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AssigneeNEC Laboratories Europe GmbH
InventorsNicolas Weber, Roberto Bifulco, Marc Betzwieser, Yves Ekspenszid
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A computer-implemented, machine learning method for preprocessing code for performance portability includes extracting performance critical code segments from an application and obtaining input data. Ground truth data is generated based on the input data and the application. Original code of the application is transpiled using a large language model (LLM) into a tensor computation language (TCL) candidate. Correctness of an implementation of the TCL candidate is verified using the ground truth data. The method has applications including, but not limited to, use cases in medicine/healthcare, and other artificial intelligence applications for preprocessing and optimizing code for performance portability.
A computer-implemented method for preprocessing code for performance portability, the computer-implemented method comprising:
A computer system for preprocessing code for performance portability, the computer system comprising one or more hardware processors which, alone or in combination, are configured to provide for execution of the following steps:
A tangible, non-transitory computer-readable medium having instructions thereon which, upon being executed by one or more processors, provide for preprocessing code for performance portability by execution of the following steps:
Dependencies are inferred from the claim text.