IP Library › Granted Patent US 12,739,193
Granted Patent B2
US 12,739,193 · App. 19/227,465 · Granted Sep 15, 2026

Control plane proxy server for managing use of network connecting endpoint processing units

Inventors: Daniel P. Daly (Santa Barbara, CA); Edward V. E. Doe (Palo Alto, CA); Alain J. E. Gravel (Thousand Oaks, CA)
Assignee: DELOS DATA INC.
H04L45/24H04L67/10
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Quick Facts
Patent No.
US 12,739,193
App. No.
19/227,465
Granted
Sep 15, 2026
Kind
B2
Abstract

Some embodiments provide a method of managing communication between EPUs connected through a network having multiple forwarding elements. At a set of configuration servers, the method assigns, for each EPU, a CP proxy server to configure the network interface of the EPU to forward data messages through the network. The method distributes configuration data to CP proxy servers. Each particular CP proxy server (i) through one or more forwarding elements and from the network interface of each EPU assigned to the particular CP proxy server, receives requests for scheduling parameters for a data message flow that the network interface has to forward through the network, (ii) uses the received configuration data to generate the scheduling parameters for each EPU, and (iii) provides, through one or more forwarding elements, the generated scheduling parameters to the network interface of each EPU to use to forward the data message flow through the network.

Claims (24)

1 . A method of managing communication between endpoint processing units (EPUs) connected through a network comprising a plurality of forwarding elements, the method comprising:

at a set of one or more configuration servers:

assigning, for each EPU, one CP proxy server to configure a network interface of the EPU to forward data messages through the network; and

distributing configuration data to CP proxy servers, each particular CP proxy server (i) through one or more forwarding elements, receiving, from the network interface of each EPU assigned to the particular CP proxy server, requests for a set of scheduling parameters for a data message flow that the network interface has to forward through the network, (ii) using the distributed configuration data to generate the set of scheduling parameters for each EPU, and (iii) providing, through one or more forwarding elements, the generated set of scheduling parameters to the network interface of each EPU to use to forward the data message flow through the network.

2 . The method of claim 1 , wherein the EPUs are graphics processing units (GPUs).

3 . The method of claim 1 , wherein the EPUs comprise at least one of graphics processing units (GPUs), tensor processing units (TPUs) and central processing units (CPUs).

4 . The method of claim 1 , wherein for each request sent from a particular network interface, the particular CP proxy server receives the request from a forwarding element that is a last hop in a path from the particular network interface to a destination of the data message flow for which the particular network interface sends the request.

5 . The method of claim 4 , wherein the particular CP proxy server provides the generated set of scheduling parameters for each request to the forwarding element from which the particular CP proxy server receives the request, in order for the forwarding element to forward the generated set of scheduling parameters in a reply back to the particular network interface that sent the request.

6 . The method of claim 5 , wherein each request from each particular network interface and each reply back to the particular network interface is sent as an in-band control message through the forwarding elements that form the network connecting the EPUs.

7 . The method of claim 4 , wherein each forwarding element has a data plane circuit that (i) intercepts each request when the forwarding element is the last hop for that request and (ii) for said interception, has a policy-based rule to identify all requests addressed to a destination that is one hop away from the forwarding element to a CP proxy server to process as a control plane message.

8 . The method of claim 1 , wherein based on the distributed configuration data, each CP proxy server provides the set of scheduling parameters for a data message flow to each network interface.

9 . The method of claim 8 , wherein each set of scheduling parameters for each EPU network interface controls at least one of a launch time and rate for forwarding a data message flow storing a result computed by the EPU to the result's destinations in the network.

10 . The method of claim 8 , wherein each set of scheduling parameters is part of the distributed configuration data.

11 . The method of claim 8 , wherein each CP proxy server generates at least a subset of the scheduling parameters from the distributed configuration data.

12 . A non-transitory machine readable medium storing a program that when executed by at least one processor manages communication between graphics processing units (GPUs) connected through a network comprising a plurality of forwarding elements, the program comprising sets of instructions for:

assigning, for each GPU, one CP proxy server to configure a network interface of the GPU to forward data messages through the network; and

distributing configuration data to CP proxy servers, each particular CP proxy server (i) through one or more forwarding elements, receiving, from the network interface of each GPU assigned to the particular CP proxy server, requests for a set of scheduling parameters for a data message flow that the network interface has to forward through the network, (ii) using the distributed configuration data to generate the set of scheduling parameters for each GPU, and (iii) providing, through one or more forwarding elements, the generated set of scheduling parameters to the network interface of each GPU to use to forward the data message flow through the network.

13 . The non-transitory machine readable medium of claim 12 , wherein for each request sent from a particular network interface, the particular CP proxy server receives the request from a forwarding element that is a last hop in a path from the particular network interface to a destination of the data message flow for which the particular network interface sends the request.

14 . The non-transitory machine readable medium of claim 13 , wherein the particular CP proxy server provides the generated set of scheduling parameters for each request to the forwarding element from which the particular CP proxy server receives the request, in order for the forwarding element to forward the generated set of scheduling parameters in a reply back to the particular network interface that sent the request.

15 . The non-transitory machine readable medium of claim 14 , wherein each request from each particular network interface and each reply back to the particular network interface is sent as an in-band control message through the forwarding elements that form the network connecting the GPUs.

16 . The non-transitory machine readable medium of claim 13 , wherein each forwarding element has a data plane circuit that (i) intercepts each request when the forwarding element is the last hop for that request and (ii) for said interception, has a policy-based rule to identify all requests addressed to a destination that is one hop away from the forwarding element to a CP proxy server to process as a control plane message.

17 . The non-transitory machine readable medium of claim 12 , wherein based on the distributed configuration data, each CP proxy server provides the set of scheduling parameters for a data message flow to each network interface.

18 . The non-transitory machine readable medium of claim 17 , wherein each set of scheduling parameters for each GPU network interface controls at least one of a launch time and rate for forwarding a data message flow storing a result computed by the GPU to the result's destinations in the network.

19 . The non-transitory machine readable medium of claim 17 , wherein each set of scheduling parameters is part of the distributed configuration data.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 13, 2025
From: DALY, DANIEL P.; DOE, EDWARD V. E.; GRAVEL, ALAIN J. E.
To: DELOS DATA INC.
Reel/Frame 072012/0191 →
Continuity (6)
Provisional Application 63777883 · Mar 26, 2025
Provisional Application 63714118 · Oct 30, 2024
Provisional Application 63707702 · Oct 15, 2024
Provisional Application 63698036 · Sep 23, 2024
Provisional Application 63697485 · Sep 21, 2024
Related Publication 20260089234A1 · Mar 26, 2026
References Cited (92)
US 6101549A · Baugher et al. · 2000 [cited by applicant]
US 7627744B2 · Maher et al. · 2009 [cited by applicant]
US 8738684B1 · Ellis · 2014 [cited by applicant]
US 8743888B2 · Casado et al. · 2014 [cited by applicant]
US 8743889B2 · Koponen et al. · 2014 [cited by applicant]
US 8817620B2 · Koponen et al. · 2014 [cited by applicant]
US 8966035B2 · Casado et al. · 2015 [cited by applicant]
US 9083609B2 · Casado et al. · 2015 [cited by applicant]
US 10200235B2 · Pfaff et al. · 2019 [cited by applicant]
US 10275851B1 · Zhao et al. · 2019 [cited by applicant]
US 10382401B1 · Lee et al. · 2019 [cited by applicant]
US 10728091B2 · Zhao et al. · 2020 [cited by applicant]
US 11080225B2 · Borikar et al. · 2021 [cited by applicant]
US 11477114B2 · Hu · 2022 [cited by applicant]
US 12603829B2 · Clark · 2026 [cited by applicant]
US 20010034771A1 · Hutsch et al. · 2001 [cited by applicant]
US 20020110119A1 · Fredette et al. · 2002 [cited by applicant]
US 20040105440A1 · Strachan et al. · 2004 [cited by applicant]
US 20080059602A1 · Matsuda et al. · 2008 [cited by applicant]
US 20120131252A1 · Rau · 2012 [cited by applicant]
US 20130329549A1 · Kusama et al. · 2013 [cited by applicant]
US 20140269379A1 · Holbrook et al. · 2014 [cited by applicant]
US 20150319009A1 · Zhao · 2015 [cited by applicant]
US 20160124852A1 · Shachar et al. · 2016 [cited by applicant]
US 20170351555A1 · Coffin · 2017 [cited by applicant]
US 20180322387A1 · Sridharan et al. · 2018 [cited by applicant]
US 20190109789A1 · Friedman et al. · 2019 [cited by applicant]
US 20190123894A1 · Yuan · 2019 [cited by applicant]
US 20190132150A1 · Ramachandran et al. · 2019 [cited by applicant]
US 20190158371A1 · Dillon et al. · 2019 [cited by applicant]
US 20190182143A1 · Kim et al. · 2019 [cited by applicant]
US 20190182149A1 · Kim et al. · 2019 [cited by applicant]
US 20200177629A1 · Hooda et al. · 2020 [cited by applicant]
US 20200302568A1 · Li et al. · 2020 [cited by applicant]
US 20210191774A1 · Kanteti et al. · 2021 [cited by applicant]
US 20210219175A1 · Xu et al. · 2021 [cited by applicant]
US 20210318878A1 · Zhao et al. · 2021 [cited by applicant]
US 20210328902A1 · Huselton et al. · 2021 [cited by applicant]
US 20210334234A1 · Yudanov · 2021 [cited by applicant]
US 20220085916A1 · Debbage et al. · 2022 [cited by applicant]
US 20220086096A1 · Sugiyama et al. · 2022 [cited by applicant]
US 20220188688A1 · Launay et al. · 2022 [cited by applicant]
US 20220351326A1 · Rimmer et al. · 2022 [cited by applicant]
US 20220361262A1 · Liu et al. · 2022 [cited by applicant]
US 20230034757A1 · Wu · 2023 [cited by examiner]
US 20230064808A1 · Thubert · 2023 [cited by examiner]
US 20230214345A1 · Taylor · 2023 [cited by applicant]
US 20230297292A1 · Potyraj et al. · 2023 [cited by applicant]
US 20230325265A1 · Balle et al. · 2023 [cited by applicant]
US 20230327988A1 · Rennie et al. · 2023 [cited by applicant]
US 20240061796A1 · Dastidar et al. · 2024 [cited by applicant]
US 20240069978A1 · Singh et al. · 2024 [cited by applicant]
US 20240086258A1 · Lal et al. · 2024 [cited by applicant]
US 20240098033A1 · Hong et al. · 2024 [cited by applicant]
US 20240129234A1 · Farrokhbakht et al. · 2024 [cited by applicant]
US 20240152409A1 · Brar et al. · 2024 [cited by applicant]
US 20240220336A1 · Punniyamurthy et al. · 2024 [cited by applicant]
US 20240256475A1 · Chen et al. · 2024 [cited by applicant]
US 20240406093A1 · Chuang · 2024 [cited by examiner]
US 20250126071A1 · Brar et al. · 2025 [cited by applicant]
US 20250274380A1 · Barkai et al. · 2025 [cited by applicant]
US 20250291760A1 · Ensey et al. · 2025 [cited by applicant]
US 20250292355A1 · Heinecke et al. · 2025 [cited by applicant]
US 20250321795A1 · Narayanaswamy et al. · 2025 [cited by applicant]
US 20260046317A1 · Crabtree et al. · 2026 [cited by applicant]
US 20260052100A1 · Holl et al. · 2026 [cited by applicant]
US 20260058900A1 · Kommula et al. · 2026 [cited by applicant]
CN 117157953A · 2023 [cited by applicant]
CN 118503194A · 2024 [cited by applicant]
HU E033041T2 · 2017 [cited by applicant]
Author Unknown, “Source Routing,” Wikipedia, Sep. 5, 2024, 3 pages, Wikipedia.com. [cited by applicant]
Bosshart, Pat, et al., “P4: Programming Protocol-Independent Packet Processors,” ACM SIGCOMM Computer Communication Review, vol. 44, No. 3, Jul. 2014, pp. 88-95. [cited by applicant]
Cai, Zheng, et al., “The Preliminary Design and Implementation of the Maestro Network Control Platform,” Oct. 1, 2008, 17 pages, NSF. [cited by applicant]
Casado, Martin, et al. “Ethane: Taking Control of the Enterprise,” SIGCOMM'07, Aug. 27-31, 2007, 12 pages, ACM, Kyoto, Japan. [cited by applicant]
Casado, Martin, et al., “Rethinking Packet Forwarding Hardware,” Seventh ACM SIGCOMM' HotNets Workshop, Nov. 2008, 6 pages, ACM. [cited by applicant]
Casado, Martin, et al., “SANE: A Protection Architecture for Enterprise Networks,” Proceedings of the 15th USENIX Security Symposium, Jul. 31-Aug. 4, 2006, 15 pages, USENIX, Vancouver, Canada. [cited by applicant]
Casado, Martin, et al., “Scaling Out: Network Virtualization Revisited,” Month Unknown 2010, 8 pages. [cited by applicant]
Casado, Martin, et al., “Virtualizing the Network Forwarding Plane,” Dec. 2010, 6 pages. [cited by applicant]
Das, Saurav, et al., “Unifying Packet and Circuit Switched Networks with OpenFlow,” Dec. 7, 2009, 10 pages, available at https://yuba.stanford.edu/~nickm/papers/UArch_Cam_Rdy.pdf. [cited by applicant]
Filsfils, Clarence, et al., “SRv6”, Dec. 5, 2017, Cisco, available at https://www.segment-routing.net/tutorials/2017-12-05-srv6-introduction. [cited by applicant]
Greenberg, Albert, et al., “VL2: A Scalable and Flexible Data Center Network,” SIGCOMM '09, Aug. 17-21, 2009, 12 pages, ACM, Barcelona, Spain. [cited by applicant]
Gude, Natasha, et al., “NOX: Towards an Operating System for Networks,” Acm Sigcomm Computer Communication Review, Jul. 2008, 6 pages, Vo. 38, No. 3, ACM. [cited by applicant]
Guo, Chanxiong, et al., “BCube: A High Performance, Server-centric Network Architecture for Modular Data Centers,” SIGCOMM'09, Aug. 17-21, 2009, 12 pages, ACM, Barcelona, Spain. [cited by applicant]
Kim, Changhoon, et al., “Floodless in Seattle: A Scalable Ethernet Architecture for Large Enterprises,” SIGCOMM'08, Aug. 17-22, 2008, 12 pages, ACM, Seattle, Washington, USA. [cited by applicant]
Koponen, Teemu, et al., “Onix: A Distributed Control Platform for Large-scale Production Networks,” In Proc. OSDI, Oct. 2010, 14 pages. [cited by applicant]
PCT International Search Report and Written Opinion of Commonly Owned International Patent Application PCT/US2025/047269, mailing date Nov. 25, 2025, 17 pages, International Searching Authority (US). [cited by applicant]
Sherwood, Rob, et al., “FlowVisor: A Network Virtualization Layer,” Oct. 14, 2009, 15 pages, Openflow-TR-2009-1. [cited by applicant]
Tavakoli, Arsalan, et al., “Applying NOX to the Datacenter,” Proc. HotNets, Month Unknown 2009, 6 pages. [cited by applicant]
Yang, L., et al., “Forwarding and Control Element Separation (ForCES) Framework,” Apr. 2004, 41 pages, The Internet Society. [cited by applicant]
Yu, Minlan, et al., “Scalable Flow-Based Networking with DIFANE,” In Proc. SIGCOMM, Aug. 2010, 16 pages. [cited by applicant]
Asterfuison, “AOC, DAC, ACC, AEC Modules: The most Complete Overview”, May 20, 2024, Asterfusion Data Technologies, Co., Ltd., Shenzhen, China, 17 pages. [cited by applicant]
Lebeane, Michael, et al., “GPU Triggered Networking for Intra-Kernel Communications,” The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC '17), Nov. 12-17, 2017, Denver, Co… [cited by applicant]