Invention Grant
- Patent Title: Dynamic computation rates for distributed deep learning
-
Application No.: US16925161Application Date: 2020-07-09
-
Publication No.: US11977986B2Publication Date: 2024-05-07
- Inventor: Wei Zhang , Xiaodong Cui , Abdullah Kayi , Alper Buyuktosunoglu
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agent Stosch Sabo
- Main IPC: G06N3/098
- IPC: G06N3/098 ; G06N3/045 ; G06N3/08 ; G06N5/043 ; G06N20/00 ; G06N20/20 ; G06F18/214

Abstract:
Embodiments of a method are disclosed. The method includes performing distributed deep learning training on multiple batches of training data using corresponding learners. Additionally, the method includes determining training times wherein the learners perform the distributed deep learning training on the batches of training data. The method also includes modifying a processing aspect of the straggler to reduce a future training time of the straggler for performing the distributed deep learning training on a new batch of training data in response to identifying a straggler of the learners by a centralized control.
Public/Granted literature
- US20220012629A1 DYNAMIC COMPUTATION RATES FOR DISTRIBUTED DEEP LEARNING Public/Granted day:2022-01-13
Information query