Abstract: A smart, bi-directional electrical microgrid includes processor-on-demand systems, including a computing device having a processing unit and a memory, an Energy Management System (EMS) configured for regulating power usage and optimizing energy efficiency, a distributed power resource for providing a stable and efficient energy supply, a database configured to store energy metrics, a Large Language Model (LLM) for processing the energy metrics stored to generate an energy management plan, an API gateway providing external systems secure, on-demand access to the processing unit, and a software module for managing the processor-on-demand system according to the energy management plan. The microgrid also includes one or more management servers for managing the delivery and distribution of power among the processor-on-demand systems to optimize efficiency and uptime, and a network of power lines that interconnect the processor-on-demand systems.

Abstract: A smart, bi-directional electrical microgrid includes GPU-on-demand systems, including a computing device having a graphics processing unit (GPU) and a memory, an Energy Management System (EMS) configured for regulating power usage and optimizing energy efficiency, a distributed power resource for providing a stable and efficient energy supply, a database configured to store energy metrics, a Large Language Model (LLM) for processing the energy metrics stored to generate an energy management plan, an API gateway providing external systems secure, on-demand access to the GPU, and a software module for managing the GPU-on-demand system according to the energy management plan. The microgrid also includes one or more management servers for managing the delivery and distribution of power among the GPU-on-demand systems to optimize efficiency and uptime, and a network of power lines that interconnect the GPU-on-demand systems.

Abstract: A GPU-on-demand system includes a computing device equipped with a graphics processing unit (GPU) and memory, an Energy Management System (EMS) and a distributed power resource, a database for storing energy metrics including energy expenditure, a Large Language Model (LLM) for processing the energy metrics so as to generate an energy management plan that defines when each of the plurality of distributed power resources shall be used, an API gateway comprising an API coupled to a network connection, the API gateway configured for providing external systems secure, on-demand access to the GPU, and, a software module executing on the computing device, the software module configured for managing the GPU-on-demand system according to the energy management plan.