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AssigneeBoard of Regents, The University of Texas System
InventorsLizy Kurian John, Reena Panda, Xinnian Zheng, Andreas Gerstlauer
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A method, system and computer program product for generating sets of training programs for machine learning models. Fixed values of one or more workload metrics are received from a user, where the workload metrics correspond to low-level program features which define particular low-level application behavior. A profile using the fixed values of the workload metrics is then created. A suite of synthetic applications is generated using the created profile to form a set of training programs which target particular aspects of program behavior. A machine learning model is then trained using the set of training programs. Since the generated synthetic applications provide a broader coverage of the program state-space, the formed set of training programs more accurately targets performance behavior thereby improving the prediction accuracy of the machine learning based predictive models.
A method for generating sets of training programs for machine learning models, the method comprising:
A computer program product for generating sets of training programs for machine learning models, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code comprising the programming instructions for:
A system, comprising:
Dependencies are inferred from the claim text.