US 12,307,337 B2
Flexible control of machine learning model execution for real-time execution environments
Jonas Nordin, New York, NY (US)
Assigned to NASDAQ, INC., Rockville, MD (US)
Filed by Nasdaq, Inc., New York, NY (US)
Filed on Feb. 17, 2023, as Appl. No. 18/110,967.
Prior Publication US 2024/0281696 A1, Aug. 22, 2024
Int. Cl. G06N 20/00 (2019.01)
CPC G06N 20/00 (2019.01) 19 Claims
OG exemplary drawing
 
1. A system comprising:
a memory comprising a feature store, wherein the feature store comprises a plurality of predefined memory regions each of which is configured to store data of a respective data type of a plurality of data types; and
a processing system comprising at least one processor and being configured to perform operations comprising:
running a first process configured to receive data from a real-time transaction engine and to store the received data in the feature store in accordance with a data type of the received data;
running a second process configured to control execution of machine learning model based on a clock signal obtained from the feature store, wherein the machine learning model is configured to use data stored in one or more of the predefined memory regions of the feature store as input;
running a third process configured to receive result data generated by the machine learning model and to provide the result data to the real-time transaction engine,
wherein the first process is configured to extract data of a first set of data types from a core data stream received from the transaction processing engine and to write the extracted data of each data type of the first set of data types in respectively different first predefined memory regions of the plurality of memory regions; and
running a fourth process configured to extract data of a second set of data types from a from a second data stream and to write the extracted data of each data type of the second set of data types to respectively different second predefined memory regions of the plurality of memory regions.