Hewlett Packard Enterprise Development LP

David Strenski

Sreenivas Rangan Sukumar

Examples disclosed herein relate to selection of a set of nodes in a HPC system for running one or more computational jobs. In some examples, the selection of the set of nodes includes gathering information about a cluster of nodes in a high-performance computing system. The HPC system may be in a production state with one or more computational workloads getting executed thereon. In some examples, periodically sending one or more test-computing jobs for execution on each node to measure one or more performance metrics thereof. Receiving measured performance metrics from each node, in response to the one or more test-computing jobs executed thereon. Recording in a database, the measured performance metrics received from each node. Selecting the set of nodes from the cluster of nodes, based on the database, and based on a request received to nm one or more computational jobs on the HPC system.

Selecting nodes in a cluster of nodes for running computational jobs

Systems and methods are provided for implementing a machine learning (ML) model based compiler, language translator, and/or a decompiler. For example, the system may receive a first source code in a first programming language, tokenize the first source code file forming tokenized code, generate a sequence vector of tokenized code, and provide the sequence vector of tokenized code as input to a trained ML model compiler. The output of the trained ML model compiler may create a second executable file or the source code in a second programming language.

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Ypsilanti, MI, United States of America

David Strenski