Huawei Technologies Co., Limited

Zhejiang Lab

Hongcai Cheng

Wei Dong Chen

Yu Hu

Hujun Bao

Hongsheng Wang

Haitao Guo

Guang Chen

Can Chen

Chunyi Tan

Hao Chen

Yong Li

Hongguang Liu

Sicong Li

Lingfang Zeng

Jian Zhu

Huanbo Zheng

The present disclosure discloses a method for execution of a computational graph in a neural network model and an apparatus thereof, including: creating task execution bodies on a native machine according to a physical computational graph compiled and generated by a deep learning framework, and designing a solution for allocating a plurality of idle memory blocks to each task execution body, so that the entire computational graph participates in deep learning training tasks of different batches of data in a pipelining and parallelizing manner.

Method for execution of computational graph in neural network model and apparatus thereof

A data processing system and method, and a corresponding apparatus, where the data processing system includes a controller and at least two storage nodes. The controller is configured to receive, using a first coupling between the controller and a host, an operation request received from the host, where the operation request includes an identity of target data and an operation type, determine at least one target storage node from the at least two storage nodes according to the identity of the target data, and send an instruction message to the at least one target storage node using a second coupling to the at least one target storage node, where the at least one target storage node is configured to send the target data to the host or obtain the target data from the host according to the instruction message.

Method, apparatus, and data processing system including controller to manage storage nodes and host operations

Growing community of inventors

Hangzhou, China

Hongcai Cheng