US 12,236,323 B1
Network switch with integrated gradient aggregation for distributed machine learning
William Brad Matthews, Los Gatos, CA (US); and Puneet Agarwal, Santa Clara, CA (US)
Assigned to Innovium, Inc., Santa Clara, CA (US)
Filed by Innovium, Inc., Santa Clara, CA (US)
Filed on Jun. 30, 2023, as Appl. No. 18/217,483.
Application 18/217,483 is a continuation of application No. 17/741,371, filed on May 10, 2022, granted, now 11,715,040.
Application 17/741,371 is a continuation of application No. 16/409,703, filed on May 10, 2019, granted, now 11,328,222, issued on May 10, 2022.
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 20/00 (2019.01); H04L 47/2441 (2022.01); H04L 47/32 (2022.01); H04L 49/00 (2022.01); H04L 67/10 (2022.01); H04L 49/25 (2022.01)
CPC G06N 20/00 (2019.01) [H04L 47/2441 (2013.01); H04L 47/32 (2013.01); H04L 49/3027 (2013.01); H04L 67/10 (2013.01); H04L 49/252 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A network switching apparatus, comprising:
a plurality of communication interfaces configured to connect to specific computing devices in a network, including compute devices of a distributed learning system;
packet-switching logic configured to receive data units via the communication interfaces;
machine learning logic configured to:
determine, in the data units, particular data units containing data from a machine learning model being trained against a training data set;
based on information contained in the particular data units:
identify one or more actions to be performed on the data in the particular data units;
perform the one or more actions on the data in the particular data units;
aggregate results from the one or more actions; and
return the aggregated results to one or more of the compute devices.