Method and system for controlling hardware performance for high frequency trading

A method for adjusting a performance of hardware for high frequency trading, the method being performed by one or more processors and comprising:

• receiving, by the one or more processors, context information including at least one of a traffic of market data for one or more target items or a computational complexity of using a machine learning model performed based on the market data;
• determining, by the one or more processors, a workload for an inference computation of the machine learning model with at least one target item based on time allowed until a task is completed and available resources of the hardware, wherein the determining the workload includes determining one or more resources of the hardware for processing the workload;
• determining, by the one or more processors, whether or not to change a processing performance of the hardware based on the received context information and the determined workload;
• changing, by the one or more processors, one or more resources to be supplied to the hardware based on the determination result for changing the processing performance;
• supplying, by the one or more processors, the one or more changed resources to the hardware using supply lines formed between the one or more changed resources and the hardware;
• and
• performing, by using the hardware to which the one or more changed resources are supplied, the machine learning model based on the market data.