Embodiments described generally herein relate to processing of data packets sent or received through a network. Some embodiments relate to hardware acceleration of data packet processing.
Hardware switches when combined with specialized hardware functions provide network capabilities including packet switching, security, deep packet inspection, and other capabilities. Recently, there has been a trend in providing virtual switches and virtual functions executing on high-volume computer architectures. The industry has ongoing efforts focused on improving the coordination between the virtual switches for purposes of optimally taking advantage of the throughput benefits, provided by hardware switches along with the flexibility and power of virtual switches.
In the drawings, which are not necessarily drawn to scale, like numerals may describe similar components in different views. Like numerals having different letter suffixes may represent different instances of similar components. The drawings illustrate generally, by way of example, but not by way of limitation, various embodiments discussed in the present document.
Some network packet processing solutions have focused on hardware the use top-of-rack (ToR) switches and special function hardware to provide network functions including packet switching, security, deep packet inspection, and other functions. However, customers may experience reduced functionality caused by hardware limitations such as limited memory, limited Ternary Content-Addressable Memory (TCAM), reduced total number of supported data flows, etc. Furthermore, hardware switches may be overly rigid with respect to packet parsing, and hardware switches can exhibit a general lack of platform flexibility and configurability.
Therefore, the industry trend has been to provide software-defined networking (SDN) for decoupling network functions from underlying hardware, which can help increase agility and lower costs. Similarly, network function virtualization (NFV) can replace fixed-function hardware with implementations fully deployed in software that runs more cost-effectively on general purpose, standards-based servers, high-volume servers, and the like. However, such software-defined systems may not take advantage of some desirable characteristics of hardware switches.
These software-based solutions include a variety of software-based abstractions to the underlying physical architectures. For example, a virtual switch permits one or more Virtual Machines (VMs) to communicate with one another. A Virtual Network Function (VNF) may include one or more VMs (running different Operating Systems (OSs)) executing on one or more high volume hardware server architectures, hardware switches, hardware storage, and/or cloud infrastructures. VNFs process to provide specialized network processing in place of customized network appliances.
A variety of Application Programming Interfaces (APIs) and software platforms exist in the industry for permitting network automation utilizing virtual switches. A significant benefit of these approaches is the ability to define and customize packet processing rules and corresponding actions at the user-level of the Operating System (OS). One problem with these approaches is the underutilization of the underlying physical hardware switch, because a significant amount of rule matching and action identification for packet processing takes place within the kernel space of the OS and not on the underlying hardware switch, which has substantially better processing throughput.
One approach, associated with better utilization of the underlying switch architecture, is Single Root Input/Output (I/O) Virtualization (SR-IOV). With SR-IOV, an interface is provided that allows a device adapter to separate hardware resources among packet processing functions. However, this is a binary approach where the feature is: on or off. Moreover, SR-IOV activation alters the architecture's configuration and management. Consequently, SR-IOV is a packet processing “offload” solution, rather than a packet acceleration solution.
Embodiments provide a way to accelerate existing virtual switch solutions to better utilize the underlying physical switch hardware without changing or modifying how the existing virtual switch solutions interact with upper layers of device management and configuration.
Packet processing coordinates and manages, in a fine-grained fashion, multiple data plane components to utilize desirable features of both hardware switching and SDN/NFV usages. Control plane components include mechanisms to determine where traffic (e.g., data packets or flows) should be directed, while data plane components include mechanisms that forward traffic to those destinations. Embodiments provide control plane methods, systems, and devices to accelerate packet processing for multiple data plane components. Data plane components can include, by way of non-limiting example, Data Plane Development Kit (DPDK) components, field programmable gate array (FPGA) components, and Red Rock Canyon (RRC)/FM10K switch components available from Intel of Santa Clara, California, among other components. Methods in accordance with various embodiments can coordinate utilization of these and other components in a dynamic and flexible fashion based on user-defined and user-configured actions to reduce or minimize energy consumption or to enhance speed and performance. In embodiments, a control plane can offload a simple fast packet-processing pipeline from software-based switches or virtual switches to switch hardware, while providing for more-complicated processing on the CPU-based software data plane.
The system 100 implements techniques having enhanced match-action acceleration in existing software-based packet processing pipelines (series of packet processing stages) for optimized increased bandwidth, lower latency and jitter, and lower Central Processing Unit (CPU) consumption. Match-action processing refers to a mechanism by which the system 100 enables packet processing acceleration. Match-action resources found in the system 100 execute this acceleration. Existing software-based control planes 101 and 102 (such as OpenStack, OpenDaylight, etc.) do not need modification in order to realize the acceleration presented herein. In addition, existing virtualization constructs (providing virtualized environment management), such as Virtio 113 and 133 do not need modified to use the architecture underlying the system 100, which include the optimizations for packet acceleration.
There are no additional interfaces or control planes, which a user is, required to learn in order to realize the optimizations presented herein with respect to accelerated packet processing/communication between devices (such as VMs managed by VNFs 110, 120, and 130).
Specifically, a Network Interface Controller (NIC) provides one or more novel physical functions (PF 141) and one or more virtual functions (VFs 142 and 143). These functions 141-143 respond to one or more novel match-action (e.g., P4) tables and cooperate with existing control planes 101 and 102 and their existing API commands for executing enhanced network packet processing between VNFs (110, 120, and 130) by offloading software-based match-action network packet processing to the underlying switch architecture of the NIC 140. The processing occurs below the operating system (OS) kernel stack 115 on the NIC 140 within TCAM, the PFs 141, and/or the VFs 142 and 143.
The functions 141-143 provide: 1) virtual switch (vSwitch) acceleration 118, 2) vSwitch offloading 126, 3) VNF acceleration 124, and 4) vitrio (virtualization (VM)) acceleration 135.
It is to be noted that although the system 100 depicts functions 141-143 supporting the four types of acceleration (118, 124, 126, and 135); this does not have to be the case in every instance. That is, in other embodiments, the NIC can implement one and/or configured for supporting, all, or various combinations of the four types of acceleration (118, 124, 126, and 135).
The functions (141, 142, and 143) and the supported four types of network packet acceleration (118, 124, 126, and 135) through match-action processing is as follows (with reference to the system 100 of the
It is noted that the VNF 110 is programmed for processing (on the underlying hardware of the system 100) a variety of software, such as and by way of example, a network application 111 (performing one or more specialized network packet processing operations), a Data Plan Development Kit 122 (DPDK 122) API, and a virtualization service (virtio 113). The VNF 120 includes a network application 121, a DPDK API option 122, and a NIC VF Driver 123. The VNF 130 includes a network application 131, a DPDK API option 132, and a virtualization service (virtio 133).
The VNFs 110, 120, and 130 situated above the vSwitch 114. The vSwitch 114 situated above the kernel stack 115. Access by the vSwitch for matching and accessing the PF 141 over link 117. Access for accessing VF 142 by the NIC VF driver 123 of VNF 120 over link 125 (for direct TLV lookups through VF 142). Access for the VF 143 by the virtio instance 133 of VNF 130 over links 134 and 137 through 136 for virtio TLV driven lookups 134 and match TLV lookups 137 directly through the VF 143.
By employing metadata generated in response to a match action table (e.g., P4 file(s)), acceleration of the packet-processing pipeline for the vSwitch 114 occurs.
A P4 file describes capabilities of the match-action pipeline. In an embodiment, the structure of the match-action table is a P4 file (defined by p4.org open source programming language and formats) is: [Parser]-[Ingress Quality of Service (QoS)]-[Filtering]-[Tunnel/Network Address Translation (NAT)]-[Replication]-[Egress QoS]
In an embodiment, the parser is in P4 format as well. This also provides frame formats (packet payload formats) for matching.
Additionally, P4 provides the mechanism for defining the match filed. A non-limiting set of files can appear as follows:
The parse tree also recognizes a format for inner header tunnel-encapsulated frames:
P4 also provides a mechanism for specifying the supported actions, as well as which tables support which actions. A non-limiting example set of actions can be as follows:
vSwitch Acceleration Using Metadata
The host Ethernet controller (e.g., NIC 140) processes received-received frames first on system 100, and then the host Ethernet controller passes the processed frames up into the various software layers of the system 100 for further additional processing. On the receive path, the Ethernet controller can pre-process the frames and associate with the frame additional metadata. The semantics of this pre-processing are match-action based. The following examples illustrate the processing by which the vSwitch 114 (such as Open vSwitch (OvS) 114) pipeline processing accelerates with embodiments presented herein.
TCAM Pre-Classify
The host controller pushes received packet frames into the TCAM in the pipeline. The vSwitch 114 programs a set of matching rules into the TCAM (using and existing API of the vSwitch 114, such as an API associated with OvS). This causes some amount of metadata being set that include the result of the TCAM lookup. The PF 141, upon matching, appends the result (extra metadata and either in an encapsulating VLAN or a soft_id_value) within the received frame. The software pipeline uses that result in the metadata embedded in the received frame and can avoid having to achieve this TCAM lookup within the software pipeline.
In an embodiment and in the case of OvS (114), an enhanced-patch to OvS 114 detects this added metadata in the packet. If the metadata does not exist in the packet header in the packet header, the OvS 114 pursues its normal processing path. However, the OvS 114 skips 117 its typical software-based TCAM lookup processing within its pipeline when the metadata exists in the packet header (an indication that the PF 141 previously appended the TCAM look results within the NIC 140 before the OvS 114 processes the packet).
Tunnel Decapsulation
The host controller 140 receives a frame, the vSwitch 114 programs rules that map outer VXLAN, VXLAN-Generic-Protocol-Extension (GPE)+NSH, Generic Network Virtualization Encapsulation (Geneve), or Network Virtualization using Generic Routing Extension (NVGRE) headers into the metadata. In an embodiment, The PF 141 processes these rules for: 1) matching the rules on outer header (L2, L3, VNI, and Service Header); 2) decapsulates the matched outer header, and 3) and adds some additional metadata for signaling the removed header. The pipeline processing detects the removed outer header and processes the inner header accordingly.
In the case of OvS 114 (vSwitch 114), the PF 141 uses the decapsulation processing in conjunction with TCAM pre-classify processing for providing metadata on the outer header as well as metadata on the rules matched in the TCAM. When used in conjunction, the TCAM pre-classify rules apply to the inner header.
vSwitch Tap
Tapping an interface can be used for monitoring packet processing by copying some or all of the frames (associated with the interface) and sending the frames to a different location. This unduly taxes the software and hardware resources of the system 100 and is intrusive to the vSwitch 114 processing. Therefore, the teachings presented herein are particularly beneficial in such a scenario. The system 100 achieves this copying using a match rule that maps in the match-action table to a mirror action, which the functions (141-143) process within the NIC 140.
In an embodiment, the vSwitch 114 sends the frames and then processes for multicast replication, tunnel encapsulation, and monitoring in the accelerated pipeline occurs after the frames occurs. In this manner, performance of packet acceleration takes place during transmit of the packets.
vSwitch offload 126 is an extension of vSwitch acceleration 118 when the following conditions are true of a given set of traffic (network packets being processed through the system 100):
1) the accelerated pipeline has a direct connection 125 to the VM (associated with the traffic managed within VNF 120); and
2) the accelerated pipeline has the capability to fully process the traffic with all of the same rules (which the vSwitch 114 data plane processes).
Although identified as an “offload,” the rules within the vSwitch 114 never leave the vSwitch 114; here, the processing pushes and copies the rules into the accelerated pipeline, and pushes statistics for these rules back to the vSwitch 114 so that the rules stay in the software tables. A common configuration where vSwitch offload 126 can occur is when using OvS 114 to implement rules. The rules are applied by a separate control plane software layer; for example, OpenStack and OpenDaylight (e.g., Third Party APIs 101 and 102). The control flow is as follows:
1) A tunnel manager enumerates the virtual switches (multiple instances of vSwitch 114 not shown in the
2) When two VMs/containers want to connect to one another (from the VNFs 110-130), population of the forwarding rules to the VMs/containers respective vSwitches occurs. Certain systems will populate these rules via virtual L2 learning; other systems will provision the rules directly from a centralized controller.
In addition to tunnel rules (as discussed above), a vSwitch 114 can implement Access Control Lists (ACLs), service function classification, service function forwarding, basic ingress QoS, and connection tracking.
In both vSwitch acceleration 118 and vSwitch offload 126, the vSwitch 114 is executing in the host system 100 and has full control of the underlying device associated with the system 100 for acceleration processing. Here, the connecting VM/container does not have any control over any sort of acceleration “from the network.” The VM/container does not have any control over what happens inside the vSwitch 114. The VNF 120 uses the same semantics as the vSwitch 114 does for: discovering which tables are available, how many entries are available in each table, and what match-action rules for application. However, restriction of the VNF 120 occurs in the following manners:
1) The host system 100 trusts the VNF 120 for enabling the acceleration (otherwise, the host system 100 cannot honor requests from the VNF 120).
2) Application or the VNF's rules occur on traffic sent to or received from that VNF 120. Therefore, the focus in VNF acceleration 124 is on grooming traffic before sending that traffic to the VNF 120. Thus, the VNF 120 cannot add rules to affect traffic going to/from other VFs (such as VF 143), other PFs 141, or the physical uplink ports.
3) The VNF 120 does not have visibility beyond its own interface. Therefore, the VNF 120 cannot add rules affecting traffic going to/from other VNFs (110 and/or 130), PFs 141, VFs 141 and 143, or physical uplink ports.
4) The VNF 120 may not have the same sets of actions available to it. That is, the VNF functions are generally limited to functions related to the VNF 120, such as ACLs (drops, counts, and policing), steering packets to queues, prioritizing packets into queues, and marking packets with metadata for pre-processing.
In an embodiment, the VNF 120 has multiple queues associated with that VNF 120. The VNF 120 is programmed (using for example Data Plan Development Kit 122 (DPDK 122) API) in the following manner:
1) Configure a default Receive Site Scaling (RSS) rule to spread traffic across multiple queues. Here, the VNF 120 can associate a CPU core for each queue to scale the packet processing across multiple flows.
2) Configure a set of FlowDirector® (Intel® packet steering product) rules that work as exceptions to the RSS default-spreading rule, which places specific flow types and mega flows into specific flows or given specific priorities. When RSS cannot efficiently spread with RSS, the configuration of the FlowDirector® aids in handling that traffic. The configuration of the FlowDirector® also aids in handling high priority traffic.
3) Configure a set of filtering rules to drop or police traffic. This can protect the VNF 120 from unwanted traffic, or from receiving traffic at too high a rate.
4) In a manner similar to vSwitch acceleration 118, the VNF 120 can also associate a 16-bit software identifier (ID) on flows, based on match-action rules. This can accelerate certain forwarding paths within the VNF 120 (such as TCAM processing).
Virtio acceleration 135 is a variant of vSwitch offload 126 still requiring that the hardware of the system 100 be capable of fully forwarding and performing packet processing the frame, but there is no direct connection between the VNF 130/VM and the underlying hardware (134 and 137). Instead, the VNF 130 connects (via software) with a virtio driver 136. In this scenario, there is a software loop (this may be OvS with the DPDK netdev, or some other entity that is copying frames to/from the VF 143 and the virtio queues within the VF 130/VM. A presented scenario implementing OvS with the DPDK netdev is as follows.
Discussion of the virtio acceleration provided with reference to the
Although embodiments of
Again, system 200 illustrates a number of VNFs (210, 220, and 230) each having a network application (211, 221, and 231), DPDK option APIs (212, 222, and 232), and an instance of virtio (virtualization management services—213, 223, and 233). Each virtio instance (214, 223, and 233) connected to a corresponding vHost (241, 242, and 243) having the ability for virtio TLV lookups via 214, 224, and 234.
The vHosts (241, 242, and 245) situated in the OS with a vSwitch 240 and service provided by DPDK 244. The kernel stack 250 situated in the OS under the vSwitch 240 and the DPDK 244. The kernel stack 250 having direct access to the PF 261 and the DPDK 244 and vSwitch 240 having direct access to the VFs 262-265. Match TLVs lookup configurations occur over 266-268. Link 251 providing operations offloaded to the PF 261. The PF 261 and the VFs 262-265 part of the NIC 260.
Underneath OvS, instantiation of N (number of) DPDK netdevs (Linux virtual unction netdevs-functions for obtaining state and capabilities) occurs. Each netdev corresponds to a VF (such as VFs 261 and 262) within the hardware. The arrangement of ports underneath OvS then appears as follows:
1) PFs accelerated ports attached as regular non-DPDK to the OvS kernel data path. Using these interfaces, when a flow requires processing by the kernel (requires TCP, IP tables, etc.).
2) Default Rule VF(s): between 0 and 4 VFs, hardware accessible for sending frames (which are incapable of forwarded a packet processed) to the DPDK user space pipeline for processing. These VFs (such as VFs 142 and 143) have a similar function as the PF 141 ports, except that the packet processing data plane is in the DPDK (with higher performance but without kernel stacks).
3) Virtio Alias VFs: remaining VFs (142 or 143 or 261-265 of
When attachment of a new VNF 130/VM to the OvS occurs, allocation of this VF 130 occurs as a virtio alias VF. When this happens, the OvS with the DPDK netdev enables a set of “Hardware Offload Virtual (HOV)” paths between its virtual Host (vHost) implementation and the virtio alias VF. Installation of the software logic is as follows:
1) If all of the rules pertaining to the packets coming FROM this VNF 130/VM has been put into the hardware, then zero-copy directly from the vHost into the corresponding virtio alias VF.
2) Else if a partial set of rules pertaining to the packets coming FROM this VF 130/VM has been put into the hardware, process this frame through the OvS user-space pipeline, and when finished push the frame into the corresponding virtio alias VF.
3) Else pass the packet through the OvS packet-processing pipeline. The packet can be sent into the network either via the PF netdevs (the frames are directly forwarded out of a port), via the DPDK VF 130 (in which case the transmitting uplink chosen by the hardware that uses the embedded switch beneath it, or pushed into the kernel for processing via Kernel NIC Interface (KNIC).
4) In the other direction, all received packets on the virtio alias VFs are sent directly from the hardware into the software virtio queues (via vHost) on the HOV path (in an embodiment, a third-party application may provide a zero-copy implementation for doing this).
In the hardware, plumbing of the reverse path occurs and the processing looks similar:
1) If application of all of the rules pertaining to the packets coming TO this VF 130/VM occurred, then forwarding the frame to the VF 130 corresponding to this VM. The PMD picks up this frame and pushes the frame to the VM over the HOV path.
2) If application of a partial set of rules pertaining to this packet occurred, or if this packet misses in the hardware tables, forward the frame to the default rule VF for handling. These frames picked up by the PMD and processed in the DPDK user-space pipeline.
3) Optionally, specific flows needing kernel processing trapped to the PF 141 for standard kernel processing.
When programming the hardware, rules that split traffic between virtio alias, default user space, and kernel data paths preserve conversational ordering. That is one rule does not forward a particular 5-tuple (Destination IP, Source IP, L4-Destination, L4-Source, Protocol) via one path and then forward another frame with the same 5-tuple through another path.
The inverse processing used on the software side: the vHost arbitrates between frames coming directly from the virtio alias, DPDK user-space and kernel data paths. As these are already in conversational order, just process a scheduling function. The virtio alias has highest processing priority, followed by the DPDK user-space and then kernel path.
In this scenario, a VNF 130 may request acceleration by sending Tag-Length-Values (TLVs) via virtio. If this VNF 130 has an aliased VF, these TLVs converted into VNF acceleration requests over a VF mailbox. For this reason and in an embodiment, a configuration provides support for multi-queue virtio, since this allows the VNF 130 to enable RSS and FlowDirector® to spread traffic to multiple queues within the VM. For VNFs using multiple cores, this allows the hardware to spread traffic to multiple cores appearing the connection between VNF 130 and the VF 130 is a direct connection.
In a scenario in which the DPDK or kernel data paths completely process the traffic, the processing through system 100 occurs in two manners:
1) In-line: The first data path to process the frame (hardware packets from the network, software for packets from the vHost) can minimally process the frame and send it to the primary data plane (user space, kernel, or hardware). This is a very efficient mechanism for choosing between data paths, as it does not “bounce-back” frames between data paths, but it does necessitate some amount of processing by the first data path, which may be redundant or overhead on top of the primary data path doing the processing.
2) Bounce-Back: In this scenario software “fastpaths” frames into the hardware, which then loopbacks frames back to the DPDK or the kernel if it cannot handle the frame itself. This has a lower amount of software overhead, but utilizes extra Peripheral Component Internet express (PCIe) bandwidth when frames bounced-back from the hardware back into the software.
In an embodiment, the above-mentioned techniques implemented as methods, an apparatus, and a system for computing-device architectures for achieving accelerated inter-device communication or operations (such as inter-VM communication on-chip for a single device architecture). This provides acceleration for one, all, or combinations of: 1) vSwitch acceleration using metadata, 2) offloaded vSwitch for Virtio connected VMs, 3) offloaded vSwitch for NSH service chaining, and/or 4) Multi-Layer Traffic Pre-Classify (VNF acceleration and NSH service chaining.
These and other embodiments of accelerated inter-device communication presented below with reference to the
In an embodiment, the control device 300 is a NIC.
In an embodiment, the control device 300 is the NIC 140 of the
In an embodiment, the control device 300 is the NIC 260 of the
In an embodiment, the control device 300 integrated within and/or interfaced to a multi-core processor. In an embodiment, the multicore processor is a server.
In an embodiment, the control device 300 operates within multiple heterogeneous and virtualized processing environments having a variety of VMs, operating systems, etc.
The control device 300 includes processor 302 to perform functionalities as described herein. It will be understood that any or all of the functions performed by processor 302 can be executed with hardware, software, firmware, or any combination thereof, on one or more processing cores, for example Intel® Architecture cores 114 or a core of the control device 300.
In an embodiment, the processor 302 performs the processing described above with respect to the PF 141 and the VFs 142 and 143 of the
In an embodiment, the processor 302 performs the processing described above with respect to the PF 261 and the VFs 262-265.
In embodiments, the processor 302 can match an action referenced from a table to a portion of data in a network packet. The processor 302.
In an embodiment, the processor 302 is at least partial programmed by an Application Programming Interface (API). In an embodiment, the API provided in formats supported by one or more of: DPDK, OvS, OpenDaylight, and OpenStack.
In an embodiment, the processor 302 is programmed to be responsive to one or more tables or files that identify actions that the processor 302 is responsive to for purposes of performing predefined processing based on a particular identified action.
In an embodiment, a user interface permits a user to access the API for populating the table or file with actions.
In an embodiment, the file or table is the match-action files discussed above with reference to the
The processor 302 can match an action reference from a file/table to a portion of a packet header for a received network packet. The processor 302 processes the action identified by the action reference in cooperation with the memory 301 to accelerate a packet-processing pipeline for the network packet.
In an embodiment, the memory 301 is Random Access Memory (RAM) on the control device 300.
Processing the action does not have to be a single operation; rather, the action can trigger the processor 302 to perform a series of predefined operations.
In an embodiment, the processor 302 when processing the action performs a Ternary CAM lookup on some of the packet data. This was discussed above in the
In an embodiment, the processor 302 when processing the actions decapsulates an outer tunnel encapsulated header for the network packet, removes that header, and adds metadata into the header indicating that the header was removed. This processing discussed above with reference to the
In an embodiment, the processor 302 when processing the actions copies a packet payload (frame) from the network packet and then sends that copied payload to a network location, which is independent of network locations, defined within or identify resources for processing the packet-processing pipeline. This scenario describes network traffic mirror and monitor operations having substantial improvements in processing throughput since resolution, processing, and sending for mirror packets occur on the control device 300 and not at upper layers within the network architecture, such as the OS layer for a specific VM, and the like.
In an embodiment, the processor 302 when processing the action copies the network packet forwarding rules from a first virtual switch to a second virtual switch. This scenario discussed above with reference to vSwitch offload acceleration and the discussion of the
The processor 302 configured to communicate with the underlying switch silicon 310 through a switch interface 304.
In an embodiment, the executable instructions representing the packet accelerator is stored in a non-transitory computer-readable storage medium that when executed by one or more computing devices performs the method 400 processing.
In an embodiment, the packet accelerator configured for execution as firmware on a NIC. In an embodiment, the packet accelerator is the PF 141 of the
In an embodiment, the packet accelerator configured for execution within one or more virtual switches, one or more physical switches, one or more device interfaces, one or more virtual device interfaces, and/or one or more operating systems.
In an embodiment, the packet accelerator configured for execution within one or more independent and virtualized environments (execution on system 100 and/or system 200 of the
In an embodiment, the packet accelerator configured for execution as the control device 300 of the
At 410, the packet accelerator matches a portion of a network data packet to an action in a match-action table. For example, the processing and file structures of match-action files and matching to network packets discussed in the
At 420, the packet accelerator accelerates processing of the network packet through the machine by executing the action as part of a packet-processing pipeline for the network data packet. That is, action processing accelerates packet processing in a number of manners that can include processing for: 1) offloading processing of software-based resources to hardware-based resources; 2) reorganizing processing of the software-based resources; and/or 3) reorganizing how the software-based resources access the hardware-based resources.
According to an embodiment, at 421, the packet accelerator inserts metadata into the network data packet as an indication that a portion of the packet processing has been handled/processed when the action processed. For example, the pre-classify processing and the TCAM processing presented above in the
In an embodiment, at 422, the packet accelerator copies a packet frame for the network data packet and sends the copied packet frame to a location that is independent of locations associated with the packet-processing pipeline. This is a packet mirroring processing situation discussed above with reference to the
In an embodiment, at 423, the packet accelerator assigns the network data packet to a queue associated with a specific processing core. This may entail other configuration dependencies and processing presented above with the discussion of the virtio acceleration processing of the
In an embodiment of 423 and at 424, the packet accelerator filters the network packet responsive to filtering rules.
In an embodiment of 424 and at 425, the packet accelerator sets a resource identifier on the network data packet that identifies a resource for processing against the network data packet when processing the network data packet through the packet-processing pipeline. So, tables, metadata, and/or the packet-processing pipeline control structures providing a mechanism by which different heterogeneous software and/or hardware resources that assist in accelerating the network data packet through the packet-processing pipeline (network/device(s)), and these mechanisms identified as a resource identifier for the network data packet. The packet accelerator configured for identifying the resource identifier and causing the corresponding resource to process for accelerating the pipeline processing of the packet through the network/device(s).
In an embodiment, at 426, the packet accelerator performs a variety of alternative processing depending on whether traffic rules are fully offloaded to hardware or other conditions. Such conditions discussed with reference to the virtio acceleration of the
Examples, as described herein, may include, or may operate on, logic or a number of components, modules, or mechanisms. Modules are tangible entities (e.g., hardware) capable of performing specified operations and may be configured or arranged in a certain manner. In an example, circuits may be arranged (e.g., internally or with respect to external entities such as other circuits) in a specified manner as a module. In an example, at least a part of one or more computer systems (e.g., a standalone, client or server computer system) or one or more processors of the control device 300 may be configured by firmware or software (e.g., instructions 303 (
The term “module” is understood to encompass a tangible entity, be that an entity that is physically constructed, specifically configured (e.g., hardwired), or temporarily (e.g., transitorily) configured (e.g., programmed) to operate in a specified manner or to perform at least part of any operation described herein. Considering examples in which modules are temporarily configured, a module need not be instantiated at any one moment in time. For example, where the modules comprise a general-purpose hardware processor configured using software; the general-purpose hardware processor may be configured as respective different modules at different times. Software may accordingly configure a hardware processor, for example, to constitute a particular module at one instance of time and to constitute a different module at a different instance of time. The terms “application, process, or service,” or variants thereof, is used expansively herein to include routines, program modules, programs, components, and the like, and may be implemented on various system configurations, including single-processor or multiprocessor systems, microprocessor-based electronics, single-core or multi-core systems, combinations thereof, and the like. Thus, the terms “application, process, or service” may be used to refer to an embodiment of software or to hardware arranged to perform at least part of any operation described herein.
While a machine-readable medium may include a single medium, the term “machine-readable medium” may include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers).
The term “machine-readable medium” may include any medium that is capable of storing, encoding, or carrying instructions 303 for execution by a machine (e.g., the control device 300 or any other module) and that cause the machine to perform any one or more of the techniques of the present disclosure, or that is capable of storing, encoding or carrying data structures used by or associated with such instructions. In other words, the processor 302 (
The instructions 303 may further be transmitted or received over a communications network using a transmission medium utilizing any one of a number of transfer protocols (e.g., frame relay, internet protocol (IP), TCP, user datagram protocol (UDP), hypertext transfer protocol (HTTP), etc.). Example communication networks may include a local area network (LAN), a wide area network (WAN), a packet data network (e.g., the Internet), mobile telephone networks ((e.g., channel access methods including Code Division Multiple Access (CDMA), Time-division multiple access (TDMA), Frequency-division multiple access (FDMA), and Orthogonal Frequency Division Multiple Access (OFDMA) and cellular networks such as Global System for Mobile Communications (GSM), Universal Mobile Telecommunications System (UMTS), CDMA 2000 1×* standards and Long Term Evolution (LTE)), Plain Old Telephone (POTS) networks, and wireless data networks (e.g., Institute of Electrical and Electronics Engineers (IEEE) 802 family of standards including IEEE 802.11 standards (WiFi), IEEE 802.16 standards (WiMax®) and others), peer-to-peer (P2P) networks, or other protocols now known or later developed.
The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by hardware processing circuitry, and includes digital or analog communications signals or other intangible medium to facilitate communication of such software.
In an embodiment, the system is a multi-core server 510.
In an embodiment, the multi-core server 510 configured for performing vSwitch acceleration in the manners discussed above with reference to the
In an embodiment, the multi-core server 510 configured for performing vSwitch offload acceleration in the manners discussed above with reference to the
In an embodiment, the multi-core server 510 configured for performing VNF acceleration in the manners discussed above with reference to the
In an embodiment, the multi-core server 510 configured for performing virtio acceleration in the manners discussed above with reference to the
In an embodiment, the multi-core server 510 configured for performing selective network packet acceleration for: vSwitch acceleration, vSwitch offload acceleration, VNF acceleration, and/or virtio acceleration in the manners discussed above with reference to the
The system 500 includes a means for matching a portion of a network packet to an action and a means for processing the action to accelerate a packet-processing pipeline, and, optionally, a means for configuring the means for matching and the means for processing.
The means for matching a portion of a network packet to an action during network-packet processing.
In an embodiment, the means for matching includes a match-action table 521 or file, such as a P4 file as discussed above with reference to the
In an embodiment, the means for matching includes a memory, such as memory 301 of the
In an embodiment, the means for matching includes volatile or non-volatile memory on a NIC, such as NIC 140 or 260 of the
In an embodiment, the means for matching includes volatile or non-volatile memory accessible on one or more devices representing the system 500.
In an embodiment, the means for matching includes a combination of memory and storage accessible on one or more device representing the system 500.
The means for processing configured to process the action (obtained from the means for matching). The action processed to accelerate a packet-processing pipeline (associated with or assigned to) for the network packet.
In an embodiment, the means for processing is one or more of: one or more device driver(s) (interface(s)) 540, one or more virtual interface(s) 540, one or more virtual switch(es) 550, one or more OS kernel processes (560), and/or a NIC with a physical switch 570.
In an embodiment, the means for processing is various combinations of the component devices and modules illustrated in the
In an embodiment, the system 500 includes a means for configuring the means for processing to custom-define (or user-define) the action.
In an embodiment, the means for configuring is the API 520. In an embodiment, the API 520 is a specific configured instance of components illustrated in the
In an embodiment, the means for configuring also provides a means for configuring the means for matching. In an embodiment, the API 520 is the means for configuring and permits tables of files to be established for action in the match-action table/file 521.
Example 1 includes subject matter (such as a control device, interplane control device, control plane processor, computer device and or any other electrical apparatus, device or processor) including a memory and processing circuitry. The processing circuitry configured to match an action reference from a table to a portion of data in a network data packet. The processing circuitry further configured to process an action identified by the action reference in cooperation with the memory that accelerates a packet-processing pipeline for the network data packet.
In Example 2, the subject matter of Example 1 can optionally include wherein when the processing circuitry processes the action, the processing circuitry is further configured to perform a Ternary CAM lookup on the portion of data and insert results from the lookup into the network packet as a pre-classification of the network data packet.
In Example 3, the subject matter of any of Examples 1-2 can optionally include wherein when the processing circuitry processes the action, the processing circuitry is further configured to decapsulate an outer tunnel encapsulated header of the network data packet, remove the tunnel encapsulated header from the network data packet, and add metadata into a header for the network data packet that indicates the tunnel encapsulated header was removed from the network data packet.
In Example 4, the subject matter of any of Examples 1-3 can optionally include wherein when the processing circuitry processes the action, the processing circuitry is further configured to copy a packet payload from the network data packet and send the copied packet payload to a location independent of locations that process the packet processing pipeline.
In Example 5, the subject matter of Examples 1-4 can optionally include wherein when the processing circuitry processes the action, the processing circuitry is further configured to copy data packet forwarding rules from a first virtual switch to a second virtual switch.
In Example 6, the subject matter of any of Examples 1-5 can optionally include wherein the processing circuitry is a physical function integrated into the control device.
In Example 7, the subject matter of any of Examples 1-5 can optionally include wherein the processing circuitry is a virtualized function programmed into the control device.
In Example 8, the subject matter of any of Examples 1-7 can optionally include a data plane interface configured to forward the network data packet to one of: an OS kernel stack, a virtualized switch, and a device driver.
In Example 9, the subject matter of any of Examples 1-8 can optionally include wherein the control device is a network interface controller (NIC).
In Example 10, the subject matter of any of Examples 1-9 can optionally include wherein the control device is interfaced and integrated into a multi-core hardware server.
Example 11 includes subject matter such as a machine-readable medium including instructions that, when executed on a machine (such as a control device, interplane control device, control plane processor, computing device, NIC card, etc.) cause the machine to match a portion of a network data packet to an action in a match action table and accelerate processing of the network data packet through the machine by executing the action as part of a packet processing pipeline for the network data packet.
In Example 12, the subject matter of Example 11 may optionally include wherein the instructions to accelerate further include insert metadata into the network data packet indicating that a portion of the packet-processing pipeline was processed when the action was processed.
In Example 13, the subject matter of any of Examples 11-12 may optionally include wherein the instructions to accelerate further include instructions to copy a packet frame for the network data packet and send the copied packet frame to a location that is independent of locations associated with the packet-processing pipeline.
In Example 14, the subject matter of any of Examples 11-13 may optionally include wherein the instructions to accelerate further include instructions to assign the network data packet to a queue associated with a specific processing core of the machine.
In Example 15, the subject matter of Example 14 may optionally include wherein the instructions to accelerate further include instructions to filter the network data packet responsive to filtering rules.
In Example 16, the subject matter of Example 15 may optionally include wherein the instructions to accelerate further include instructions to set a resource identifier on the network data packet that identifies a resource for processing against the network data packet when processing the network data packet through the packet-processing pipeline.
Example 17 include a system (e.g., a server, computer, set of cooperating computers, etc.) a means for matching a portion of a network packet to an action and a means for processing the action to accelerate a packet-processing pipeline associated with the network packet based on processing the action.
Example 18 includes the subject matter of Example 17, and optionally wherein the network packet is sent from a first Virtual Machine (VM) to a second VM, and each of the VMs executing on a same multi-core server that executes the means for matching and the means for processing.
Example 19 includes subject matter of any of the Examples 16-17, and optionally further including a means for configuring the means for processing to custom-define the action.
In Example 20, the subject matter of any of the Examples 16-17, and optionally includes wherein the means for processing is one of: a virtualized network switch, a hardware switch, a kernel process, a device driver, and a virtualized interface.
The above detailed description includes references to the accompanying drawings, which form a part of the detailed description. The drawings show, by way of illustration, specific embodiments that may be practiced. These embodiments are also referred to herein as “examples.” Such examples may include elements in addition to those shown or described. However, also contemplated are examples that include the elements shown or described. Moreover, also contemplate are examples using any combination or permutation of those elements shown or described (or one or more aspects thereof), either with respect to a particular example (or one or more aspects thereof), or with respect to other examples (or one or more aspects thereof) shown or described herein.
Publications, patents, and patent documents referred to in this document are incorporated by reference herein in their entirety, as though individually incorporated by reference. In the event of inconsistent usages between this document and those documents so incorporated by reference, the usage in the incorporated reference(s) are supplementary to that of this document; for irreconcilable inconsistencies, the usage in this document controls.
In this document, the terms “a” or “an” are used, as is common in patent documents, to include one or more than one, independent of any other instances or usages of “at least one” or “one or more.” In this document, the term “or” is used to refer to a nonexclusive or, such that “A or B” includes “A but not B,” “B but not A,” and “A and B,” unless otherwise indicated. In the appended claims, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Also, in the following claims, the terms “including” and “comprising” are open-ended, that is, a system, device, article, or process that includes elements in addition to those listed after such a term in a claim are still deemed to fall within the scope of that claim. Moreover, in the following claims, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to suggest a numerical order for their objects.
The above description is intended to be illustrative, and not restrictive. For example, the above-described examples (or one or more aspects thereof) may be used in combination with others. Other embodiments may be used, such as by one of ordinary skill in the art upon reviewing the above description. The Abstract is to allow the reader to quickly ascertain the nature of the technical disclosure and is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. Also, in the above Detailed Description, various features may be grouped together to streamline the disclosure. However, the claims may not set forth features disclosed herein because embodiments may include a subset of said features. Further, embodiments may include fewer features than those disclosed in a particular example. Thus, the following claims are hereby incorporated into the Detailed Description, with a claim standing on its own as a separate embodiment. The scope of the embodiments disclosed herein is to be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.
This application is a continuation (and claims the benefit of priority under 35 U.S.C. § 120) of U.S. application Ser. No. 16/460,798, filed Jul. 2, 2019, and entitled ACCELERATED NETWORK PACKET PROCESSING, which application is a continuation (and claims the benefit of priority under 35 U.S.C. § 120) of U.S. application Ser. No. 15/878,966, filed Jan. 24, 2018, and entitled ACCELERATED NETWORK PACKET PROCESSING, which application is a continuation (and claims the benefit of priority under 35 U.S.C. § 120) of U.S. application Ser. No. 14/977,810, filed Dec. 22, 2015 and entitled ACCELERATED NETWORK PACKET PROCESSING. The disclosures of the prior applications are considered part of and are hereby incorporated by reference in their entirety in the disclosure of this application.
Number | Name | Date | Kind |
---|---|---|---|
5243596 | Port et al. | Sep 1993 | A |
5642483 | Topper | Jun 1997 | A |
5784003 | Dahlgren | Jul 1998 | A |
6157955 | Narad et al. | Dec 2000 | A |
6442172 | Wallner et al. | Aug 2002 | B1 |
6453360 | Muller et al. | Sep 2002 | B1 |
6735679 | Herbst et al. | May 2004 | B1 |
6836483 | Lee | Dec 2004 | B1 |
6948099 | Tallam | Sep 2005 | B1 |
6976149 | Brandt et al. | Dec 2005 | B1 |
6980552 | Belz et al. | Dec 2005 | B1 |
7042888 | Berggreen | May 2006 | B2 |
7046685 | Matsuoka et al. | May 2006 | B1 |
7062571 | Dale et al. | Jun 2006 | B1 |
7177276 | Epps et al. | Feb 2007 | B1 |
7203740 | Putzolu et al. | Apr 2007 | B1 |
7389462 | Wang | Jun 2008 | B1 |
7421688 | Righi et al. | Sep 2008 | B1 |
7492714 | Liao et al. | Feb 2009 | B1 |
7499941 | Michaeli et al. | Mar 2009 | B2 |
7539777 | Aitken | May 2009 | B1 |
7633880 | Bang et al. | Dec 2009 | B2 |
7643486 | Belz et al. | Jan 2010 | B2 |
7826470 | Aloni et al. | Nov 2010 | B1 |
7872774 | Okamoto | Jan 2011 | B2 |
7873959 | Zhu et al. | Jan 2011 | B2 |
7889750 | Parker | Feb 2011 | B1 |
7904642 | Gupta et al. | Mar 2011 | B1 |
7961734 | Panwar et al. | Jun 2011 | B2 |
8077611 | Bettink et al. | Dec 2011 | B2 |
8094659 | Arad | Jan 2012 | B1 |
8125810 | Bosshart | Feb 2012 | B2 |
8155135 | Aloni et al. | Apr 2012 | B2 |
8514855 | Robertson et al. | Aug 2013 | B1 |
8527613 | Malone et al. | Sep 2013 | B2 |
8593955 | Yano et al. | Nov 2013 | B2 |
8638793 | Ben-Mayor et al. | Jan 2014 | B1 |
8693374 | Murphy et al. | Apr 2014 | B1 |
8738860 | Griffin et al. | May 2014 | B1 |
8788512 | Asaad et al. | Jul 2014 | B2 |
8798047 | Wadekar et al. | Aug 2014 | B1 |
8971338 | Mishra et al. | Mar 2015 | B2 |
9049153 | Casado et al. | Jun 2015 | B2 |
9049271 | Hobbs et al. | Jun 2015 | B1 |
9055004 | Edsall et al. | Jun 2015 | B2 |
9055114 | Talaski et al. | Jun 2015 | B1 |
9112818 | Arad et al. | Aug 2015 | B1 |
9124644 | Patel et al. | Sep 2015 | B2 |
9213537 | Bandakka et al. | Dec 2015 | B2 |
9258224 | Bosshart et al. | Feb 2016 | B2 |
9276846 | Goyal et al. | Mar 2016 | B2 |
9294386 | Narad | Mar 2016 | B2 |
9298446 | Chang et al. | Mar 2016 | B2 |
9438505 | Zhou et al. | Sep 2016 | B1 |
9450817 | Bahadur et al. | Sep 2016 | B1 |
9467363 | Gao | Oct 2016 | B2 |
9544231 | Bosshart et al. | Jan 2017 | B2 |
9590925 | Yamashita | Mar 2017 | B2 |
9660904 | Kotalwar et al. | May 2017 | B2 |
9686209 | Arad et al. | Jun 2017 | B1 |
9692690 | Joshi et al. | Jun 2017 | B2 |
9712439 | Bosshart et al. | Jul 2017 | B2 |
9755932 | Godbole et al. | Sep 2017 | B1 |
9825862 | Bosshart | Nov 2017 | B2 |
9826071 | Bosshart | Nov 2017 | B2 |
9838268 | Mattson | Dec 2017 | B1 |
9888033 | Li et al. | Feb 2018 | B1 |
9891898 | Tonsing | Feb 2018 | B1 |
9912610 | Bosshart et al. | Mar 2018 | B2 |
9912774 | Daly et al. | Mar 2018 | B2 |
9923816 | Kim et al. | Mar 2018 | B2 |
9960956 | Johnson et al. | May 2018 | B1 |
10009276 | Bosshart et al. | Jun 2018 | B2 |
10015048 | Gasparakis et al. | Jul 2018 | B2 |
10044646 | Detwiler | Aug 2018 | B1 |
10091090 | Chang | Oct 2018 | B2 |
10091137 | Tran et al. | Oct 2018 | B2 |
10135734 | Singh et al. | Nov 2018 | B1 |
10225381 | Bosshart | Mar 2019 | B1 |
10291555 | K et al. | May 2019 | B2 |
10341242 | Srinivasan et al. | Jul 2019 | B2 |
10361914 | Gasparakis et al. | Jul 2019 | B2 |
10412018 | Feng et al. | Sep 2019 | B1 |
10419242 | Tonsing et al. | Sep 2019 | B1 |
10419366 | Kim et al. | Sep 2019 | B1 |
10432527 | Bosshart | Oct 2019 | B1 |
10686735 | Watson | Jun 2020 | B1 |
10892939 | Castaldelli et al. | Jan 2021 | B2 |
10944696 | Galles | Mar 2021 | B2 |
11018977 | Hood | May 2021 | B2 |
11388053 | Gasparakis | Jul 2022 | B2 |
11394610 | Gasparakis | Jul 2022 | B2 |
11394611 | Gasparakis et al. | Jul 2022 | B2 |
20010043611 | Kadambi et al. | Nov 2001 | A1 |
20020001356 | Shenoi | Jan 2002 | A1 |
20020136163 | Kawakami et al. | Sep 2002 | A1 |
20020172210 | Wolrich et al. | Nov 2002 | A1 |
20030005103 | Narad et al. | Jan 2003 | A1 |
20030009466 | Ta et al. | Jan 2003 | A1 |
20030043825 | Magnussen et al. | Mar 2003 | A1 |
20030046414 | Pettyjohn et al. | Mar 2003 | A1 |
20030046429 | Sonksen | Mar 2003 | A1 |
20030063345 | Fossum et al. | Apr 2003 | A1 |
20030107996 | Black et al. | Jun 2003 | A1 |
20030118022 | Kulkarni et al. | Jun 2003 | A1 |
20030147401 | Kyronaho et al. | Aug 2003 | A1 |
20030154358 | Seong et al. | Aug 2003 | A1 |
20030167373 | Winters et al. | Sep 2003 | A1 |
20030219026 | Sun et al. | Nov 2003 | A1 |
20040024894 | Osman et al. | Feb 2004 | A1 |
20040031029 | Lee et al. | Feb 2004 | A1 |
20040042477 | Bitar et al. | Mar 2004 | A1 |
20040105384 | Gallezot et al. | Jun 2004 | A1 |
20040123220 | Johnson et al. | Jun 2004 | A1 |
20040165588 | Pandya | Aug 2004 | A1 |
20040213156 | Smallwood et al. | Oct 2004 | A1 |
20050013251 | Wang et al. | Jan 2005 | A1 |
20050041590 | Olakangil et al. | Feb 2005 | A1 |
20050060428 | Corl et al. | Mar 2005 | A1 |
20050078651 | Lee et al. | Apr 2005 | A1 |
20050086353 | Shirakawa et al. | Apr 2005 | A1 |
20050108518 | Pandya | May 2005 | A1 |
20050120173 | Minowa | Jun 2005 | A1 |
20050129059 | Jiang et al. | Jun 2005 | A1 |
20050135399 | Baden et al. | Jun 2005 | A1 |
20050147095 | Guerrero et al. | Jul 2005 | A1 |
20050149823 | Lee | Jul 2005 | A1 |
20050198531 | Kaniz et al. | Sep 2005 | A1 |
20050243852 | Bitar et al. | Nov 2005 | A1 |
20060002386 | Yik et al. | Jan 2006 | A1 |
20060039372 | Sarkinen et al. | Feb 2006 | A1 |
20060039374 | Belz et al. | Feb 2006 | A1 |
20060050690 | Epps et al. | Mar 2006 | A1 |
20060072480 | Deval et al. | Apr 2006 | A1 |
20060092857 | Ansari et al. | May 2006 | A1 |
20060114895 | Anand et al. | Jun 2006 | A1 |
20060114914 | Anand et al. | Jun 2006 | A1 |
20060117126 | Leung et al. | Jun 2006 | A1 |
20060174242 | Zhu et al. | Aug 2006 | A1 |
20060277346 | Doak et al. | Dec 2006 | A1 |
20070008985 | Lakshmanamurthy et al. | Jan 2007 | A1 |
20070050426 | Dubal et al. | Mar 2007 | A1 |
20070055664 | Michaeli et al. | Mar 2007 | A1 |
20070104102 | Opsasnick | May 2007 | A1 |
20070104211 | Opsasnick | May 2007 | A1 |
20070153796 | Kesavan et al. | Jul 2007 | A1 |
20070195761 | Tatar et al. | Aug 2007 | A1 |
20070195773 | Tatar et al. | Aug 2007 | A1 |
20070208876 | Davis | Sep 2007 | A1 |
20070230493 | Dravida et al. | Oct 2007 | A1 |
20070236734 | Okamoto | Oct 2007 | A1 |
20070280277 | Lund et al. | Dec 2007 | A1 |
20080082792 | Vincent et al. | Apr 2008 | A1 |
20080130670 | Kim et al. | Jun 2008 | A1 |
20080144662 | Marcondes et al. | Jun 2008 | A1 |
20080175449 | Fang et al. | Jul 2008 | A1 |
20080285571 | Arulambalam et al. | Nov 2008 | A1 |
20090006605 | Chen et al. | Jan 2009 | A1 |
20090096797 | Du et al. | Apr 2009 | A1 |
20090106523 | Steiss | Apr 2009 | A1 |
20090147787 | Arulambalam et al. | Jun 2009 | A1 |
20090180475 | Hashimoto | Jul 2009 | A1 |
20100085891 | Kind et al. | Apr 2010 | A1 |
20100128735 | Lipschutz | May 2010 | A1 |
20100135158 | Adams | Jun 2010 | A1 |
20100140364 | Nordberg et al. | Jun 2010 | A1 |
20100145475 | Bartels et al. | Jun 2010 | A1 |
20100150164 | Ma | Jun 2010 | A1 |
20100182920 | Matsuoka | Jul 2010 | A1 |
20100191951 | Malone et al. | Jul 2010 | A1 |
20100228733 | Harrison et al. | Sep 2010 | A1 |
20100238812 | Boutros et al. | Sep 2010 | A1 |
20100312941 | Aloni et al. | Dec 2010 | A1 |
20110080916 | Davies et al. | Apr 2011 | A1 |
20110149776 | Park et al. | Jun 2011 | A1 |
20110149960 | Gutierrez | Jun 2011 | A1 |
20120033550 | Yano et al. | Feb 2012 | A1 |
20120155395 | Yadav et al. | Jun 2012 | A1 |
20120159235 | Suganthi et al. | Jun 2012 | A1 |
20120170585 | Mehra et al. | Jul 2012 | A1 |
20120173661 | Mahaffey et al. | Jul 2012 | A1 |
20120177047 | Roitshtein | Jul 2012 | A1 |
20120284438 | Zievers | Nov 2012 | A1 |
20130003556 | Boden et al. | Jan 2013 | A1 |
20130028265 | Ronchetti et al. | Jan 2013 | A1 |
20130100951 | Ishizuka | Apr 2013 | A1 |
20130108264 | Deruijter et al. | May 2013 | A1 |
20130124491 | Pepper et al. | May 2013 | A1 |
20130163426 | Beliveau et al. | Jun 2013 | A1 |
20130163427 | Beliveau et al. | Jun 2013 | A1 |
20130163475 | Beliveau et al. | Jun 2013 | A1 |
20130166703 | Hammer et al. | Jun 2013 | A1 |
20130227051 | Khakpour et al. | Aug 2013 | A1 |
20130227519 | Maleport | Aug 2013 | A1 |
20130290622 | Dey et al. | Oct 2013 | A1 |
20130315054 | Shamis et al. | Nov 2013 | A1 |
20130318107 | Asaad et al. | Nov 2013 | A1 |
20130346814 | Zadigian et al. | Dec 2013 | A1 |
20140033489 | Kawashima | Feb 2014 | A1 |
20140040527 | Kanigicheria et al. | Feb 2014 | A1 |
20140043974 | Kwan et al. | Feb 2014 | A1 |
20140050002 | Sun | Feb 2014 | A1 |
20140082302 | Rommelmann et al. | Mar 2014 | A1 |
20140115571 | Wang et al. | Apr 2014 | A1 |
20140115666 | Garcia Morchon et al. | Apr 2014 | A1 |
20140140342 | Narad | May 2014 | A1 |
20140181232 | Manula et al. | Jun 2014 | A1 |
20140181818 | Vincent et al. | Jun 2014 | A1 |
20140204943 | Palmer | Jul 2014 | A1 |
20140233568 | Dong | Aug 2014 | A1 |
20140241358 | Bosshart et al. | Aug 2014 | A1 |
20140241359 | Bosshart et al. | Aug 2014 | A1 |
20140241361 | Bosshart et al. | Aug 2014 | A1 |
20140241362 | Bosshart et al. | Aug 2014 | A1 |
20140244966 | Bosshart et al. | Aug 2014 | A1 |
20140269432 | Goyal et al. | Sep 2014 | A1 |
20140301192 | Lee et al. | Oct 2014 | A1 |
20140321473 | Chen et al. | Oct 2014 | A1 |
20140321476 | Yu et al. | Oct 2014 | A1 |
20140328180 | Kim et al. | Nov 2014 | A1 |
20140328344 | Bosshart | Nov 2014 | A1 |
20140334489 | Bosshart et al. | Nov 2014 | A1 |
20150003259 | Gao | Jan 2015 | A1 |
20150009796 | Koponen et al. | Jan 2015 | A1 |
20150010000 | Zhang et al. | Jan 2015 | A1 |
20150020060 | Bandakka et al. | Jan 2015 | A1 |
20150023147 | Lee et al. | Jan 2015 | A1 |
20150043589 | Han et al. | Feb 2015 | A1 |
20150081833 | Pettit et al. | Mar 2015 | A1 |
20150092539 | Sivabalan et al. | Apr 2015 | A1 |
20150109913 | Yamashita | Apr 2015 | A1 |
20150110114 | Wohlgemuth et al. | Apr 2015 | A1 |
20150121355 | Chang et al. | Apr 2015 | A1 |
20150131666 | Kang et al. | May 2015 | A1 |
20150131667 | Ko et al. | May 2015 | A1 |
20150142932 | Hallivuori et al. | May 2015 | A1 |
20150142991 | Zaloom | May 2015 | A1 |
20150146527 | Kishore et al. | May 2015 | A1 |
20150156288 | Lu et al. | Jun 2015 | A1 |
20150172198 | Levy et al. | Jun 2015 | A1 |
20150178395 | Tiwari et al. | Jun 2015 | A1 |
20150180769 | Wang et al. | Jun 2015 | A1 |
20150194215 | Douglas et al. | Jul 2015 | A1 |
20150195206 | Memon et al. | Jul 2015 | A1 |
20150222560 | Kakadia et al. | Aug 2015 | A1 |
20150249572 | Mack-Crane et al. | Sep 2015 | A1 |
20150256465 | Mack-Crane et al. | Sep 2015 | A1 |
20150271011 | Neginhal et al. | Sep 2015 | A1 |
20150281125 | Koponen et al. | Oct 2015 | A1 |
20150319086 | Tripathi et al. | Nov 2015 | A1 |
20150358290 | Jain et al. | Dec 2015 | A1 |
20150363522 | Maurya | Dec 2015 | A1 |
20150381418 | Fausak et al. | Dec 2015 | A1 |
20150381495 | Cherian et al. | Dec 2015 | A1 |
20160006654 | Fernando et al. | Jan 2016 | A1 |
20160014073 | Reddy et al. | Jan 2016 | A1 |
20160019161 | Patel et al. | Jan 2016 | A1 |
20160094460 | Shelar et al. | Mar 2016 | A1 |
20160112317 | Hood | Apr 2016 | A1 |
20160139892 | Atreya et al. | May 2016 | A1 |
20160149784 | Zhang et al. | May 2016 | A1 |
20160156557 | Bosshart et al. | Jun 2016 | A1 |
20160173371 | Bays | Jun 2016 | A1 |
20160173383 | Liu et al. | Jun 2016 | A1 |
20160188313 | Dubal et al. | Jun 2016 | A1 |
20160188320 | Chang et al. | Jun 2016 | A1 |
20160191306 | Gasparakis et al. | Jun 2016 | A1 |
20160191361 | Behera et al. | Jun 2016 | A1 |
20160191370 | Wood | Jun 2016 | A1 |
20160191384 | Shelar et al. | Jun 2016 | A1 |
20160191406 | Xiao et al. | Jun 2016 | A1 |
20160191530 | Jain et al. | Jun 2016 | A1 |
20160197852 | Hutchison et al. | Jul 2016 | A1 |
20160212012 | Young et al. | Jul 2016 | A1 |
20160232019 | Shah et al. | Aug 2016 | A1 |
20160234067 | Dolganow et al. | Aug 2016 | A1 |
20160234097 | Chang | Aug 2016 | A1 |
20160234102 | Kotalwar et al. | Aug 2016 | A1 |
20160234103 | Kotalwar et al. | Aug 2016 | A1 |
20160241459 | Zheng et al. | Aug 2016 | A1 |
20160301601 | Anand et al. | Oct 2016 | A1 |
20160315866 | Thapar et al. | Oct 2016 | A1 |
20160323243 | Levasseur et al. | Nov 2016 | A1 |
20160330127 | Kim et al. | Nov 2016 | A1 |
20160330128 | Wang | Nov 2016 | A1 |
20160337329 | Sood et al. | Nov 2016 | A1 |
20160342510 | Pani | Nov 2016 | A1 |
20160344629 | Gray | Nov 2016 | A1 |
20160357534 | Krishnamoorthi et al. | Dec 2016 | A1 |
20160359685 | Yadav et al. | Dec 2016 | A1 |
20170005951 | Labonte et al. | Jan 2017 | A1 |
20170013452 | Mentze et al. | Jan 2017 | A1 |
20170019302 | Lapiotis et al. | Jan 2017 | A1 |
20170019329 | Kozat et al. | Jan 2017 | A1 |
20170034082 | Pfaff | Feb 2017 | A1 |
20170041209 | Joshi et al. | Feb 2017 | A1 |
20170048144 | Liu | Feb 2017 | A1 |
20170053012 | Levy et al. | Feb 2017 | A1 |
20170063690 | Bosshart | Mar 2017 | A1 |
20170064047 | Bosshart | Mar 2017 | A1 |
20170070416 | Narayanan et al. | Mar 2017 | A1 |
20170075692 | Naresh et al. | Mar 2017 | A1 |
20170085414 | Castaldelli et al. | Mar 2017 | A1 |
20170085477 | Li et al. | Mar 2017 | A1 |
20170085479 | Wang et al. | Mar 2017 | A1 |
20170091258 | Rajahalme | Mar 2017 | A1 |
20170093707 | Kim et al. | Mar 2017 | A1 |
20170093986 | Kim et al. | Mar 2017 | A1 |
20170093987 | Kaushalram et al. | Mar 2017 | A1 |
20170111275 | Li et al. | Apr 2017 | A1 |
20170118041 | Bhattacharya et al. | Apr 2017 | A1 |
20170118042 | Bhattacharya et al. | Apr 2017 | A1 |
20170126588 | Anand et al. | May 2017 | A1 |
20170134282 | Agarwal et al. | May 2017 | A1 |
20170134310 | Koladi et al. | May 2017 | A1 |
20170142000 | Cai et al. | May 2017 | A1 |
20170142011 | Zhang et al. | May 2017 | A1 |
20170149632 | Saltsidis et al. | May 2017 | A1 |
20170180273 | Daly et al. | Jun 2017 | A1 |
20170195229 | Ulas et al. | Jul 2017 | A1 |
20170208015 | Volkening et al. | Jul 2017 | A1 |
20170220499 | Gray | Aug 2017 | A1 |
20170222881 | Holbrook et al. | Aug 2017 | A1 |
20170223575 | Duda et al. | Aug 2017 | A1 |
20170251077 | Eerpini et al. | Aug 2017 | A1 |
20170264571 | Aibester et al. | Sep 2017 | A1 |
20170289034 | Bosshart et al. | Oct 2017 | A1 |
20180006945 | Flajslik et al. | Jan 2018 | A1 |
20180006950 | Flajslik et al. | Jan 2018 | A1 |
20180054385 | Dharmapurikar et al. | Feb 2018 | A1 |
20180103060 | Li et al. | Apr 2018 | A1 |
20180115478 | Kim et al. | Apr 2018 | A1 |
20180124183 | Kozat et al. | May 2018 | A1 |
20180191640 | Calderon et al. | Jul 2018 | A1 |
20180234340 | Kim et al. | Aug 2018 | A1 |
20180234355 | Kim et al. | Aug 2018 | A1 |
20180262424 | Roeland et al. | Sep 2018 | A1 |
20180287819 | Mayer-Wolf et al. | Oct 2018 | A1 |
20180316549 | Gasparakis et al. | Nov 2018 | A1 |
20180375755 | Joshi et al. | Dec 2018 | A1 |
20190394086 | Gasparakis et al. | Dec 2019 | A1 |
20200007473 | Kim et al. | Jan 2020 | A1 |
20200021486 | Gasparakis et al. | Jan 2020 | A1 |
20200076737 | Bosshart | Mar 2020 | A1 |
20200084093 | Gasparakis et al. | Mar 2020 | A1 |
20200099617 | Bosshart | Mar 2020 | A1 |
20200099618 | Bosshart | Mar 2020 | A1 |
20200099619 | Bosshart | Mar 2020 | A1 |
20200228433 | Lee | Jul 2020 | A1 |
20200244576 | Wetterwald et al. | Jul 2020 | A1 |
20200267098 | Galles | Aug 2020 | A1 |
20200280428 | Kovacs et al. | Sep 2020 | A1 |
20200280518 | Lee et al. | Sep 2020 | A1 |
20220091992 | Shanbhogue et al. | Mar 2022 | A1 |
20220321404 | Gasparakis et al. | Oct 2022 | A1 |
Number | Date | Country |
---|---|---|
1522006 | Aug 2004 | CN |
1589551 | Mar 2005 | CN |
101305561 | Nov 2008 | CN |
101352012 | Jan 2009 | CN |
101453673 | Jun 2009 | CN |
103248573 | Aug 2013 | CN |
104067231 | Sep 2014 | CN |
104205080 | Dec 2014 | CN |
104205753 | Dec 2014 | CN |
105052113 | Nov 2015 | CN |
3229424 | Oct 2017 | EP |
2015080175 | Apr 2015 | JP |
6127900 | May 2017 | JP |
2013101024 | Jul 2013 | WO |
2016063189 | Apr 2016 | WO |
2017112165 | Jun 2017 | WO |
Entry |
---|
Advisory Action for U.S. Appl. No. 15/835,238, dated Nov. 22, 2019, 3 pages. |
Advisory Action for U.S. Appl. No. 15/888,054, dated Feb. 10, 2020. |
Final Office Action for U.S. Appl. No. 15/784,191, dated Feb. 26, 2021. |
Final Office Action for U.S. Appl. No. 15/784,191, dated May 7, 2020, 13 pages. |
Final Office Action for U.S. Appl. No. 15/784,192, dated Jun. 1, 2020, 14 pages. |
Final Office Action for U.S. Appl. No. 15/888,050, dated Dec. 12, 2019. |
Final Office Action for U.S. Appl. No. 15/888,054, dated Sep. 18, 2019. |
Final Office Action for U.S. Appl. No. 16/695,044, dated Dec. 20, 2021. |
Final Office Action for U.S. Appl. No. 16/804,960, dated Apr. 14, 2022. |
Final Office Action for U.S. Appl. No. 17/134,110 dated Oct. 25, 2022. |
International Preliminary Report on Patentability for PCT Application No. PCT/US2016/062511, dated Jun. 26, 2018. |
International Search Report and Written Opinion for PCT Application No. PCT/US2016/062511, dated Feb. 28, 2017. |
Non-Final Office Action for U.S. Appl. No. 16/569,554, dated Feb. 19, 2021. |
Notice of Allowance for Chinese Patent Application No. 201680075637.4, dated Apr. 1, 2022. |
Notice of Allowance for U.S. Appl. No. 14/583,664, dated Feb. 28, 2018. |
Notice of Allowance for U.S. Appl. No. 14/836,850, dated Jun. 20, 2017. |
Notice of Allowance for U.S. Appl. No. 14/836,855, dated Jun. 30, 2017. |
Notice of Allowance for U.S. Appl. No. 14/977,810, dated Oct. 20, 2017. |
Notice of Allowance for U.S. Appl. No. 15/678,549, dated Apr. 8, 2020. |
Notice of Allowance for U.S. Appl. No. 15/678,549, dated Dec. 27, 2019. |
Notice of Allowance for U.S. Appl. No. 15/678,556, dated Feb. 4, 2020. |
Notice of Allowance for U.S. Appl. No. 15/729,555, dated May 2, 2019. |
Notice of Allowance for U.S. Appl. No. 15/729,593, dated Nov. 15, 2018. |
Notice of Allowance for U.S. Appl. No. 15/784,190, dated May 10, 2019, 20 pages. |
Notice of Allowance for U.S. Appl. No. 15/784,191, dated Apr. 19, 2019, 7 pages. |
Notice of Allowance for U.S. Appl. No. 15/784,191, dated Aug. 21, 2019, 8 pages. |
Notice of Allowance for U.S. Appl. No. 15/784,191, dated Aug. 31, 2021. |
Notice of Allowance for U.S. Appl. No. 15/784,191, dated May 5, 2021. |
Notice of Allowance for U.S. Appl. No. 15/784,192, dated Mar. 17, 2021. |
Notice of Allowance for U.S. Appl. No. 15/784,192, dated Jun. 30, 2021. |
Notice of Allowance for U.S. Appl. No. 15/784,192, dated Sep. 30, 2021. |
Notice of Allowance for U.S. Appl. No. 15/835,233, dated Jul. 3, 2019, 8 pages. |
Notice of Allowance for U.S. Appl. No. 15/835,233, dated Oct. 29, 2019. |
Notice of Allowance for U.S. Appl. No. 15/835,235, dated Apr. 24, 2020. |
Notice of Allowance for U.S. Appl. No. 15/835,235, dated Aug. 20, 2019, 16 pages. |
Notice of Allowance for U.S. Appl. No. 15/835,238, dated Sep. 30, 2020. |
Notice of Allowance for U.S. Appl. No. 15/835,239, dated Nov. 13, 2019, 10 pages. |
Notice of Allowance for U.S. Appl. No. 15/835,242, dated Jun. 24, 2020. |
Notice of Allowance for U.S. Appl. No. 15/835,242, dated Jul. 1, 2019, 7 pages. |
Notice of Allowance for U.S. Appl. No. 15/835,247 dated Dec. 29, 2021. |
Notice of Allowance for U.S. Appl. No. 15/835,247, dated Apr. 7, 2022. |
Notice of Allowance for U.S. Appl. No. 15/835,247, dated Jul. 29, 2022. |
Notice of Allowance for U.S. Appl. No. 15/835,249, dated Jul. 25, 2019. |
Notice of Allowance for U.S. Appl. No. 15/835,250, dated Jul. 25, 2019, 17 pages. |
Notice of Allowance for U.S. Appl. No. 15/878,966, dated May 15, 2019. |
Notice of Allowance for U.S. Appl. No. 16/026,318, dated Mar. 12, 2019. |
Notice of Allowance for U.S. Appl. No. 16/460,798, dated May 27, 2021. |
Notice of Allowance for U.S. Appl. No. 16/519,873, dated Aug. 30, 2021. |
Notice of Allowance for U.S. Appl. No. 16/519,873, dated Dec. 3, 2021. |
Notice of Allowance for U.S. Appl. No. 16/519,873, dated Mar. 17, 2022. |
Notice of Allowance for U.S. Appl. No. 16/573,847, dated Apr. 14, 2022. |
Notice of Allowance for U.S. Appl. No. 16/573,847, dated Dec. 15, 2021. |
Notice of Allowance for U.S. Appl. No. 16/582,798, dated Aug. 27, 2021. |
Notice of Allowance for U.S. Appl. No. 16/582,798, dated Dec. 1, 2021. |
Notice of Allowance for U.S. Appl. No. 16/582,798, dated Mar. 22, 2022. |
Notice of Allowance for U.S. Appl. No. 16/687,271, dated Aug. 30, 2021. |
Notice of Allowance for U.S. Appl. No. 16/687,271, dated Dec. 1, 2021. |
Notice of Allowance for U.S. Appl. No. 16/687,271, dated Mar. 22, 2022. |
Notice of Allowance for U.S. Appl. No. 16/695,044 dated Apr. 27, 2022. |
Notice of Allowance for U.S. Appl. No. 16/695,049, dated Apr. 28, 2022. |
Notice of Allowance for U.S. Appl. No. 16/695,049, dated Jan. 5, 2022. |
Notice of Allowance for U.S. Appl. No. 16/789,339, dated Jul. 29, 2021. |
Notice of Allowance for U.S. Appl. No. 16/879,704, dated Apr. 26, 2022. |
Notice of Allowance for U.S. Appl. No. 17/318,890, dated Jun. 8, 2022. |
Notice of Allowance for U.S. Appl. No. 17/318,890, dated Mar. 3, 2022. |
Notice of Allowance for U.S. Appl. No. 17/484,004, dated Feb. 15, 2023. |
Notice of Allowance for U.S. Appl. No. 17/494,515, dated Feb. 28, 2023. |
Notice of Allowance for U.S. Appl. No. 17/867,508, dated Nov. 14, 2022. |
Office Action for Chinese Patent Application No. 201680075637.4, dated Mar. 2, 2021. |
Office Action for Chinese Patent Application No. 201680075637.4, dated Sep. 23, 2021. |
Office Action for U.S. Appl. No. 15/878,966, dated Jan. 11, 2019. |
Office Action for U.S. Appl. No. 14/583,664, dated Feb. 27, 2017. |
Office Action for U.S. Appl. No. 14/583,664, dated Jul. 28, 2016. |
Office Action for U.S. Appl. No. 14/583,664, dated Oct. 18, 2017. |
Office Action for U.S. Appl. No. 14/863,961, dated Jun. 16, 2017. |
Office Action for U.S. Appl. No. 14/864,032, dated Feb. 14, 2017. |
Office Action for U.S. Appl. No. 14/977,810, dated Jun. 29, 2017. |
Office Action for U.S. Appl. No. 15/678,549, dated Feb. 26, 2019. |
Office Action for U.S. Appl. No. 15/678,549, dated Jul. 30, 2019. |
Office Action for U.S. Appl. No. 15/678,556, dated Jun. 19, 2019. |
Office Action for U.S. Appl. No. 15/678,565, dated Jun. 13, 2019. |
Office Action for U.S. Appl. No. 15/729,593, dated Aug. 10, 2018. |
Office Action for U.S. Appl. No. 15/784,191, dated Aug. 26, 2020, 14 pages. |
Office Action for U.S. Appl. No. 15/784,191, dated Dec. 19, 2018, 11 pages. |
Office Action for U.S. Appl. No. 15/784,191, dated Jan. 24, 2020, 12 pages. |
Office Action for U.S. Appl. No. 15/784,192, dated Sep. 19, 2019, 14 pages. |
Office Action for U.S. Appl. No. 15/835,233, dated Feb. 8, 2019, 17 pages. |
Office Action for U.S. Appl. No. 15/835,235, dated Feb. 25, 2019, 24 pages. |
Office Action for U.S. Appl. No. 15/835,238, dated Dec. 11, 2019. |
Office Action for U.S. Appl. No. 15/835,238, dated Feb. 7, 2019. |
Office Action for U.S. Appl. No. 15/835,238, dated Jun. 19, 2019. |
Office Action for U.S. Appl. No. 15/835,238, dated Jun. 5, 2020. |
Office Action for U.S. Appl. No. 15/835,239, dated Feb. 7, 2019, 20 pages. |
Office Action for U.S. Appl. No. 15/835,239, dated Jun. 19, 2019, 18 pages. |
Office Action for U.S. Appl. No. 15/835,242, dated Oct. 18, 2019, 8 pages. |
Office Action for U.S. Appl. No. 15/835,247, dated Dec. 31, 2018, 18 pages. |
Office Action for U.S. Appl. No. 15/835,247, dated Jul. 10, 2019. |
Office Action for U.S. Appl. No. 15/835,249, dated Dec. 31, 2018. |
Office Action for U.S. Appl. No. 15/835,250, dated Apr. 4, 2019, 16 pages. |
Office Action for U.S. Appl. No. 15/888,050, dated Jun. 11, 2019. |
Office Action for U.S. Appl. No. 15/888,054, dated Mar. 11, 2019. |
Office Action for U.S. Appl. No. 16/026,318, dated Sep. 20, 2018. |
Office Action for U.S. Appl. No. 16/288,074, dated Oct. 7, 2020. |
Office Action for U.S. Appl. No. 16/288,074, dated Mar. 5, 2020. |
Office Action for U.S. Appl. No. 16/4670,798, dated Nov. 18, 2020. |
Office Action for U.S. Appl. No. 16/519,873, dated Jun. 11, 2021. |
Office Action for U.S. Appl. No. 16/569,554, dated Aug. 18, 2020. |
Office Action for U.S. Appl. No. 16/569,554, dated Jul. 2, 2021. |
Office Action for U.S. Appl. No. 16/569,554, dated Mar. 14, 2022. |
Office Action for U.S. Appl. No. 16/569,554, dated Sep. 27, 2021. |
Office Action for U.S. Appl. No. 16/573,847 dated Jan. 6, 2021. |
Office Action for U.S. Appl. No. 16/573,847, dated Aug. 2, 2021. |
Office Action for U.S. Appl. No. 16/582,798, dated Jun. 24, 2021. |
Office Action for U.S. Appl. No. 16/687,271, dated Jun. 24, 2021. |
Office Action for U.S. Appl. No. 16/695,044, dated Jul. 8, 2021. |
Office Action for U.S. Appl. No. 16/695,049, dated Jul. 21, 2021. |
Office Action for U.S. Appl. No. 16/695,053 dated Aug. 4, 2021. |
Office Action for U.S. Appl. No. 16/695,053 dated Jan. 5, 2022. |
Office Action for U.S. Appl. No. 16/695,053, dated May 11, 2022. |
Office Action for U.S. Appl. No. 16/695,053, dated Oct. 14, 2022. |
Office Action for U.S. Appl. No. 16/804,960, dated Aug. 19, 2021. |
Office Action for U.S. Appl. No. 16/804,960, dated Dec. 13, 2021. |
Office Action for U.S. Appl. No. 16/804,960, dated May 12, 2021. |
Office Action for U.S. Appl. No. 17/134,110, dated Dec. 22, 2022. |
Office Action for U.S. Appl. No. 17/134,110, dated Jun. 24, 2022. |
Office Action for U.S. Appl. No. 17/484,004, dated Oct. 27, 2022. |
Office Action for U.S. Appl. No. 17/859,722, dated Mar. 28, 2023. |
Office Action for U.S. Appl. No. 17/859,722, dated Oct. 26, 2022. |
Office Action in Chinese Patent Application No. 201680075637.4, dated Jan. 5, 2022. |
“Selection of Cyclic Redundancy Code and Checksum Algorithms to Ensure Critical Data Integrity”, Federal Aviation Administration William J. Hughes Technical Center Aviation Research Division Atlantic City International Airport New Jersey 08405, DOT/FAA/TC-14/49, Mar. 2015, 111 pages. |
Arashloo, Mina Tahmasbi , et al. , “SNAP: Stateful Network-Wide Abstractions for Packet Processing”, SIGCOMM '16, Aug. 22-26, 2016, 27 pages, ACM, Florianopolis, Brazil. |
Bosshart, P. , et al. , “Forwarding Metamorphosis: Fast Programmable Match-Action Processing in Hardware or SDN”, SIGCOMM'13, Aug. 12-16, 2013, 12 pages, ACM, Hong Kong, China. |
Kaufmann, A. , et al. , “High Performance Packet Processing with FlexNIC”, ASPLOS'16, Apr. 2-6, 2016, 15 pages, ACM, Atlanta, GA, USA. |
Moshref, Masoud , et al. , “Flow-level State Transition as a New Switch Primitive for SON”, HotSDN'14, Aug. 22, 2014, 6 pages, ACM, Chicago, IL, USA. |
Sivaraman, A. , et al. , “Towards Programmable Packet Scheduling”, HotNets'15, Nov. 16-17, 2015, 7 pages, ACM, Philadelphia, PA, USA. |
Sivaraman, Anirudh , et al. , “Packet Transactions: A Programming Model for Data-Plane Algorithms at Hardware Speed”, arXiv:1512.05023v1, Dec. 16, 2015, 22 pages. |
Sivaraman, Anirudh , et al. , “Packet Transactions: High-level Programming for Line-Rate Switches”, ?rXiv:1512.05023v2, Jan. 30, 2016, 16 pages. |
Sivaraman, Anirudh , et al. , “Packet Transactions: High-level Programming for Line-Rate Switches”, SIGCOMM'16, Aug. 22-26, 2016, 14 pages, ACM, Florianopolis, Brazil. |
Sivaraman, Anirudh , et al. , “Programmable Packet Scheduling at Line Rate”, SIGCOMM'16, Aug. 22-26, 2016, 14 pages, ACM, Florianopolis, Brazil. |
Song , “Protocol-Oblivious Forwarding: Unleash the Power of SDN through a Future-Proof Forwarding Plane”, Huawei Technologies, USA, 6 pages. |
Non-Final Office Action from U.S. Appl. No. 17/837,864 dated Mar. 16, 2023, 18 pgs. |
Notice of Allowance from Chinese Patent Application No. 202111494631.X dated Jan. 2, 2024, 4 pgs. |
Notice of Allowance from U.S. Appl. No. 17/134,110 dated Apr. 26, 2023, 9 pgs. |
Notice of Allowance from U.S. Appl. No. 17/837,864 dated Jul. 14, 2023, 14 pgs. |
Notice of Allowance from U.S. Appl. No. 17/837,864 dated Oct. 31, 2023, 17 pgs. |
Notice of Allowance from U.S. Appl. No. 17/859,722 dated Aug. 9, 2023, 9 pgs. |
Notice of Allowance from U.S. Appl. No. 18/077,543 dated Aug. 23, 2023, 16 pgs. |
Notice of Allowance from U.S. Appl. No. 17/859,722 dated Dec. 12, 2023, 16 pgs. |
Notice of Allowance from U.S. Appl. No. 18/077,543 dated Dec. 15, 2023, 17 pgs. |
Office Action from Chinese Patent Application No. 202111206815.1 dated Oct. 19, 2023, 14 pgs. |
Office Action from Chinese Patent Application No. 202111494631.X dated Jul. 18, 2023, 18 pgs. |
Office Action from Chinese Patent Application No. 202111494631.X dated Oct. 20, 2023, 5 pgs. |
“In-band Network Telemetry (INT)”, The P4.org Applications Working Group, Contributions from: Alibaba, Arista, Barefoot Networks, Dell, Intel, VMware. Dec. 11, 2017, 29 pgs. |
“Intel Tofino 6.4 Tbps, 4 pipelines”, Intel, 3 pgs. |
“P416 Language Specification Version 1.0.0”, The P2 Language Consortium, Jul. 22, 2017, 129 pgs. |
“P416 Language Specification Version 1.1.0”, The P4 Language Consortium, Nov. 20, 2018, 147 pgs. |
“The P4 Language Specification Version 1.0.2”, The P4 Language Consortium, Mar. 3, 2015, 90 pgs. |
“The P4 Language Specification Version 1.0.4”, The P4 Language Consortium, May 24, 2017, 97 pgs. |
“The P4 Language Specification Version 1.0.5”, The P4 Language Consortium, Nov. 26, 2018, 96 pgs. |
“The P4 Language Specification Version 1.1.0”, The P4 Language Consortium, Jan. 27, 2016, 124 pgs. |
“The P4 Language Specification, Version 1.0.3”, The P4 Language Consortium, Nov. 2, 2016, 97 pgs. |
“The Walls Come Down On the Last Bastion of Proprietary”, The Next Platform, Jun. 14, 2016, 13 pgs. |
“Tofino 2.0 Tbps, 2 pipelines”, Intel, 3 pgs. |
“Tofino 3.2 Tbps, 2 pipelines”, Intel, 3 pgs. |
“Tofino 3.2 Tbps, 4 pipelines”, Intel, 3 pgs. |
“Tofino(TM)-based Wedge 100B Switch Designs with the Open Compute Project (OCP)”, Barefoot Networks, Jan. 23, 2017. 7 pgs. |
Bosshart, et al., “Forwarding Metamorphosis: Fast Programmable Match-Action Processing in Hardware for SDN (Extended Version)”, Chip Techreport, 2013, 16 pgs. |
Bosshart, et al., “P4: Programming Protocol-Independent Packet Processors”, ACM SIGCOMM Computer Communication Review, vol. 44, No. 3. Jul. 2014, 8 pgs. |
Gurevich, “Programmable Data Plane at Terabit Speeds”, Barefoot Networks, May 16, 2017, 45 pgs. |
Kfoury, et al., “An Exhaustive Survey on P4 Programmable Data Plane Switches: Taxonomy, Applications, Challenges, and Future Trends”, IEEE, vol. 14, 2016, 64 pgs. |
Non-Final Office Action from U.S. Appl. No. 18/214,665 notified Feb. 1, 2024, 9 pgs. |
Notice of Allowance from Chinese Patent Application No. 202111206815.1 notified Mar. 19, 2024, 6 pgs. |
Notice of Allowance from U.S. Appl. No. 17/837,864 notified Mar. 1, 2024, 18 pgs. |
Notice of Allowance from U.S. Appl. No. 17/859,722 notified Mar. 20, 2024, 13 pgs. |
Notice of Allowance from U.S. Appl. No. 18/077,543 notified Apr. 8, 2024, 13 pgs. |
Number | Date | Country | |
---|---|---|---|
20230239368 A1 | Jul 2023 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 17484004 | Sep 2021 | US |
Child | 18130733 | US | |
Parent | 16460798 | Jul 2019 | US |
Child | 17484004 | US | |
Parent | 15878966 | Jan 2018 | US |
Child | 16460798 | US | |
Parent | 14977810 | Dec 2015 | US |
Child | 15878966 | US |