US 12,118,616 B2
Method and system for controlling hardware performance for high frequency trading
Hyunsung Kim, Seongnam-si (KR); Sungyeob Yoo, Seongnam-si (KR); and Jinwook Oh, Seongnam-si (KR)
Assigned to Rebellions Inc., Seongnam-si (KR)
Filed by REBELLIONS INC., Seongnam-si (KR)
Filed on Oct. 25, 2023, as Appl. No. 18/494,703.
Application 18/494,703 is a continuation of application No. 18/184,534, filed on Mar. 15, 2023, granted, now 11,836,800.
Claims priority of application No. 10-2022-0043474 (KR), filed on Apr. 7, 2022; and application No. 10-2023-0000451 (KR), filed on Jan. 2, 2023.
Prior Publication US 2024/0054562 A1, Feb. 15, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 40/04 (2012.01)
CPC G06Q 40/04 (2013.01) 12 Claims
OG exemplary drawing
 
1. A system for adjusting a hardware performance for high frequency trading comprising:
a memory; and
one or more processors connected to the memory and configured to execute one or more computer-readable programs included in the memory,
wherein the one or more programs include instructions for:
acquiring, by the one or more processors, a plurality of input data items for high frequency trading;
determining, by the one or more processors, a workload for an inference computation of a machine learning model 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;
supplying, by the one or more processors, the one or more determined resources to the hardware using one or more supply lines formed between the one or more determined resources and the hardware;
selecting, by the one or more processors, at least one input data item from among the plurality of input data based on the determined workload; and
applying, by the one or more processors, the selected at least one input data item to the machine learning model.