- 专利标题: DETERMINING OPTIMAL DATA ACCESS FOR DEEP LEARNING APPLICATIONS ON A CLUSTER
-
申请号: US17305735申请日: 2021-07-14
-
公开(公告)号: US20230014344A1公开(公告)日: 2023-01-19
- 发明人: Srikumar Venugopal , Archit Patke , Ioannis Gkoufas , Christian Pinto , Panagiotis Koutsovasilis
- 申请人: International Business Machines Corporation
- 申请人地址: US NY Armonk
- 专利权人: International Business Machines Corporation
- 当前专利权人: International Business Machines Corporation
- 当前专利权人地址: US NY Armonk
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G06F9/50 ; G06F12/0815 ; G06K9/62
摘要:
A computer-implemented method, a computer program product, and a computer system for determining optimal data access for deep learning applications on a cluster. A server determines candidate cache locations for one or more compute nodes in the cluster. The server fetches a mini-batch of a dataset located at a remote storage service into the candidate cache locations. The server collects information about time periods of completing a job on the one or more nodes, where the job is executed against fetched mini-batch at the candidate cache locations and the mini-batch at the remote storage location. The server selects, from the candidate cache locations and the remote storage location, a cache location. The server fetches the data of the dataset from the remote storage service to the cache location, and the one or more nodes execute the job against fetched data of the dataset at the cache location.
信息查询