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기록

ABSTRACTION LAYERS FOR SCALABLE DISTRIBUTED MACHINE LEARNING

발명심사 중
1조회수
21청구항 · 4 독립항
§ Ⅰ

개요

발명자

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

IPC 분류

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

CPC 분류

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.

원문 (중국어)

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.