DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4/18/2025; 6/17/2025; 7/31/2025; 10/16/2025 and 12/17/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
This application claims priority to Greek Patent Application No. 20240100894, filed on December 18, 2024, which is (i) a Continuation-in-Part of U.S. Application No. 18/427,046, filed on January 30, 2024, which claims priority to Greek Patent Application No. 20240100049, filed on January 25, 2024, and (ii) a Continuation-in-Part of U.S. Application No. 18/427,269, filed on January 30, 2024, which claims priority to Greek Patent Application No. 20240100053, filed on January 25, 2024.
The earlies priority date is 1/30/2024. However, some of the features recited in the claims are not include in the Greek Patent Application, for example the claimed “the data distribution task is associated with an artificial intelligent (AI) workload and “the transmission facilitates processing of the AI workload across the plurality of hosts.” These features do not have the above indicated priority. The earliest priority date the features can claim is the filing date of the pending application which is 10 January 2025.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 2, 11 and 12 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 16 and 17 of co-pending Application No. 18/427,046 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because each of the limitations of claims 1, 2, 16 and 17 of co-pending Application No. 18/427,046 reads on each of the limitations of claims 1, 2, 11 and 12 of the pending application, respectively. The rejection is presented in the table below.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Pending Application 19/016,091
Co-pending Application 18/427,046
1. A method for allocation of network resources, the method comprising:
receiving, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the data distribution task is associated with an artificial intelligence (AI) workload, wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determining a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k);
operatively coupling the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload;
identifying, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k); and
executing the data distribution task by transmitting respective portions of the plurality of data portions to from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs, wherein the transmission facilitates processing of the Al workload across the plurality of hosts.
1. (Currently Amended) A method, the method comprising:
receiving, from a user input device, a data distribution task and parameters associated with the data distribution task,
wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determining a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs is associated with a plurality of switches, wherein each switch is associated with a radix (k);
operatively coupling the plurality of switches to the plurality of hosts to configure a network structure;
identifying, from the plurality of hosts, at least one destination host for each source host based on at least a number of communication hops, wherein the number of communication hops is determined based on a corresponding subset of the plurality of switches associated with traversal of data from each source host to the at least one destination; and
executing, in a sequence of data distribution stages, the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host simultaneously via the corresponding subset of the plurality of switches,
wherein, at each data distribution stage, the at least one destination host for each source host is identified based on at least a local offset derived from a cyclic rotation among hosts under each switch.
2. The method of Claim 1, wherein executing the data distribution task comprises transmitting the plurality of data portions according to an all-to-all communication pattern.
2. The method of Claim 1, wherein executing the data distribution task comprises transmitting the plurality of data portions according to an all-to-all communication pattern.
3. The method of Claim 1, wherein configuring the network structure comprises arranging the plurality of PODs and the plurality of hosts in a mesh topology to facilitate data transmission.
4. The method of Claim 1, wherein executing the data distribution task comprises:
determining a required number of data distribution stages for execution of the data distribution task based on at least an aggregate count of the plurality of hosts; and
transmitting the plurality of data portions in a sequence of data distribution stages based on the required number of data distribution stages.
5. The method of Claim 4, wherein for each data distribution stage (s), the method comprises:
identifying a destination host (j) for each source host (i) based on at least a distribution of hosts (Hz) within each POD, and the radix (k) of each switch; and
transmitting a first data portion from the source host (i) to the identified destination host (j) via the corresponding subset of the plurality of PODs using a bandwidth, B, of corresponding communication links.
6. The method of Claim 5, wherein the destination host is identified based on:
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7. The method of Claim 5, wherein, for each data distribution stage (s), a number of destination hosts for each source host (i) is determined based on a window size, W, and wherein the number of destination hosts for each source host (i) is equal to the window size, W.
8. The method of Claim 7, wherein for window size, W>1, executing the data distribution task comprises executing the data distribution task in a clustered grouping of data distribution stages, wherein a size of the clustered grouping is based on at least the window size, W.
9. The method of Claim 4, wherein executing the data distribution task in the sequence of data distribution stages further comprises:
iteratively determining the destination host (j) for each source host (i) at each data distribution stage (s) for the required number of data distribution stages; and
at each iteration, transmitting data portions from the plurality of data portions from the source host (i) to the determined destination host (j).
10. The method of Claim 1, wherein the method comprises:
determining that an allocation of the subset of the plurality of hosts under each POD is asymmetric;
integrating a plurality of virtual hosts in the network structure to balance the asymmetric distribution of the subset of the plurality of hosts under each POD to create a symmetric distribution; and
executing the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host via the corresponding subset of PODs, wherein the at least one identified destination host comprises at least one of the plurality of hosts and the plurality of virtual hosts.
11. A system for allocation of network resources, the system comprising:
a processing device; and
a non-transitory storage device containing instructions that, when executed by the processing device, cause the processing device to:
receive, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the data distribution task is associated with an artificial intelligence (Al) workload, wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determine a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k);
operatively couple the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload;
identify, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k); and
execute the data distribution task by transmitting respective portions of the plurality of data portions to from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs, wherein the transmission facilitates processing of the Al workload across the plurality of hosts.
16. A system, the system comprising:
a processing device; and
a non-transitory storage device containing instructions that, when executed by the processing device, cause the processing device to:
receive, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determine a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs is associated with a plurality of switches, wherein each switch is associated with a radix (k);
operatively couple the plurality of switches to the plurality of hosts to configure a network structure;
identify, from the plurality of hosts, at least one destination host for each source host based on at least a number of communication hops, wherein the number of communication hops is determined based on a corresponding subset of the plurality of switches associated with traversal of data from each source host to the at least one destination; and
execute, in a sequence of data distribution stages, the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host simultaneously via the corresponding subset of the plurality of switches, wherein, at each data distribution stage, the at least one destination host for each source host is identified based on at least a local offset derived from a cyclic rotation among hosts under each switch.
12. The system of Claim 11, wherein, in executing the data distribution task, the instructions, when executed, cause the processing device to transmit the plurality of data portions according to an all-to-all communication pattern.
17.The system of Claim 16, wherein the instructions, when executed, cause the processing device to execute the data distribution task by transmitting the plurality of data portions according to an all-to-all communication pattern.
13. The system of Claim 11, wherein, in configuring the network structure, the instructions, when executed, cause the processing device to arrange the plurality of PODs and the plurality of hosts in a mesh topology to facilitate data transmission.
14. The system of Claim 11, wherein, in executing the data distribution task, the instructions when executed, cause the processing device to:
determine a required number of data distribution stages for execution of the data distribution task based on at least an aggregate count of the plurality of hosts; and
transmit the plurality of data portions in a sequence of data distribution stages based on the required number of data distribution stages.
15. The system of Claim 14, wherein for each data distribution stage (s), the instructions, when executed, cause the processing device to:
identifying a destination host (j) for each source host (i) based on at least a distribution of hosts (Hz) within each POD, and the radix (k) of each switch; and
transmitting a first data portion from the source host (i) to the identified destination host (j) via the corresponding subset of the plurality of PODs using a bandwidth, B, of corresponding communication links.
19. The system of Claim 18, wherein for each data distribution stage (s), the instructions, when executed, cause the processing device to:
identify the at least one destination host (j) for each source host (i) such that the number of communication hops required for traversal of data from each source host (i) to the at least one identified destination host (j) via the corresponding subset of the plurality of switches is equal; and
transmit a predetermined data portion from the source host (i) to the at least one identified destination host (j) via the corresponding subset of the plurality of switches.
16. The system of Claim 15, wherein the instructions, when executed, cause the processing device to identify the destination host based on:
17. A computer program product for allocation of network resources, the computer program product comprising a non-transitory computer-readable medium comprising code configured to cause an apparatus to:
receive, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the data distribution task is associated with an artificial intelligence (Al) workload, wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determine a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k);
operatively couple the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload;
identify, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k); and
execute the data distribution task by transmitting respective portions of the plurality of data portions to from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs, wherein the transmission facilitates processing of the Al workload across the plurality of hosts.
17. A computer program product, the computer program product comprising a non-transitory computer-readable medium comprising code configured to cause an apparatus to:
receive, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determine a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs is associated with a plurality of switches, wherein each switch is associated with a radix (k);
operatively couple the plurality of switches to the plurality of hosts to configure a network structure;
identify, from the plurality of hosts, at least one destination host for each source host based on at least a number of communication hops, wherein the number of communication hops is determined based on a corresponding subset of the plurality of switches associated with traversal of data from each source host to the at least one destination; and
execute, in a sequence of data distribution stages, the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host simultaneously via the corresponding subset of the plurality of switches, wherein, at each data distribution stage, the at least one destination host for each source host is identified based on at least a local offset derived from a cyclic rotation among hosts under each switch.
18. The computer program product of Claim 17, wherein, in executing the data distribution task, the code is further configured to cause the apparatus to:
transmit the plurality of data portions according to an all-to-all communication pattern.
19. The computer program product of Claim 17, wherein, in configuring the network structure, the code is further configured to cause the apparatus to:
arrange the plurality of PODs and the plurality of hosts in a mesh topology to facilitate data transmission.
20. The computer program product of Claim 17, wherein, in executing the data distribution task, the code is further configured to cause the apparatus to:
determine a required number of data distribution stages for execution of the data distribution task based on at least an aggregate count of the plurality of hosts; and
transmit the plurality of data portions in a sequence of data distribution stages based on the required number of data distribution stages.
Claims 1, 4, 5, 6, 7, 9, 10, 11, 12 and 14 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 4, 5, 6, 7-8, 12, 13, 16, 18 and 19 of prior U.S. Patent No. 12,566,491. Although the claims at issue are not identical, they are not patentably distinct from each other because of the listing of claim limitations in the table below.
Pending Application 19/016,091
US Patent Number 12,556,491
A method for allocation of network resources, the method comprising:
receiving, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the data distribution task is associated with an artificial intelligence (AI) workload, wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determining a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k);
operatively coupling the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload;
identifying, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k); and
executing the data distribution task by transmitting respective portions of the plurality of data portions to from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs, wherein the transmission facilitates processing of the Al workload across the plurality of hosts.
1. A method for allocation of network resources, the method comprising:
receiving, from a user input device, a data distribution task and parameters associated with the data distribution task,
wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determining a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k), wherein the radix (k) is indicative of a connectivity capacity of the switch;
operatively coupling the plurality of PODs to the plurality of hosts to configure a network structure;
identifying, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k); and
executing the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs.
4. The method of Claim 1, wherein executing the data distribution task comprises:
determining a required number of data distribution stages for execution of the data distribution task based on at least an aggregate count of the plurality of hosts; and
transmitting the plurality of data portions in a sequence of data distribution stages based on the required number of data distribution stages.
The method of claim 1, wherein executing the data distribution task comprises:
determining a required number of data distribution stages for execution of the data distribution task based on at least an aggregate count of the plurality of hosts; and
transmitting the plurality of data portions in a sequence of data distribution stages based on the required number of data distribution stages.
5. The method of Claim 4, wherein for each data distribution stage (s), the method comprises:
identifying a destination host (j) for each source host (i) based on at least a distribution of hosts (Hz) within each POD, and the radix (k) of each switch; and
transmitting a first data portion from the source host (i) to the identified destination host (j) via the corresponding subset of the plurality of PODs using a bandwidth, B, of corresponding communication links.
5. The method of claim 4, wherein for each data distribution stage(s), the method comprises:
identifying a destination host (j) for each source host (i) based on at least a distribution of hosts (Hz) within each POD, and the radix (k) of each switch; and
transmitting a first data portion from the source host (i) to the identified destination host (j) via the corresponding subset of the plurality of PODs using a bandwidth, B, of corresponding communication links.
6. The method of Claim 5, wherein the destination host is identified based on:
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6. The method of claim 5, wherein the destination host is identified based on
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wherein/represents a destination host index,
wherein i represents a source host index,
wherein s represents a data distribution stage index, wherein Hx represents a host count for a POD, x, wherein j, i, s, H, and x are non-negative integers, and wherein j, i, s, H, and x are obtained from stored data structures.
7. The method of Claim 5, wherein, for each data distribution stage (s), a number of destination hosts for each source host (i) is determined based on a window size, W, and wherein the number of destination hosts for each source host (i) is equal to the window size, W.
7. The method of claim 5, wherein, for each data distribution stage(s), a number of destination hosts for each source host (i) is determined based on a window size, W.
8. The method of claim 7, wherein the number of destination hosts for each source host (i) is equal to the window size, W.
9. The method of Claim 4, wherein executing the data distribution task in the sequence of data distribution stages further comprises:
iteratively determining the destination host (j) for each source host (i) at each data distribution stage (s) for the required number of data distribution stages; and
at each iteration, transmitting data portions from the plurality of data portions from the source host (i) to the determined destination host (j).
12. The method of claim 4, wherein executing the data distribution task in the sequence of data distribution stages further comprises:
iteratively determining the destination host (j) for each source host (i) at each data distribution stage(s) for the required number of data distribution stages; and
at each iteration, transmitting data portions from the plurality of data portions from the source host (i) to the determined destination host (j).
10. The method of Claim 1, wherein the method comprises:
determining that an allocation of the subset of the plurality of hosts under each POD is asymmetric;
integrating a plurality of virtual hosts in the network structure to balance the asymmetric distribution of the subset of the plurality of hosts under each POD to create a symmetric distribution; and
executing the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host via the corresponding subset of PODs, wherein the at least one identified destination host comprises at least one of the plurality of hosts and the plurality of virtual hosts.
13. The method of claim 1, wherein the method comprises:
determining that an allocation of the subset of the plurality of hosts under each POD is asymmetric;
integrating a plurality of virtual hosts in the network structure to balance the asymmetric distribution of the subset of the plurality of hosts under each POD to create a symmetric distribution; and
executing the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host via the corresponding subset of PODs, wherein the at least one identified destination host comprises at least one of the plurality of hosts and the plurality of virtual hosts.
11. A system for allocation of network resources, the system comprising:
a processing device; and
a non-transitory storage device containing instructions that, when executed by the processing device, cause the processing device to:
receive, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the data distribution task is associated with an artificial intelligence (Al) workload, wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determine a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k);
operatively couple the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload;
identify, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k); and
execute the data distribution task by transmitting respective portions of the plurality of data portions to from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs, wherein the transmission facilitates processing of the Al workload across the plurality of hosts.
16. A system for allocation of network resources, the system comprising:
a processing device; and
a non-transitory storage device containing instructions that, when executed by the processing device, cause the processing device to:
receive, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determine a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k), wherein the radix (k) is indicative of a connectivity capacity of the switch;
operatively couple the plurality of PODs to the plurality of hosts to configure a network structure;
identify, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k); and
execute the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs.
12. The system of Claim 11, wherein, in executing the data distribution task, the instructions, when executed, cause the processing device to transmit the plurality of data portions according to an all-to-all communication pattern.
18. The system of claim 16, wherein the instructions, when executed, cause the processing device to execute the data distribution task by transmitting the plurality of data portions according to an all-to-all communication pattern.
14. The system of Claim 11, wherein, in executing the data distribution task, the instructions when executed, cause the processing device to:
determine a required number of data distribution stages for execution of the data distribution task based on at least an aggregate count of the plurality of hosts; and
transmit the plurality of data portions in a sequence of data distribution stages based on the required number of data distribution stages.
19. The system of claim 16, wherein the instructions, when executed, cause the processing device to execute the data distribution task by:
determining a required number of data distribution stages for execution of the data distribution task based on at least an aggregate count of the plurality of hosts; and
transmitting the plurality of data portions in a sequence of data distribution stages based on the required number of data distribution stages.
17. A computer program product for allocation of network resources, the computer program product comprising a non-transitory computer-readable medium comprising code configured to cause an apparatus to:
receive, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the data distribution task is associated with an artificial intelligence (Al) workload, wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determine a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k);
operatively couple the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload;
identify, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k); and
execute the data distribution task by transmitting respective portions of the plurality of data portions to from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs, wherein the transmission facilitates processing of the Al workload across the plurality of hosts.
24. A computer program product for allocation of network resources, the computer program product comprising a non-transitory computer-readable medium comprising code configured to cause an apparatus to:
receive, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the parameters comprise a plurality of data portions and a plurality of hosts;
determine a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k), wherein the radix (k) is indicative of a connectivity capacity of the switch;
operatively couple the plurality of PODs to the plurality of hosts to configure a network structure;
identify, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k); and
execute the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs.
Claims 1, 4, 5, 6, 7, 9,10, 11, 12, 14 and 17 are provisionally rejected on the ground of nonstatutory –obviousness-type double patenting as being unpatentable over claims 1, 4, 5, 6, 7-8, 12, 13, 16, 18, 19 and 25 of U.S. Patent No. 12,556,491, hereinafter ‘491 in view of Lokesh et al. (US 2025/0363224), hereinafter Lokesh.
As for claim 1, ‘491 teaches a method for allocation of network resources (claim 1, preamble), the method comprising:
receiving, from a user input device, a data distribution task and parameters associated with the data distribution task (claim 1, 1st stanza), wherein the parameters comprise a plurality of data portions and a plurality of hosts (claim 1, 1st stanza);
determining a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k) (claim 1, 2nd stanza);
operatively coupling the plurality of PODs to the plurality of hosts (claim 1, 3rd stanza);
identifying, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k) (claim 1, 4th stanza); and
executing the data distribution task by transmitting respective portions of the plurality of data portions to from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs (claim 1, 5th stanza).
‘491 fails to teach
wherein the data distribution task is associated with an artificial intelligence (AI) workload,
wherein a coupling the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload.
Lokesh discloses
wherein the transmission facilitates processing of the Al workload across the plurality of hosts (paragraphs [0024]-[0026] describe a distributed system comprising a number of clients, any number of infrastructure nodes (IN), the system fortifies user security by applying machine learning (ML) functionality of a microservice; paragraphs [0043]-[0044] describe the clients cooperate with the IN by issuing requests to the IN to receive responses and interact with various components of the ID. The clients transmit information to the IN that allows the IN to perform computations; paragraphs [0064] and [0101]-[0111] describe the IN and their components (e.g. the engine, the analyzer and the visualizer) utilize ML model to analyze, annotate data included in dataset (from the clients) to mark regions of a sensitive object)
wherein coupling a plurality of PODs to a plurality of hosts to configure a network structure optimized for executing the Al workload (paragraphs [0043]-[0044] describe the clients cooperate with the IN by issuing requests to the IN to receive responses and interact with various components of the ID. The clients transmit information to the IN that allows the IN to perform computations; Fig. 5.1; paragraphs [0150]-[0164] describe operations perform by the IN by applying ML/AI model to detect/recognize objects, specific actions and features marked as “sensitive” in the testing data).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Lokesh for fortifying user security. The teachings of Lokesh, when implemented in the ‘491 system, will allow one of ordinary skill in the art to prevent unauthorized access to digital interactions to ensure data confidentiality. One of ordinary skill in the art would be motivated to utilize the teachings of Lokesh in the ‘491 system in order to ensure that an additional layer of security is provided to users so that users can enhance their data privacy and security by masking or blurring images of specific objects in their video feed remains hidden from potential prying eyes, for a better user experience (Lokesh: paragraph [0024]).
As for claim 4, the combined system of ‘491 and Lokesh teaches wherein executing the data distribution task comprises:
determining a required number of data distribution stages for execution of the data distribution task based on at least an aggregate count of the plurality of hosts (‘491; claim 4, 1st stanza); and
transmitting the plurality of data portions in a sequence of data distribution stages based on the required number of data distribution stages (‘491; claim 4, 2nd stanza).
As for claim 5, the combined system of ‘491 and Lokesh teaches wherein for each data distribution stage (s) (‘491; claim 5, preamble), the method comprises:
identifying a destination host (j) for each source host (i) based on at least a distribution of hosts (Hz) within each POD, and the radix (k) of each switch (‘491; claim 5, 1st stanza); and
transmitting a first data portion from the source host (i) to the identified destination host (j) via the corresponding subset of the plurality of PODs using a bandwidth, B, of corresponding communication links (‘491; claim 5, 2nd stanza).
As for claim 6, the combined system of ‘491 and Lokesh teaches wherein the destination host is identified based on:
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(‘491; claim 6).
As for claim 7, the combined system of ‘491 and Lokesh teaches wherein, for each data distribution stage (s), a number of destination hosts for each source host (i) is determined based on a window size, W (‘491: claim 7), and wherein the number of destination hosts for each source host (i) is equal to the window size, W (‘491; claim 8).
As for claim 9, the combined system of ‘491 and Lokesh teaches wherein executing the data distribution task in the sequence of data distribution stages further comprises (‘491; claim 12, preamble):
iteratively determining the destination host (j) for each source host (i) at each data distribution stage (s) for the required number of data distribution stages (‘491, claim 12, 1st stanza); and
at each iteration, transmitting data portions from the plurality of data portions from the source host (i) to the determined destination host (j) (‘491, claim 12, 2nd stanza).
As for claim 10, the combined system of ‘491 and Lokesh teaches wherein the method comprises:
determining that an allocation of the subset of the plurality of hosts under each POD is asymmetric (‘491: claim 13, 1st stanza);
integrating a plurality of virtual hosts in the network structure to balance the asymmetric distribution of the subset of the plurality of hosts under each POD to create a symmetric distribution (‘491: claim 13, 2nd stanza); and
executing the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host via the corresponding subset of PODs, wherein the at least one identified destination host comprises at least one of the plurality of hosts and the plurality of virtual hosts (‘491; claim 13, 3rd stanza).
As for claim 11, ‘491 teaches a system for allocation of network resources (claim 16, preamble), the system comprising:
a processing device (claim 16, 1st stanza); and
a non-transitory storage device containing instructions that, when executed by the processing device, cause the processing device to (claim 16, 2nd stanza):
receive, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the data distribution task is associated with an artificial intelligence (Al) workload, wherein the parameters comprise a plurality of data portions and a plurality of hosts (claim 16, 3rd stanza);
determine a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k) (claim 16, 4th stanza);
operatively couple the plurality of PODs to the plurality of hosts (claim 16, 5th stanza);
identify, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k) (claim 16, 6th stanza); and
execute the data distribution task by transmitting respective portions of the plurality of data portions to from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs (claim 16, 7th stanza).
‘491 fails to teach
wherein the data distribution task is associated with an artificial intelligence (AI) workload,
wherein a coupling the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload.
Lokesh discloses
wherein the transmission facilitates processing of the Al workload across the plurality of hosts (paragraphs [0024]-[0026] describe a distributed system comprising a number of clients, any number of infrastructure nodes (IN), the system fortifies user security by applying machine learning (ML) functionality of a microservice; paragraphs [0043]-[0044] describe the clients cooperate with the IN by issuing requests to the IN to receive responses and interact with various components of the ID. The clients transmit information to the IN that allows the IN to perform computations; paragraphs [0064] and [0101]-[0111] describe the IN and their components (e.g. the engine, the analyzer and the visualizer) utilize ML model to analyze, annotate data included in dataset (from the clients) to mark regions of a sensitive object)
wherein coupling a plurality of PODs to a plurality of hosts to configure a network structure optimized for executing the Al workload (paragraphs [0043]-[0044] describe the clients cooperate with the IN by issuing requests to the IN to receive responses and interact with various components of the ID. The clients transmit information to the IN that allows the IN to perform computations; Fig. 5.1; paragraphs [0150]-[0164] describe operations perform by the IN by applying ML/AI model to detect/recognize objects, specific actions and features marked as “sensitive” in the testing data).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Lokesh for fortifying user security. The teachings of Lokesh, when implemented in the ‘491 system, will allow one of ordinary skill in the art to prevent unauthorized access to digital interactions to ensure data confidentiality. One of ordinary skill in the art would be motivated to utilize the teachings of Lokesh in the ‘491 system in order to ensure that an additional layer of security is provided to users so that users can enhance their data privacy and security by masking or blurring images of specific objects in their video feed remains hidden from potential prying eyes, for a better user experience (Lokesh: paragraph [0024]).
As for claim 12, the combined system of ‘491 and Lokesh teaches wherein, in executing the data distribution task, the instructions, when executed, cause the processing device to transmit the plurality of data portions according to an all-to-all communication pattern (‘491: claim 18).
As for claim 14, the combined system of ‘491 and Lokesh teaches wherein, in executing the data distribution task, the instructions when executed, cause the processing device to (‘491: claim 19, preamble):
determine a required number of data distribution stages for execution of the data distribution task based on at least an aggregate count of the plurality of hosts (‘491; claim 19, 1st stanza); and
transmit the plurality of data portions in a sequence of data distribution stages based on the required number of data distribution stages (‘491; claim 19, 2nd stanza).
As for claim 17, a computer program product for allocation of network resources, the computer program product comprising a non-transitory computer-readable medium comprising code configured to cause an apparatus to (claim 25, preamble):
receive, from a user input device, a data distribution task and parameters associated with the data distribution task, wherein the parameters comprise a plurality of data portions and a plurality of hosts (claim 25, 1st stanza);
determine a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs comprises a plurality of switches, wherein each switch is associated with a radix (k) (claim 25, 2nd stanza);
operatively couple the plurality of PODs to the plurality of hosts (claim 25, 3rd stanza);
identify, from the plurality of hosts, at least one destination host for each source host based on at least the radix (k) (claim 25, 4th stanza); and
execute the data distribution task by transmitting respective portions of the plurality of data portions to from each source host to the at least one identified destination host via a corresponding subset of the plurality of PODs (claim 25, 5th stanza)
‘491 fails to teach
wherein the data distribution task is associated with an artificial intelligence (AI) workload,
wherein a couple the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload.
Lokesh discloses
wherein the transmission facilitates processing of the Al workload across the plurality of hosts (paragraphs [0024]-[0026] describe a distributed system comprising a number of clients, any number of infrastructure nodes (IN), the system fortifies user security by applying machine learning (ML) functionality of a microservice; paragraphs [0043]-[0044] describe the clients cooperate with the IN by issuing requests to the IN to receive responses and interact with various components of the ID. The clients transmit information to the IN that allows the IN to perform computations; paragraphs [0064] and [0101]-[0111] describe the IN and their components (e.g. the engine, the analyzer and the visualizer) utilize ML model to analyze, annotate data included in dataset (from the clients) to mark regions of a sensitive object);
wherein couple a plurality of PODs to a plurality of hosts to configure a network structure optimized for executing the Al workload (paragraphs [0043]-[0044] describe the clients cooperate with the IN by issuing requests to the IN to receive responses and interact with various components of the ID. The clients transmit information to the IN that allows the IN to perform computations; Fig. 5.1; paragraphs [0150]-[0164] describe operations perform by the IN by applying ML/AI model to detect/recognize objects, specific actions and features marked as “sensitive” in the testing data).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Lokesh for fortifying user security. The teachings of Lokesh, when implemented in the ‘491 system, will allow one of ordinary skill in the art to prevent unauthorized access to digital interactions to ensure data confidentiality. One of ordinary skill in the art would be motivated to utilize the teachings of Lokesh in the ‘491 system in order to ensure that an additional layer of security is provided to users so that users can enhance their data privacy and security by masking or blurring images of specific objects in their video feed remains hidden from potential prying eyes, for a better user experience (Lokesh: paragraph [0024]).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as failing to set forth the subject matter which the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the applicant regards as the invention.
As for claim 1, the claim recites the limitation “each switch is associated with a radix (k)” without providing information to define the recited parameter “radix(k)”. The claim is indefinite because it fails to provide adequate information to make use and understand the claim.
Claim 1 also recites in line 14 the limitation “executing the data distribution task by transmitting respective portions of the plurality of data portions to from each source host to the at least one identified destination host..” the phrase “to from” makes the claim indefinite because it fails to convey whether the transmission operation is an egress or an ingress operation and it also fails to convey whether each source host is a sender or a receiver of the portions of the distribution task. The claim is interpreted as “transmitting respective portions of the plurality of data portion from each source host to the at lease one identified host”
Similar limitation is also recited in claims 11 and 17.
As for claim 6, the claim recites a formula comprising multiple parameters, however, the claim fails to define the value of each of the parameters which enable an ordinary skill in the art to understand and execute the recited formula.
Similar limitation is also recited in claim 16.
Claims 2-10, 12-16 and 18-20 are dependent claims of claims 1, 11 and 17. Therefore, the claims inherit the same deficiency of their parent claim.
Due to the deficiencies, the claims are interpreted broadly.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 11 and 17 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Marr et al. (US 2016/0087915), hereinafter Marr in view of Lokesh (US 2025/0363224).
As for claim 1, Marr teaches a method, the method comprising:
receiving, from a user input device, a data distribution task and parameters associated with the data distribution task (Fig. 5; paragraphs [0026], [0035] and [0054] describe an end user device send requests across a network to one of a plurality of core switches. The request includes a workload data having a specified terminating address, the request is received to one of a group of host servers selected to process a common set of workload data for a customer), wherein the parameters comprise a plurality of data portions and a plurality of hosts (paragraphs [0035] and [0054] describe a request is received to a provisioning component for a network environment which includes a plurality of host servers connected by an aggregation fabric including layers of network switches. A number of the host servers is determined to be included in a group of hosts for performing subsequent operations associated with a source of the request. For a lowest layer of the aggregation fabric, a number of network switches over which to disperse the group of host servers is determined);
determining a plurality of points of delivery (PODs) based on the plurality of hosts, wherein the plurality of PODs is associated with a plurality of switches (paragraph [0035] describes a number of the host servers is determined to be included in a group of hosts for performing subsequent operations associated with a source of the request. For a lowest layer of the aggregation fabric, a number of network switches over which to disperse the group of host servers is determined. At least one of the determined number of host servers connected to each network switch of the lowest level can be assigned to process one of the subsequent operation), wherein each switch is associated with a radix (k) (paragraphs [0027]-[0029] describe each core switch is able to communicate with each of a plurality of aggregation switches which are utilized in pairs, each aggregation switch can be connected to a number of different racks, each with a number of host machines, the arrangement is a high radix interconnection);
operatively coupling the plurality of PODs to the plurality of hosts to configure a network structure (paragraphs [0027] and [0030]-[0031] describe each pair of aggregation switches is linked to a plurality of physical racks, each of which contains a top of rack or access switch and a plurality of physical host machines);
identifying, from the plurality of hosts, at least one destination host for each source host based on at least the radix(k) (paragraph [0062] describes the practice of clustering participating hosts to subtend a smaller section of network spanning tree can be used to reduce load on the higher switching layers. All hosts can be connected to a single switch, such that a host would need only one intermediate hop to get to other hosts); and
executing the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host via the corresponding subset of the plurality of PODs (Fig. 5, paragraph [0054] describes a process for dispersing workload data that have a specified terminating address. Workload data is received to one of a group of host servers selected to process a common set of workload data for a customer. The workload data can be routed to the appropriate host server corresponding to the address and the workload can be processed by that host server. If there are data updates as a result of the processing that need to be propagated to the other host servers in the group, the processing host server selects a random ordering of the other host servers in the group. The data updates then can be sent to each of the other host servers according to the random ordering).
Marr fails to teach
wherein the data distribution task is associated with an artificial intelligence (AI) workload,
wherein operatively a coupling the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload.
Lokesh discloses
wherein the data distribution task is associated with an artificial intelligent (Al) workload (paragraphs [0024]-[0026] describe a distributed system comprising a number of clients, any number of infrastructure nodes (IN), the system fortifies user security by applying machine learning (ML) functionality of a microservice; paragraphs [0043]-[0044] describe the clients cooperate with the IN by issuing requests to the IN to receive responses and interact with various components of the ID. The clients transmit information to the IN that allows the IN to perform computations; paragraphs [0064] and [0101]-[0111] describe the IN and their components (e.g. the engine, the analyzer and the visualizer) utilize ML model to analyze, annotate data included in dataset (from the clients) to mark regions of a sensitive object)
wherein operatively coupling the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload (paragraphs [0043]-[0044] describe the clients cooperate with the IN by issuing requests to the IN to receive responses and interact with various components of the ID. The clients transmit information to the IN that allows the IN to perform computations; Fig. 5.1; paragraphs [0150]-[0164] describe operations perform by the IN by applying ML/AI model to detect/recognize objects, specific actions and features marked as “sensitive” in the testing data).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Lokesh for fortifying user security. The teachings of Lokesh, when implemented in the Marr system, will allow one of ordinary skill in the art to prevent unauthorized access to digital interactions to ensure data confidentiality. One of ordinary skill in the art would be motivated to utilize the teachings of Lokesh in the Marr system in order to ensure that an additional layer of security is provided to users so that users can enhance their data privacy and security by masking or blurring images of specific objects in their video feed remains hidden from potential prying eyes, for a better user experience (Lokesh: paragraph [0024]).
As for claim 11, Marr teaches a system for allocation of network resources, the system comprising:
a processing device (paragraph [0026] describes servers); and
a non-transitory storage device containing instructions that, when executed by the processing device (paragraphs [0099]-[0100] describe computer-readable storage medium containing code that is read by computer-readable storage media reader to perform operations), cause the processing device to:
receive, from a user input device, a data distribution task and parameters associated with the data distribution task (Fig. 5; paragraphs [0026], [0035] and [0054] describe an end user device send requests across a network to one of a plurality of core switches. The request includes a workload data having a specified terminating address, the request is received to one of a group of host servers selected to process a common set of workload data for a customer), wherein the parameters comprise a plurality of data portions and a plurality of hosts (paragraphs [0035] and [0054] describe a request is received to a provisioning component for a network environment which includes a plurality of host servers connected by an aggregation fabric including layers of network switches. A number of the host servers is determined to be included in a group of hosts for performing subsequent operations associated with a source of the request. For a lowest layer of the aggregation fabric, a number of network switches over which to disperse the group of host servers is determined);
determine a plurality of points of delivery (PODs) based on the plurality of hosts (paragraph [0035] describes a number of the host servers is determined to be included in a group of hosts for performing subsequent operations associated with a source of the request. For a lowest layer of the aggregation fabric, a number of network switches over which to disperse the group of host servers is determined. At least one of the determined number of host servers connected to each network switch of the lowest level can be assigned to process one of the subsequent operation), wherein each switch is associated with a radix (k) (paragraphs [0027]-[0029] describe each core switch is able to communicate with each of a plurality of aggregation switches which are utilized in pairs, each aggregation switch can be connected to a number of different racks, each with a number of host machines, the arrangement is a high radix interconnection);
operatively couple the plurality of PODs to the plurality of hosts to configure a network structure (paragraphs [0027] and [0030]-[0031] describe each pair of aggregation switches is linked to a plurality of physical racks, each of which contains a top of rack or access switch and a plurality of physical host machines);
identify, from the plurality of hosts, at least one destination host for each source host based on at least the radix(k) (paragraph [0062] describes the practice of clustering participating hosts to subtend a smaller section of network spanning tree can be used to reduce load on the higher switching layers. All hosts can be connected to a single switch, such that a host would need only one intermediate hop to get to other hosts), wherein the number of communication hops is determined based on a corresponding subset of the plurality of switches associated with traversal of data from each source host to the at least one destination (paragraphs [0059]-[0061] describe hop and link bandwidth, a route with three hops is cheaper than a route with five hops. In an oversubscribed environment, dispersing workloads across as any switches as possible may not be an optimal approach, instead clustering participating hosts to subtend a smaller section of network spanning tree can be used to reduce load on the higher switching layers. All hosts can be connected to a single switch, such that a host would need only one intermediate hop to get to other hosts); and
execute the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host via the corresponding subset of the plurality of PODs (Fig. 5, paragraph [0054] describes a process for dispersing workload data that have a specified terminating address. The workload data can be routed to the appropriate host server corresponding to the address and the workload can be processed by that host server. If there are data updates as a result of the processing that need to be propagated to the other host servers in the group, the processing host server selects a random ordering of the other host servers in the group. The data updates then can be sent to each of the other host servers according to the random ordering).
Marr fails to teach
wherein the data distribution task is associated with an artificial intelligence (AI) workload,
wherein operatively a coupling the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload.
Lokesh discloses
wherein the data distribution task is associated with an artificial intelligent (Al) workload (paragraphs [0024]-[0026] describe a distributed system comprising a number of clients, any number of infrastructure nodes (IN), the system fortifies user security by applying machine learning (ML) functionality of a microservice; paragraphs [0043]-[0044] describe the clients cooperate with the IN by issuing requests to the IN to receive responses and interact with various components of the ID. The clients transmit information to the IN that allows the IN to perform computations; paragraphs [0064] and [0101]-[0111] describe the IN and their components (e.g. the engine, the analyzer and the visualizer) utilize ML model to analyze, annotate data included in dataset (from the clients) to mark regions of a sensitive object)
wherein operatively coupling the plurality of PODs to the plurality of hosts to configure a network structure optimized for executing the Al workload (paragraphs [0043]-[0044] describe the clients cooperate with the IN by issuing requests to the IN to receive responses and interact with various components of the ID. The clients transmit information to the IN that allows the IN to perform computations; Fig. 5.1; paragraphs [0150]-[0164] describe operations perform by the IN by applying ML/AI model to detect/recognize objects, specific actions and features marked as “sensitive” in the testing data).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Lokesh for fortifying user security. The teachings of Lokesh, when implemented in the Marr system, will allow one of ordinary skill in the art to prevent unauthorized access to digital interactions to ensure data confidentiality. One of ordinary skill in the art would be motivated to utilize the teachings of Lokesh in the Marr system in order to ensure that an additional layer of security is provided to users so that users can enhance their data privacy and security by masking or blurring images of specific objects in their video feed remains hidden from potential prying eyes, for a better user experience (Lokesh: paragraph [0024]).
As for claim 17, the claim recites limitations that are similar to limitations of method claim 1. Therefore, the rejection of claim 1 is equally applied to the rejection of claim 17.
Claims 2-4, 9, 12-14, 18, 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Marr (US 2016/0087915) in view of Lokesh (US 2025/0363224) further in view of Miwa et al. (US 10,361,886 B2), hereinafter Miwa.
As for claim 2, the combined system of Marr and Lokesh fails to teach wherein executing a data distribution task comprises transmitting a plurality of data portions according to an all-to-all communication pattern.
Miwa discloses wherein executing a data distribution task comprises transmitting a plurality of data portions according to an all-to-all communication pattern (col. 4, lines 10-11 describe the nodes of a system perform all-to-all communication).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Miwa for performing all-to-all communication. The teachings of Miwa, when implemented in the Marr and Lokesh system, will allow one of ordinary skill in the art to transmit data in a mesh network. One of ordinary skill in the art would be motivated to utilize the teachings of Miwa in the Marr and Lokesh system in order to perform all-to-all communication which prevents delay and avoid communication path contention.
As for claim 3, the combined system of Marr and Lokesh teaches wherein configuring the network structure comprises arranging the plurality of PODs and the plurality of hosts topology to facilitate data transmission (Lokesh: paragraph [0043] describes the clients utilize, rely on, or otherwise cooperate with the IN. For example, the clients issue requests to the IN to receive responses and interact with various components of the IN. The clients also request data from and/or send data to the IN).
The combined system of Marr and Lokesh fails to teach wherein a topology is a mesh topology.
Miwa discloses
wherein a topology is a mesh topology (paragraph [0053] describes a full mesh topology).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Miwa for implementing a full mesh topology. The teachings of Miwa, when implemented in the Marr and Lokesh system, will allow one of ordinary skill in the art to distribute data in a mesh network. One of ordinary skill in the art would be motivated to utilize the teachings of Miwa in the Marr and Lokesh system in order to perform all-to-all communication which prevents delay and avoid communication path contention
As for claim 4, the combined system of Marr, Lokesh and Miwa teaches wherein executing the data distribution task comprises:
determining a required number of data distribution layers for execution of the data distribution task based on at least an aggregate count of the plurality of hosts (Marr: paragraph [0025] describes multiple hosts are used to perform tasks, some of these hosts can be grouped together into clusters or other functional groups for the performance of specific tasks; paragraphs [0031]-[0032] and [0035] describe a two-tier folded Clos network which implements two layers of switches. A network environment includes a plurality of host servers connected by an aggregation fabric including layers of network switches. A number of the host servers is determined to be included in a group of hosts for performing subsequent operations associated with a source of the request. At least one of the determined number of host servers connected to each network switch of the lowest layer can be assigned to process one of the subsequent operations. The network is configured to include multiple layers of host servers, switches and hosts to execute a customer’s workload, therefore, data distribution stages are determined according to the hosts assigned to each layer); and
transmitting the plurality of data portions in a sequence of data distribution layers based on the required number of data distribution stages (Marr: paragraph [0035] describes the distribution of workload via the network environment).
The combined system of Marr and Lokesh fails to explicitly teach
wherein layers are stages.
Miwa discloses
wherein layers are stages (col. 4, lines 10-15 describe packet switching between n nodes is performed in n phases; col. 4, lines 44-46 and col. 5, lines 21-22 describe a determination unit determines a destination node of a packet in each phase based on the data stored in a data storage unit).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Miwa for implementing a network topology that spans to different stages. The teachings of Miwa, when implemented in the Marr and Lokesh system, will allow one of ordinary skill in the art to transmit data in a mesh network. One of ordinary skill in the art would be motivated to utilize the teachings of Miwa in the Marr and Lokesh system in order to perform all-to-all communication which prevents delay and avoid communication path contention.
As for claim 9, the combined system of Marr, Lokesh and Miwa teaches wherein executing the data distribution task in the sequence of data distribution stages further comprises:
iteratively determining the destination host (j) for each source host (i) at each data distribution stage (s) for the required number of data distribution stages (Miwa: col. 5, lines 18-26 describe a determination unit in a node obtains the node number of a transmission source node from a data storage unit, the determination unit sets a variable i for a phase, the determination unit then determines a destination node in phase i to be the node with the calculated node number; col. 5, lines 53-55 describe an illustration of node number of a destination node of each of transmission source nodes in each phase); and
at each iteration, transmitting data portions from the plurality of data portions from the source host (i) to the at least one identified destination host (j) (Miwa: col. 5, lines 65-67 and col. 6, lines 1-7 describe a communication unit generates a packet including the node number and transmits the packet to a leaf switch connected to the node 0, the leaf switch receives the packet and recognizes a link for transferring the packet to a destination node).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Miwa for implementing a network topology that spans to different stages. The teachings of Miwa, when implemented in the Marr and Lokesh system, will allow one of ordinary skill in the art to transmit data in a mesh network. One of ordinary skill in the art would be motivated to utilize the teachings of Miwa in the Marr and Lokesh system in order to perform all-to-all communication which prevents delay and avoid communication path contention.
As for claim 12, the combined system of Marr and Lokesh teaches wherein the instructions, when executed, cause the processing device to execute the data distribution task by transmitting the plurality of data portions according to an communication pattern (paragraphs [0099]-[0100] describe computer-readable storage medium containing code that is read by computer-readable storage media reader to perform operations; paragraphs [0044]-[0045] describe all nodes within a task cluster communicate with all other nodes concurrently).
The combined system of Marr and Lokesh fails to teach wherein data are transmitted according to an all-to-all communication pattern.
Miwa discloses wherein data are transmitted according to an all-to-all communication pattern (col. 4, lines 10-11 describe the nodes of a system perform all-to-all communication).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Miwa for performing all-to-all communication. The teachings of Miwa, when implemented in the Marr and Lokesh system, will allow one of ordinary skill in the art to transmit data in a mesh network. One of ordinary skill in the art would be motivated to utilize the teachings of Miwa in the Marr and Lokesh system in order to perform all-to-all communication which prevents delay and avoid communication path contention.
As for claim 13, the combined system of Marr and Lokesh teaches wherein , in configuring the network structure, the instructions, when executed, cause the processing device to arrange the plurality of PODs and the plurality of hosts topology to facilitate data transmission (Lokesh: paragraph [0043] describes the clients utilize, rely on, or otherwise cooperate with the IN. For example, the clients issue requests to the IN to receive responses and interact with various components of the IN. The clients also request data from and/or send data to the IN).
The combined system of Marr and Lokesh fails to teach wherein a topology is a mesh topology.
Miwa discloses
wherein a topology is a mesh topology (paragraph [0053] describes a full mesh topology).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Miwa for implementing a full mesh topology. The teachings of Miwa, when implemented in the Marr and Lokesh system, will allow one of ordinary skill in the art to distribute data in a mesh network. One of ordinary skill in the art would be motivated to utilize the teachings of Miwa in the Marr and Lokesh system in order to perform all-to-all communication which prevents delay and avoid communication path contention1
As for claim 14, the combined system of Marr and Lokesh teaches wherein the instructions, when executed, cause the processing device to execute the data distribution task by:
determine a required number of data distribution layers for execution of the data distribution task based on at least an aggregate count of the plurality of hosts (Marr: paragraph [0025] describes multiple hosts are used to perform tasks, some of these hosts can be grouped together into clusters or other functional groups for the performance of specific tasks; paragraphs [0031]-[0032] and [0035] describe a two-tier folded Clos network which implements two layers of switches. A network environment includes a plurality of host servers connected by an aggregation fabric including layers of network switches. A number of the host servers is determined to be included in a group of hosts for performing subsequent operations associated with a source of the request. At least one of the determined number of host servers connected to each network switch of the lowest layer can be assigned to process one of the subsequent operations. The network is configured to include multiple layers of host servers, switches and hosts to execute a customer’s workload, therefore, data distribution stages are determined according to the hosts assigned to each layer); and
transmit the plurality of data portions in a sequence of data distribution layers based on the required number of data distribution layers (Marr: paragraph [0035] describes the distribution of workload via the network environment).
Marr fails to explicitly teach
wherein layers are stages.
Miwa discloses
wherein layers are stages (col. 4, lines 10-15 describe packet switching between n nodes is performed in n phases; col. 4, lines 44-46 and col. 5, lines 21-22 describe a determination unit determines a destination node of a packet in each phase based on the data stored in a data storage unit).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Miwa for implementing a network topology that spans to different stages. The teachings of Miwa, when implemented in the Marr and Lokesh system, will allow one of ordinary skill in the art to transmit data in a mesh network. One of ordinary skill in the art would be motivated to utilize the teachings of Miwa in the Marr and Lokesh system in order to perform all-to-all communication which prevents delay and avoid communication path contention.
Claims 18, 19 and 20, these claims contains the same limitations of claims 9, 13 and 14, respectively. Therefore, the rejection of claims 9 and 14 are equally applied to the rejection of claims 18, 19 and 20, respectively.
Claims 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Marr (US 2016/0087915) and Lokesh (US 2025/0363224) in view of Miwa (US 10,361,886 B2) further in view of Chiussi et al. (US 7,027,457), hereinafter Chiussi.
As for claim 5, the combined system of Marr, Lokesh and Miwa teaches wherein, for each data distribution stage (s), the method comprises:
identifying a destination host (j) for each source host (i) based on at least a distribution of hosts (Hx) within each POD, and the radix (k) of each switch (Marr: paragraph [0062] describes the practice of clustering participating hosts to subtend a smaller section of network spanning tree can be used to reduce load on the higher switching layers. All hosts can be connected to a single switch, such that a host would need only one intermediate hop to get to other hosts);
transmitting a first data portion from the source host (i) to the identified destination host (j) via the corresponding subset of the plurality of PODs (Fig. 5, paragraph [0054] describes a process for dispersing workload data that have a specified terminating address. Workload data is received to one of a group of host servers selected to process a common set of workload data for a customer. The workload data can be routed to the appropriate host server corresponding to the address and the workload can be processed by that host server. If there are data updates as a result of the processing that need to be propagated to the other host servers in the group, the processing host server selects a random ordering of the other host servers in the group. The data updates then can be sent to each of the other host servers according to the random ordering).
The combined system of Marr, Lokesh and Miwa fails to teach wherein transmitting data portions from a source host (i) via the corresponding subset of the plurality of PODs using a bandwidth, B, of corresponding communication links.
Chiussi discloses
wherein transmitting a data portion from a source host (i) via the corresponding subset of the plurality of PODs using a bandwidth, B, of corresponding communication links (col. 3, lines 10-35 describe a switch fabric comprising a plurality of switch fabric outputs and a plurality of egress port cards. Each of the ingress port cards receives a respective plurality of data packets via respective input link; col. 5, lines 36-53 describe the configured traffic flows are grouped by QoS class and by destination into per-output subgroups. The port scheduler assigns bandwidth to the QoS class based on the aggregate requirements of the respective traffic flows).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Chiussi for providing differentiated QoS guarantees to data transfer sessions in packet switches having multiple contention points. The teachings of Chiussi, when implemented in the Marr, Lokesh and Miwa system, will allow one of ordinary skill in the art to satisfy QoS requirements. One of ordinary skill in the art would be motivated to utilize the teachings of Chiussi in the Marr, Lokesh and Miwa system in order to process large amount of data content and avoid network congestions.
As for claim 15, the combined system of Marr, Lokesh and Miwa teaches wherein for each data distribution stage (s), the instructions, when executed, cause the processing device to:
identifying a destination host (j) for each source host (i) (Marr: paragraph [0062] describes the practice of clustering participating hosts to subtend a smaller section of network spanning tree can be used to reduce load on the higher switching layers. All hosts can be connected to a single switch, such that a host would need only one intermediate hop to get to other hosts); and
transmitting a first data portion from the source host (i) to the identified destination host (j) via the corresponding subset of the plurality of PODs (Fig. 5, paragraph [0054] describes a process for dispersing workload data that have a specified terminating address. Workload data is received to one of a group of host servers selected to process a common set of workload data for a customer. The workload data can be routed to the appropriate host server corresponding to the address and the workload can be processed by that host server. If there are data updates as a result of the processing that need to be propagated to the other host servers in the group, the processing host server selects a random ordering of the other host servers in the group. The data updates then can be sent to each of the other host servers according to the random ordering).
The combined system of Marr, Lokesh and Miwa fails to teach wherein transmitting data portions from a source host (i) via the corresponding subset of the plurality of PODs using a bandwidth, B, of corresponding communication links.
Chiussi discloses
wherein transmitting a data portion from a source host (i) via the corresponding subset of the plurality of PODs using a bandwidth, B, of corresponding communication links (col. 3, lines 10-35 describe a switch fabric comprising a plurality of switch fabric outputs and a plurality of egress port cards. Each of the ingress port cards receives a respective plurality of data packets via respective input link; col. 5, lines 36-53 describe the configured traffic flows are grouped by QoS class and by destination into per-output subgroups. The port scheduler assigns bandwidth to the QoS class based on the aggregate requirements of the respective traffic flows).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Chiussi for providing differentiated QoS guarantees to data transfer sessions in packet switches having multiple contention points. The teachings of Chiussi, when implemented in the Marr, Lokesh and Miwa system, will allow one of ordinary skill in the art to satisfy QoS requirements. One of ordinary skill in the art would be motivated to utilize the teachings of Chiussi in the Marr, Lokesh and Miwa system in order to process large amount of data content and avoid network congestions.
Allowable Subject Matter
Claims 6-8, 10 and 16 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
As for claim 6, the claim recites the limitations “The method of Claim 5, wherein the destination host is identified based on:
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As for claim 7, the claim recites the limitations “The method of Claim 5, wherein, for each data distribution stage (s), a number of destination hosts for each source host (i) is determined based on a window size, W, and wherein the number of destination hosts for each source host (i) is equal to the window size, W.”
As for claim 8, the claim recited the limitations “The method of Claim 7, wherein for window size, W>1, executing the data distribution task comprises executing the data distribution task in a clustered grouping of data distribution stages, wherein a size of the clustered grouping is based on at least the window size, W.”
As for claim 10, the claim recites the limitations “10. The method of Claim 1, wherein the method comprises:
determining that an allocation of the subset of the plurality of hosts under each POD is asymmetric;
integrating a plurality of virtual hosts in the network structure to balance the asymmetric distribution of the subset of the plurality of hosts under each POD to create a symmetric distribution; and
executing the data distribution task by transmitting respective portions of the plurality of data portions from each source host to the at least one identified destination host via the corresponding subset of PODs, wherein the at least one identified destination host comprises at least one of the plurality of hosts and the plurality of virtual hosts.”
As for claim 16, the claim recites the limitations “The method of Claim 15, wherein the destination host is identified based on:
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The following is a statement of reasons for the indication of allowable subject matter: prior art fails to teach the limitations recited in the claims.
As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kwon et al. (US 2024/0201952) teach artificial intelligence operation system and method
Benson et al. (US 2024/0004779) teach framework for distributed open-loop vehicle simulation
Al-Maamari et al. (US 2023/0153147) teach ad-hoc proxy for batch processing task
Singh et al. (US 2025/0274382) teach method for probing network paths in disaggregated scheduled fabrics.
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/L.T.N/ Examiner, Art Unit 2459 /SCHQUITA D GOODWIN/Primary Examiner, Art Unit 2459
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