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ABSTRACTION LAYERS FOR SCALABLE DISTRIBUTED MACHINE LEARNING

发明专利审中
21权利要求 · 4 独立
§ Ⅰ

卷宗概要

发明人

Dhiraj D. KALAMKAR; Karthikeyan VAIDYANATHAN; Srinivas SRIDHARAN; Dipankar DAS

IPC 分类

G6T 1/20G6N 3/44G6N 3/45G6N 3/63G6N 3/84

CPC 分类

G6T1/20G6N3/44G6N3/45G6N3/63G6N3/84

One embodiment provides for a method of transmitting data between multiple compute nodes of a distributed compute system, the method comprising creating a global view of communication operations to be performed between the multiple compute nodes of the distributed compute system, the global view created using information specific to a machine learning model associated with the distributed compute system; using the global view to determine a communication cost of the communication operations; and automatically determining a number of network endpoints for use in transmitting the data between the multiple compute nodes of the distributed compute system.

原文(中文)

One embodiment provides for a method of transmitting data between multiple compute nodes of a distributed compute system, the method comprising creating a global view of communication operations to be performed between the multiple compute nodes of the distributed compute system, the global view created using information specific to a machine learning model associated with the distributed compute system; using the global view to determine a communication cost of the communication operations; and automatically determining a number of network endpoints for use in transmitting the data between the multiple compute nodes of the distributed compute system.