ABSTRACTION LAYERS FOR SCALABLE DISTRIBUTED MACHINE LEARNING

ABSTRACTION LAYERS FOR SCALABLE DISTRIBUTED MACHINE LEARNING

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 cre...

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Bibliographische Detailangaben
Hauptverfasser: VAIDYANATHAN, KARTHIKEYAN, SRIDHARAN, SRINIVAS, KALAMKAR, DHIRAJ D, DAS, DIPANKAR
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
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Beschreibung
Zusammenfassung: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.