US 12,468,701 B2
Method and system for query processing over tensor runtimes
Matteo Interlandi, Torrance, CA (US); Konstantinos Karanasos, San Francisco, CA (US); Dong He, Seattle, WA (US); Dalitso Hansini Banda, Mountain View, CA (US); Jesus Camacho Rodriguez, Sunnyvale, CA (US); Rathijit Sen, Madison, WI (US); and Supun Chathurang Nakandala, San Diego, CA (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Jan. 28, 2022, as Appl. No. 17/587,952.
Prior Publication US 2023/0244662 A1, Aug. 3, 2023
Int. Cl. G06F 16/2453 (2019.01); G06F 16/2458 (2019.01); G06N 3/04 (2023.01)
CPC G06F 16/24542 (2019.01) [G06F 16/2458 (2019.01); G06N 3/04 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving a query including one or more query operators;
determining a query representation based on the one or more query operators;
generating, based on the query representation, a neural network program for executing in a neural network runtime at least in part by representing one or more of the query operators, for which a corresponding operator is not provided by the neural network runtime, as one or more neural network operators for performing the query in a neural network runtime, wherein the neural network runtime provides an executable environment to at least one of train neural network models during a training mode or evaluate the neural network models in a non-training mode;
generating a neural network data structure based on a dataset associated with the query; and
executing the query by executing the neural network program, including the one or more neural network operators, in the neural network runtime over the neural network data structure to generate a query result.