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 .
DETAILED ACTION
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 7/14/26 has been entered.
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.
Claim 17 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 17 recites “the virtual control engine” without prior introduction and therefore is unclear. For the purposes of examining, the limitation will be interpreted as “a virtual control engine”.
Claim Interpretation - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
Claim limitations 1-8, 17-21 has/have been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses/they use a generic placeholders: semiconductor farm, input/output hardware units, second type chip, communications interface, control engine, field controller, communications modalities, chip, coupled with functional language without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier. Since the claim limitation(s) invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, claim 13 has/have been interpreted to cover the corresponding structure described in the specification that achieves the claimed function, and equivalents thereof.
A review of the specification, Fig. 4 [0054] shows that the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph limitation.
If applicant wishes to provide further explanation or dispute the examiner’s interpretation of the corresponding structure, applicant must identify the corresponding structure with reference to the specification by page and line number, and to the drawing, if any, by reference characters in response to this Office action.
If applicant does not intend to have the claim limitation(s) treated under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112 , sixth paragraph, applicant may amend the claim(s) so that it/they will clearly not invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, or present a sufficient showing that the claim recites/recite sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
For more information, see MPEP § 2173 et seq. and Supplementary Examination Guidelines for Determining Compliance With 35 U.S.C. 112 and for Treatment of Related Issues in Patent Applications, 76 FR 7162, 7167 (Feb. 9, 2011).
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.
Claim/s 1, 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan (Pub. No. US 2021/0382452) in view of Chandran (Pub. No. US 20190223248).
Claim 1, Krishnan teaches “a system, comprising: a semiconductor farm programmed to provide a plurality of virtualized controllers ([0043] The illustrative distributed building management 30 includes a virtual controller 32 that is hosted on a computing device 34. The virtual controller 32 may be considered as being an example of the virtual controllers 24 while the computing device 34 may be considered as being an example of the computing device 14 of FIG. 1. [0035] As used in this specification and the appended claims, the singular forms “a”, “an”, and “the” include the plural referents unless the content clearly dictates otherwise.); and a plurality of input/output hardware units corresponding to the plurality of virtualized controllers, wherein the plurality of virtualized controllers control building equipment via the plurality of input/output hardware units, the plurality of input/output hardware units located remotely from the semiconductor farm ([0043] FIG. 2 is a schematic block diagram of an illustrative distributed building management system 30 for controlling a building control device 40 (i.e. input/output hardware units) at a building site 42. In some cases, the illustrative distributed building management system 30 may be considered as a smaller example of the building system 10 shown in FIG. 1. The illustrative distributed building management 30 includes a virtual controller 32 that is hosted on a computing device 34. The virtual controller 32 may be considered as being an example of the virtual controllers 24 while the computing device 34 may be considered as being an example of the computing device 14 of FIG. 1. In some cases, the virtual controller 32 has assigned resources including assigned memory resources and assigned processing resources, wherein at least one of the assigned memory resource and assigned processing resources are adjustable via a software setting (e.g. via the orchestrator 26). The virtual controller 32 includes a virtual container or a virtual machine 36 that includes control logic 38. The control logic 38 generates control commands for controlling the building control device 40 at the building site 42. The building control device 40 may, for example, be considered as an example of one of the building management system components 18 referenced in FIG. 1.)”.
However, Krishnan may not explicitly teach the remaining limitations.
Chandran teaches “wherein the plurality of input/output hardware units are configured to communicate with the semiconductor farm via a first type of wireless communications channel and a second type of wireless communications channel ([0056] According to various embodiments, the wireless interface 210 of the building control device 200 may permit the building control device 200 to communicate over one or more wireless networks, such as network 218 and/or network 220, for example. In some cases, the wireless interface 210 may utilize a wireless protocol to communicate with a remote device 216 over network 218 and/or network 220. In some cases, networks 218 and 220 may include a Local Area Networks (LAN) such as a Wi-Fi network and/or a Wide Area Networks (WAN) such as the Internet and/or a cellular network. These are just some examples.), wherein the input/output hardware units communicate with the semiconductor farm via the second type of wireless communications channel responsive to interruption of the first type of wireless communications channel ([0059] For example, in certain embodiments, the wireless interface 210 may initially be connected to network 218 through a router, gateway or other device that functions as a network access point. In this example, the wireless interface 210 may lose connection with the network access point and become disconnected from network 218. The wireless interface 210 may become disconnected from the network 218 for any number of different reasons including, for example, a change in the network credentials of the network 218 (e.g. a change in SSID or network password of a WiFi network), a weakened or lost network signal causing the network 218 to be no longer reliably available to the wireless interface 210, the network host device of the network 218 (e.g. router or gateway) fails or otherwise becomes non-operational, and/or for a variety of other reasons. [0061] When the wireless interface 210 is not able to be reconnected to the network 218 after a predetermined amount of time (e.g. 1 second, 10 seconds, 1 minute, 5 minutes, 30 minutes, 1 hour, 1 day, etc.), the controller 202 may switch the wireless interface 210 into a configuration mode to establish a direct wireless connection with the remote device 216. For instance, in the configuration mode, the wireless interface 210 may be configured to act as a network access point and/or simply act as a host for a wireless network. In some cases, when the wireless interface 210 is acting as a network access point, the wireless interface 210 is essentially a WiFi hot spot and hosts a temporary network connection 228.)”.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Chandran with the teachings of Krishnan in order to provide a system that teaches details of handling interruptions. The motivation for applying Chandran teaching with Krishnan teaching is to provide a system that allows for improved fail over during abnormal communications. Krishnan, Chandran are analogous art directed towards distributed environments. Together Krishnan, Chandran teach every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of invention, one of ordinary skill could have applied the teachings of Chandran with the teachings of Krishnan by known methods before the effective filing date of the claimed invention and gained expected results.
Claim 2, the combination teaches the claim, wherein Krishnan teaches “the system of Claim 1, wherein the semiconductor farm is programmed to provide the plurality of virtualized controllers in a plurality of scalable containers ([0064] Returning to the decision block 258, if the answer is no, control passes to block 264 where offline containers are identified and deleted. At block 266, new containers are spun to reach a To-Be state, using information provided from the Docker Image Repository. Control then passes to the decision block 260. At decision block 260, if there are virtual containers that are not sending heartbeat messages, control passes to block 270, where virtual containers that are not providing heartbeat messages are deleted. At block 272, new containers are spun to reach a To-Be state, using information from the Docker Image Repository. Appropriate building control devices may then be mapped to the new containers. The method 240 terminates at the stop block 262.)”.
Claim/s 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan, Chandran in further view of Thummala (Pub. No. US 2019/0332683).
Claim 3, the combination may not explicitly teach the limitation.
Thummala teaches “the system of Claim 1, wherein the semiconductor farm is further configured to automatically adjust allocations of processing power and/or memory to the plurality of virtualized controllers based on demands of the plurality of virtualized controllers ([0053] One of the benefits of a virtualized architecture is the ease of handling increases in load by “scaling up” virtual machines that satisfy a resource usage threshold (e.g., 95% of CPU or memory usage) by allocating additional resources (e.g., CPU or memory). )”.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Thummala with the teachings of Krishnan, Chandran in order to provide a system that teaches details of scaling. The motivation for applying Thummala teaching with Krishnan, Chandran teaching is to provide a system that allows for improved system performance. Krishnan, Chandran, Thummala are analogous art directed towards distributed environments. Together Krishnan, Chandran, Thummala teaches every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of invention, one of ordinary skill could have applied the teachings of Thummala with the teachings of Krishnan, Chandran by known methods before the effective filing date of the claimed invention and gained expected results.
Claim/s 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan, Chandran in further view of Chen (Pub. No. US 2019/0056942).
Claim 4, the combination may not explicitly teach the limitation.
Chen teaches “the system of Clam 1, wherein the semiconductor farm comprises a first type of chip and a second type of chip, wherein the semiconductor farm is configured to allocate, to a first virtualized controller or a second virtualized controller, the first type of chip based on a first function and the second type of chip based on a second function to be provided by the first virtualized controller or the second virtualized controller ([Abstract] In a distributed computing system comprising multiple processor types, a method of provisioning includes receiving a request from a client device for execution of a function. A first data structure identifies implementations of the function and compatible processor types for each implementation. A second data structure identifies available processors in the system. Compatible processor types matching available processors are candidates for execution of the function. A provisioning instruction is created for allocating resources for execution of the function. [0052] In the depicted embodiment, each one of master servers 102, resource servers 104 and client computing devices 106 is a separate physical device. In other embodiments, one or more of master servers 102, resource servers 104 and client computing devices 106 and components thereof are virtualized, that is, one or more of master servers 102, resource servers 104 and client computing devices 106 are virtual devices residing in software at another computing device. Virtualized machines are accessible by other ones of master servers 102, resource servers 104 and client computing devices for example by way of network 107. In other embodiments, a cluster of computing devices can be connected together, and each device in the cluster can serve more than one purpose. One of the devices may serve the role of the master device, and all devices may serve as both resource servers and client computing devices.)”.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Chen with the teachings of Krishnan, Chandran in order to provide a system that teaches allocating resources. The motivation for applying Chen teaching with Krishnan, Chandran teaching is to provide a system that allows for improved system performance. Krishnan, Chandran, Chen are analogous art directed towards distributed environments. Together Krishnan, Chandran, and Chen teaches every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of invention, one of ordinary skill could have applied the teachings of Chen with the teachings of Krishnan, Chandran by known methods before the effective filing date of the claimed invention and gained expected results.
Claim/s 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan, Chandran, Chen, in further view of Chen_1 (Pub. No. US 2020/0355390).
Claim 5, the combination may not explicitly teach the limitation.
Chen_1 teaches “the system of Claim 4, wherein the second type of chip is configured for artificial intelligence processing and wherein the second virtualized controller is configured to provide an artificial intelligence function ([0060] In the background sub-process, a first set of data, usually a smaller group of data categories with respect to the operating state of the HVAC devices and/or other related information, may be received and analyzed as a backend process, i.e., without interaction with client 270 and without being presented to client 270. For example, operation state data of target HVAC devices 220 may be received and analyzed to automatically control the operation of HVAC devices 220 according to established control parameters under the specific client VM 264 based on client registration. The background data may also be used for the purposes of machine learning and artificial intelligence as the historical performance records of the target HVAC devices 220. For example, the background sub-process may generate any number of key performance index (“KPI”) values of each of the concerned HVAC devices 220. The results of the background sub-process, although not presented in real time to the client 270, may be used in a subsequent foreground sub-process of the same container process 268. For example, historical KPI values, or information representative of any such KPI values, may be presented to client 270 together with real time HVAC data in a foreground sub-process. In an embodiment, a background sub-process receives data in a slower updating rate than a foreground sub-process of the same container process 268. In an embodiment, the data receiving for the background sub-process is automatically launched upon the establishment of the client VM 264 or the launching of the container process 268 and will continue regularly until or unless the client VM 264 is terminated or modified to remove the respective container process 268.)”.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Chen_1 with the teachings of Krishnan, Chandran, Chen in order to provide a system that teaches details of AI functions. The motivation for applying Chen_1 teaching with Krishnan, Chandran, Chen teaching is to provide a system that allows for design choice. Krishnan, Chandran, Chen, Chen_1, are analogous art directed towards distributed environments. Together Krishnan, Chandran, Chen, Chen_1 teaches every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of invention, one of ordinary skill could have applied the teachings of Chen_1 with the teachings of Krishnan, Chandran, Chen by known methods before the effective filing date of the claimed invention and gained expected results.
Claim/s 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan, Chandran, Chen, Chen_1, in further view of Nagasundaram (Pub. No. US 2023/0195485).
Claim 6, the combination may not explicitly teach the limitation.
Nagasundaram teaches “the system of Claim 5, wherein the semiconductor farm is configured to reallocate, responsive to selection of the artificial intelligence function for the first virtualized controller, one or more chips of the second type of chip to the first virtualized controller ([0030] The accelerators may represent one or more types of hardware accelerators (e.g., XPUs) to which various tasks (e.g., workloads 135a-n) may be offloaded from the CPU 100. For example, workloads 135a-n may include large AI and/or ML tasks that may be more efficiently performed by a graphics processing unit (GPU) than the CPU 100. In one embodiment, rather than being manufactured on a single piece of silicon, one or more of the accelerators may be made up of one of more smaller integrated circuit (IC) blocks (e.g., tile(s) 175a and tiles(s) 175m), for example, that represent reusable IP blocks that are specifically designed to work with other similar IC blocks to form larger more complex chips (e.g., accelerators 170a-y). [Abstract] A request to deploy a workload associated with a first VM is received.)”.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Nagasundaram with the teachings of Krishnan, Chandran, Chen, Chen_1 in order to provide a system that teaches allocation of resources. The motivation for applying Nagasundaram teaching with Krishnan, Chandran, Chen, Chen_1 teaching is to provide a system that allows for design choice. Krishnan, Chandran, Chen, Chen_1, Nagasundaram are analogous art directed towards distributed environments. Together Krishnan, Chandran, Chen, Chen_1, Nagasundaram teaches every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of invention, one of ordinary skill could have applied the teachings of Nagasundaram with the teachings of Krishnan, Chandran, Chen, Chen_1 by known methods before the effective filing date of the claimed invention and gained expected results.
Claim/s 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan, Chandran in view of Li (Pat. US. 10,660,153).
Claim 7, the combination may not explicitly teach the limitation.
Li teaches “the system of Claim 1, wherein the plurality input/output hardware units are configured to control the building equipment in a fail-safe routine in response to a loss of communications in both the first type of wireless communications channel and the second type of wireless communications channel between the plurality of input/output modules and the semiconductor farm ([Claim 5]. The device of claim 4, wherein when the processor places the emergency call to the endpoint over the second wireless network after the device is handed off or redirected from the first wireless network to the second wireless network, and if the placed emergency call fails to connect the device to the endpoint over the second wireless network, the processor is configured to: place an emergency call to the endpoint over a third wireless network)”.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Li with the teachings of Krishnan, Chandran in order to provide a system that teaches details of handling interruptions. The motivation for applying Li teaching with Krishnan, Chandran teaching is to provide a system that allows for improved fail over during abnormal communications. Krishnan, Chandran, Li are analogous art directed towards distributed environments. Together Krishnan, Chandran, Li teach every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of invention, one of ordinary skill could have applied the teachings of Li with the teachings of Krishnan, Chandran by known methods before the effective filing date of the claimed invention and gained expected results.
Claim/s 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan, Chandran in view of Ozadowicz.
Claim 8, the combination may not explicitly teach the limitation.
Ozadowicz teaches “the system of Claim 1, wherein the building equipment comprises a plurality of sensors and actuators corresponding to the plurality of input/output hardware units and the plurality of virtualized controllers ([0056] In the example of the HVAC system 14a, the controller 15a may be initially programmed to only operate the HVAC system 14a responsive to temperature or humidity sensors present in the environment 10. The VM 114a may adjust the parameters at the controller 15a to allow the HVAC system 14a to also operate responsive to an occupancy sensor present in the environment 10, the occupancy sensor using a protocol 103 different from the HVAC system 14a and the parameters used by the controller 15a not previously programmed to operate responsive to occupancy in the environment 10. The VM 114a may thus adjust the parameters of the controller 15a to be responsive to not only sensor data using a non-native protocol 103, but also including a newly introduced parameter. Thus, the controller 15 (i.e. actuator) may be reparameterized by the VM 114 based on, for example, operation of other infrastructure elements 14, sensors present but not connected to the infrastructure element 14, and other features of the infrastructure environment 10.)”.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Ozadowicz with the teachings of Krishnan, Chandran in order to provide a system that teaches details of an environment. The motivation for applying Ozadowicz teaching with Krishnan, Chandran teaching is to provide a system that allows for design choice. Krishnan, Chandran, Ozadowicz are analogous art directed towards distributed environments. Together Krishnan, Chandran, Ozadowicz teach every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of invention, one of ordinary skill could have applied the teachings of Ozadowicz with the teachings of Krishnan, Chandran by known methods before the effective filing date of the claimed invention and gained expected results.
Claim/s 17, 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan in view of Featonby (Pub. No. US 2018/0204301) in view of Zhoa (Pub. No. US 2020/0133735).
Claim 17, Krishnan teaches “A field controller for building equipment, comprising: a communications interface configured to provide communications between building equipment and a semiconductor farm located remotely from the building equipment ([0043] FIG. 2 is a schematic block diagram of an illustrative distributed building management system 30 for controlling a building control device 40 (i.e. input/output hardware units) at a building site 42. In some cases, the illustrative distributed building management system 30 may be considered as a smaller example of the building system 10 shown in FIG. 1. The illustrative distributed building management 30 includes a virtual controller 32 that is hosted on a computing device 34. The virtual controller 32 may be considered as being an example of the virtual controllers 24 while the computing device 34 may be considered as being an example of the computing device 14 of FIG. 1. In some cases, the virtual controller 32 has assigned resources including assigned memory resources and assigned processing resources, wherein at least one of the assigned memory resource and assigned processing resources are adjustable via a software setting (e.g. via the orchestrator 26). The virtual controller 32 includes a virtual container or a virtual machine 36 that includes control logic 38. The control logic 38 generates control commands for controlling the building control device 40 at the building site 42. The building control device 40 may, for example, be considered as an example of one of the building management system components 18 referenced in FIG. 1.)” … wherein the field controller is configured to control the building equipment to affect a variable state or condition of a building by executing the control logic ([0038] The illustrative building site 12 includes a number of edge controllers 20 that are individually labeled as 20a, 20b, 20c. The edge controllers 20 may be used, for example, to control operation of the building management system components 18 within the building management system 16. While a total of three edge controllers 20 are shown, it will be appreciated that this is merely illustrative, as the building site 12 may include any number of edge controllers 20. In an HVAC system, for example, a particular edge controller 20 could control operation of a VAV box that is represented by one of the building management system components 18. The edge controller 20 for that particular building management system component 18 may control the relative damper position within the VAV box in order to achieve a desired air flow, or perhaps to achieve a desired temperature set point, within a corresponding portion of the building site 12. While shown as having a one-to-one relationship between an individual building management system component 18 and a corresponding individual edge controller 20, this is not necessarily true in all cases. For example, in some cases, a single edge controller 20 could control operation of two or more different building management system components 18.)”.
However, Krishnan may not explicitly teach the remaining limitations.
Featonby teaches “a chip at the semiconductor farm, the chip executing control logic to provide a virtualized control engine ([Fig. 1] 151A on 152A GPU), wherein the chip is a first type of chip selected from a plurality of types of chips located at the semiconductor farm is allocated to the virtual control engine based on a type of the control logic to be executed ([0024] For example, a client may choose a virtual GPU class from a predefined set of virtual GPU classes. As another example, a client may specify the desired resources of a virtual GPU class, and the instance type selection functionality 120 may select a virtual GPU class based on such a specification [0025] Therefore, using the instance type selection functionality 120, clients (e.g., using client devices 180A-180N) may specify requirements for virtual compute instances and virtual GPUs. The instance provisioning functionality 130 may provision virtual compute instances with attached virtual GPUs based on the specified requirements (including any specified instance types and virtual GPU classes).), the first type of chip being artificial-intelligence-adapted hardware and allocated to the virtualized control engine based on the control logic comprising artificial intelligence control logic ([0057] As another example, the virtual GPU 151B of class “B” may be accessible using one API such as a version of OpenGL, while the virtual GPU 151N of class “N” may be accessible using another API such as a version of Direct3D. As yet another example, the virtual GPU 151B of class “B” may be implemented using a physical GPU that has a particular hardware feature or capability associated with a particular GPU vendor, while the virtual GPU 151N of class “N” may lack such a hardware feature or capability. Examiner notes, Zhoa teaches as evidences, features of Featonby may be features related to machine learning and therefore would be obvious to one of ordinarily skilled in the art, features of Featonby include artificial intelligence [0027] According to embodiments of the present disclosure, the dynamic optimizer and compiler 120 may obtain hardware information of these dedicated processing resources before assigning tasks to respective dedicated processing resources, and allocate corresponding kernel codes according to respective hardware information, so as to implement dynamic optimization for heterogeneous dedicated processing resources. For example, it is possible to assign more tasks to a better-performing GPU or assign a specific type of task to a new GPU that supports a certain feature. Furthermore, embodiments of the present disclosure may be implemented as a plug-in in an existing framework (e.g., TensorFlow XLA, TVM or nGraph). In addition, for hybrid scenarios with different types of accelerator devices, embodiments of the present disclosure can more sufficiently use hardware capabilities of various accelerators. [0032] At 206, a first task is assigned to a first dedicated processing resource, and a second task is assigned to a second dedicated processing resource. The subtasks (such as kernel code) compiled at the dynamic optimizer and compiler 120 are respectively assigned to corresponding GPUs for respective execution on the respective GPUs. Therefore, according to method 200 of embodiments of the present disclosure, corresponding execution tasks are generated according to different hardware capabilities, for the task scheduling in a heterogeneous dedicated processing resource scenario. Thus, a dynamic optimization algorithm can be implemented to match the capacity of hardware, thereby improving the rate of resource utilization and execution efficiency. [0026] machine learning)”.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Featonby with the teachings of Krishnan, Zhoa in order to provide a system that teaches details of system configuration. The motivation for Featonby teaching with Krishnan teaching is to provide a system that allows for design choice of utilizing different resources. Krishnan, Zhoa, Featonby are analogous art directed towards distributed environments. Together Krishnan, Zhoa, Featonby teach every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of invention, one of ordinary skill could have applied the teachings of Featonby with the teachings of Krishnan, Zhoa by known methods before the effective filing date of the claimed invention and gained expected results.
Claim 21, the combination teaches the claim, wherein Featonby teaches “the field controller of Claim 17, further comprising an additional chip at the semiconductor farm, the additional chip being a second type of chip of the plurality of types of chips, the additional chip allocated to the virtual control engine based on the control logic further comprising a different type of control logic compared to the artificial intelligence control logic ([0082] As shown in 1120, a physical GPU resource may be selected based (at least in part) on its characteristics and also based (at least in part) on the GPU requirements for the application. For example, a physical GPU resource may be selected that meets or exceeds any minimum performance requirements associated with the application, has one or more hardware features associated with a particular vendor, is accessible using a particular API (e.g., OpenGL, Direct3D, Vulkan, OpenCL, and so on), and/or has other minimum characteristics indicated in the GPU requirements. The selected physical GPU resource may be associated with one of several virtual GPU classes offered in the provider network. The virtual GPU classes may be characterized by their differing computational resources for graphics processing, memory resources for graphics processing, and/or other suitable descriptive characteristics. Examiner notes, as evidence by Zhoa that a feature of a GPU may include specific resources for machine learning. Therefore, it would be obvious to one of ordinarily skilled in the art, resources may be selected based upon the incoming job.)”.
Claim/s 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan, Zhoa, Featonby in further view of Jebbar (Pub. No US 2023/0325303).
Claim 18, the combination teaches the claim, wherein Krishnan teaches “the field controller of Claim 17, wherein the building equipment and the semiconductor farm communicate via at least one of a plurality of types of communications channels uses a host identity protocol and an overlay network ([0039] In some cases, each of the edge controllers 20 may be operably coupled with a gateway 22. Each of the edge controllers 20 may be coupled with the gateway 22 via wired or wireless connections. [0051] An IP router 90 generates a Local Area Network (LAN1) labeled as 92. The LAN1 labeled as 92 permits communication with at least some of the virtual machines or servers 74, as well as permitting communication with the Docker Image Repository 72 over a Wide Area Network (WAN) 93. The Internet is an example of a WAN such as the WAN 93. An IP Router with WiFi 94 generates a WiFi network 96, a LAN3 labeled as 95, which permits communication between the IP router 90 and the IP Router with WiFi 94, and a LAN2 labeled as 98. The system 70 also includes a Smart I/O device 100, a Smart Sensor Bundle 102, a Smart Actuator 104 and a Smart Command Display 106, as examples of possible edge controllers/building control devices. It will be appreciated that multiple LANs are illustrated in order to show that each component may exist on a different routable network. In some cases, all of the components may be on a single LAN, or on fewer or more networks.). Examiner notes, Jebbar teaches as evidence a virtual network of Ozadowicz is an overlay network and therefore it would be obvious to one ordinarily skilled in the art, Ozadowicz teaches an overlay network [0111] A virtual network can be implemented as an overlay network (sometimes referred to as a network virtualization overlay) that provides network services (e.g., layer 2 (L2, data link layer) and/or layer 3 (L3, network layer) services) over an underlay network (e.g., an L3 network, such as an Internet Protocol (IP) network that uses tunnels (e.g., generic routing encapsulation (GRE), layer 2 tunneling protocol (L2TP), IPSec) to create the overlay network)”.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Jebbar with the teachings of Krishnan, Zhoa, Featonby in order to provide a system that teaches networking resources. The motivation for applying Jebbar teaching with Krishnan, Zhoa, Featonby teaching is to provide a system that allows for network communication. Krishnan, Zhoa, Featonby, Jebbar are analogous art directed towards distributed environments. Together Krishnan, Zhoa, Featonby, Jebbar teaches every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of invention, one of ordinary skill could have applied the teachings of Jebbar with the teachings of Krishnan, Zhoa, Featonby by known methods before the effective filing date of the claimed invention and gained expected results.
Claim 19, the combination teaches the claim, wherein Krishnan teaches “the field controller of Claim 17, wherein the communications interface communicates with the semiconductor farm via both a wired channel of the plurality of communications modalities and a wireless channel of the plurality of communications modalities, the wired channel independent of the wireless (([0039] In some cases, each of the edge controllers 20 may be operably coupled with a gateway 22. Each of the edge controllers 20 may be coupled with the gateway 22 via wired or wireless connections.)”.
Claim/s 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan, Zhoa, Featonby in further view of Gadalin (Pat. No. US 12,236,254).
Claim 20, the combination may not explicitly teach the limitation.
Gadalin teaches “the field controller of Claim 17, wherein the virtualized control engine is configured to be selectively provided using artificial-intelligence-adapted hardware of the semiconductor farm responsive to selection of an artificial intelligence feature for the virtualized control engine ([Col. 3, Lines 31-59] The service provider network may support a wide variety of workloads, such as web servers, databases, customer-facing applications, distributed data stores, batch processing, machine/deep learning training and/or inference, online gaming, video encoding, memory caching, and/or any other type of workload that can be supported by computing resources of a service provider network. In light of the different workloads that are supported on behalf of users, the service provider network may provide users with a selection of a variety of VM instance types optimized to support different workloads. Generally, each VM instance type may be allocated a different amount of computing resources, and/or different combination of computing resources, such that the VM instance types are optimized to support different workloads. As used herein, computing resources refers to compute, memory, storage, networking, and, in some implementations, graphics processing, or other types of specialized processing. As an example, one VM instance type may be allocated a larger amount of compute (e.g., processor cycles) and be optimized to support compute-heavy workloads, whereas another VM instance type may be allocated a larger amount of storage (e.g., disk space) and be optimized to support storage-intensive workloads. In this way, users can select a VM instance type or platform that is more optimized to support their workload, thereby increasing the performance of the workload while reducing underutilization of computing resources by the service provider network.)”.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the teachings of Gadalin with the teachings of Krishnan, Zhoa, Featonby in order to provide a system that teaches details of selecting features. The motivation for applying Gadalin teaching with Krishnan, Zhoa, Featonby teaching is to provide a system that allows for design choice. Krishnan, Zhoa, Featonby, Gadalin are analogous art directed towards distributed environments. Together Krishnan, Zhoa, Featonby, Gadalin teaches every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of invention, one of ordinary skill could have applied the teachings of Gadalin with the teachings of Krishnan, Zhoa, Featonby by known methods before the effective filing date of the claimed invention and gained expected results.
Conclusion
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/WYNUEL S AQUINO/Primary Examiner, Art Unit 2199
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