Neural network-based method and system for generating optimized execution plans for ai workloads in hybrid and multi-cloud environments

A neural network-based method of generating an optimized execution plan for an AI workload in hybrid and multi-cloud environments, the method comprising:

• receiving, from a user terminal, user AI workload definition information and user optimization requirement specification information;
• sampling information on different cloud environments and different network paths to generate a plurality of sample group data comprising the different cloud environments and the different network paths;
• inputting each of the plurality of sample group data into a neural network to receive a plurality of predicted values for the plurality of sample group data from the neural network;
• and
• specifying an optimal predicted value that satisfies the user AI workload definition information and the user optimization requirement specification information using optimal prediction calculation,
• wherein the plurality of sample group data further includes the user AI workload definition information, and
• wherein the generating of the plurality of sample group data comprises:
• combining, based on the user AI workload definition information, each of the sampled different cloud environment information and the different network path information with the user AI workload definition information to generate the plurality of sample group data,
• the method further comprising:
• converting each of the plurality of sample group data into a plurality of intermediate representation data based on a preset format;
• and
• inputting each of the plurality of intermediate representation data into the neural network,
• wherein the neural network performs prediction for each of the plurality of intermediate representation data and outputs the plurality of predicted values for each of the plurality of intermediate representation data, and
• wherein the plurality of predicted values includes time and price required to execute the user AI workload definition information in the different cloud environment information and the different network path information.