a first node and a second node, wherein the edge is a control dependency edge;
inserting a proxy node, a send node, and a receive node between the first node and the second node, wherein the proxy node is connected to the first node, the send node is configured to receive output data from the proxy node, and the receive node is configured to receive the output data from the send node, wherein the proxy node and the second node are included in the first subgraph and the receive node is included in the second subgraph; and
executing the first subgraph on a first accelerator and the second subgraph on a second accelerator, wherein the first accelerator is configured to execute the proxy node after executing the first node and to transfer the output data of the proxy node to the send node, and the second accelerator is configured to initiate execution of the receive node when the output data from the send node is transferred to or accessible by the second accelerator.