International Business Machines Corporation

Weichung Wang

Bhuvana Ramabhadran

I-Hsin Chung

Paul Gregory Crumley

Huifang Wen

A method and an apparatus of allocating available resources in a cluster system with learning models and tuning methods are provided. The learning model may be trained from historic performance data of previously executed jobs and used to project a suggested amount of resources for execution of a job. The tuning process may suggest a configuration for the projected amount of resources in the cluster system for an optimal operating point. An optimization may be performed with respect to a set of objective functions to improve resource utilization and system performance while suggesting the configuration. Through many executions and job characterization, the learning/tuning process for suggesting the configuration for the projected amount of resources may be improved by understanding correlations of historic data and the objective functions.

Growing community of inventors

Yorktown Heights, NY, United States of America

Weichung Wang