- 专利标题: SAMPLER AND APPARATUS FOR EXECUTING GRAPH NEURAL NETWORK MODEL
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申请号: US17677927申请日: 2022-02-22
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公开(公告)号: US20220318592A1公开(公告)日: 2022-10-06
- 发明人: Tianchan GUAN , Yanhong WANG , Shuangchen LI , Heng LIU , Hongzhong ZHENG
- 申请人: Alibaba (China) Co., Ltd.
- 申请人地址: CN Hangzhou
- 专利权人: Alibaba (China) Co., Ltd.
- 当前专利权人: Alibaba (China) Co., Ltd.
- 当前专利权人地址: CN Hangzhou
- 优先权: CN202110231273.7 20210302
- 主分类号: G06N3/04
- IPC分类号: G06N3/04 ; G06F7/58
摘要:
A sampler for executing a graph neural network (GNN) model are disclosed. The sampler is configured to implement random sampling for neighbor nodes around a specified node of a GNN model, and performs: obtaining a quantity of neighbor nodes around the specified node and a target number of neighbor nodes to be sampled; dividing a range into a plurality of subranges based on the target number; generating random numbers; determining a plurality of integer values within the plurality of subranges based on the random numbers; determining index values of the target number of neighbor nodes to be sampled by matching index values of the neighbor nodes and the plurality of determined integer values; and writing the determined index values into an output buffer. The sampler provided in the present disclosure can uniformly sample the neighbor nodes around the specified node for the specified node.
公开/授权文献
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