Abstract: An ingress packet processor in a device corresponds to a group of ports and receives network packets from ports in its port group. A traffic manager in the device manages buffers storing packet data for transmission to egress packet processors. An ingress arbiter is associated with a port group and connects the port group to an ingress packet processor coupled to the ingress arbiter. The ingress arbiter determines a traffic rate at which the associated ingress packet processor transmits packets to the traffic manager. The ingress arbiter controls an associated traffic shaper to generate a number of tokens that are assigned to the port group. Upon receiving packet data from a port in the group, the ingress arbiter determines, using information from the traffic shaper, whether a token is available. Conditioned on determining that a token is available, the ingress arbiter forwards the packet data to the ingress packet processor.

Abstract: Ingress packet processors in a device receive network packets from ingress ports. A crossbar in the device receives, from the ingress packet processors, packet data of the packets and transmits information about the packet data to a plurality of traffic managers in the device. Each traffic manager computes a total amount of packet data to be written to buffers across the plurality of traffic managers, where each traffic manager manages one or more buffers that store packet data. Each traffic manager compares the total amount of packet data to one or more threshold values. Upon determining that the total amount of packet data is equal to or greater than a threshold value, each traffic manager drops a portion of the packet data, and writes a remaining portion of the packet data to the buffers managed by the traffic manager.

Abstract: Automatic load-balancing techniques in a network device are used to select, from a multipath group, a path to assign to a flow based on observed state attributes such as path state(s), device state(s), port state(s), or queue state(s) of the paths. A mapping of the path previously assigned to a flow or group of flows (e.g., on account of having then been optimal in view of the observed state attributes) is maintained, for example, in a table. So long as the flow(s) are active and the path is still valid, the mapped path is selected for subsequent data units belonging to the flow(s), which may, among other effects, avoid or reduce packet re-ordering. However, if the flow(s) go idle, or if the mapped path fails, a new optimal path may be assigned to the flow(s) from the multipath group.

Abstract: A method, computer program product, and system to identify one or more items in a transaction are provided. The method includes capturing images of the items, determining a set of possible identifications for each item based on the images, determining information regarding the transaction, selecting an identification for each item from the sets of possible identifications, based on the determined information, and adding the selected identifications to the transaction. Identifications for items may be selected based on confidence factors, price thresholds, and customer information.

Abstract: Distributed machine learning systems and other distributed computing systems are improved by embedding compute logic at the network switch level to perform collective actions, such as reduction operations, on gradients or other data processed by the nodes of the system. The switch is configured to recognize data units that carry data associated with a collective action that needs to be performed by the distributed system, referred to herein as “compute data,” and process that data using a compute subsystem within the switch. The compute subsystem includes a compute engine that is configured to perform various operations on the compute data, such as “reduction” operations, and forward the results back to the compute nodes. The reduction operations may include, for instance, summation, averaging, bitwise operations, and so forth. In this manner, the network switch may take over some or all of the processing of the distributed system during the collective phase.

Abstract: A method, computer program product, and system are disclosed for compiling a virtual transaction for a person within an environment having a plurality of items. The method includes acquiring, using at least one visual sensor, first image information including a person. The method further includes identifying the at least one person from the first image information by classifying the person into a class. The method also includes acquiring second image information including the person and an item. The method further includes identifying a behavior of the person relative to the item, and updating, based on the identified behavior, the virtual transaction.

Abstract: In response to certain events in a network device, visibility packets may be generated. A visibility packet may be or comprise at least a portion of a packet that is in some way associated with the event, such as a packet that was dropped as a result of an event, or that was in a queue at the time of an event related to that queue. A visibility packet may be tagged or otherwise indicated as a visibility packet. The network device may include one or more visibility samplers through which visibility packets are routed on their way to a visibility queue, visibility subsystem, and/or out of the network device. The samplers allow only a limited sample of the visibility packets that they receive to pass through the sampler, essentially acting as a filter to reduce the amount of visibility packets that will be processed.

Abstract: Distributed machine learning systems and other distributed computing systems are improved by compute logic embedded in extension modules coupled directly to network switches. The compute logic performs collective actions, such as reduction operations, on gradients or other compute data processed by the nodes of the system. The reduction operations may include, for instance, summation, averaging, bitwise operations, and so forth. In this manner, the extension modules may take over some or all of the processing of the distributed system during the collective phase. An inline version of the module sits between a switch and the network. Data units carrying compute data are intercepted and processed using the compute logic, while other data units pass through the module transparently to or from the switch. Multiple modules may be connected to the switch, each coupled to a different group of nodes, and sharing intermediate results. A sidecar version is also described.

Abstract: Approaches, techniques, and mechanisms are disclosed for assigning paths to network packets. The path assignment techniques utilize path state information and/or other criteria to determine whether to route a packet along a primary candidate path selected for the packet, or one or more alternative candidate paths selected for the packet. According to an embodiment, network traffic is at least partially balanced by redistributing only a portion of the traffic that would have been assigned to a given primary path. Move-eligibility criteria are applied to traffic to determine whether a given packet is eligible for reassignment from a primary path to an alternative path. The move-eligibility criteria determine which portion of the network traffic to move and which portion to allow to proceed as normal. In an embodiment, the criteria and functions used to determine whether a packet is redistributable are adjusted over time based on path state information.

Abstract: Nodes within a network are configured to adapt to changing path states, due to congestion, node failures, and/or other factors. A node may selectively convey path information and/or other state information to another node by annotating the information into packets it receives from the other node. A node may selectively reflect these annotated packets back to the other node, or other nodes that subsequently receive these annotated packets may reflect them. A weighted cost multipathing selection technique is improved by dynamically adjusting weights of paths in response to feedback indicating the current state of the network topology, such as collected through these reflected packets. In an embodiment, certain packets that would have been dropped may instead be transformed into “special visibility” packets that may be stored and/or sent for analysis. In an embodiment, insight into the performance of a network device is enhanced through the use of programmable visibility engines.

Abstract: Approaches, techniques, and mechanisms facilitate actionable reporting of network state information and real-time, autonomous network engineering directly in-network at a switch or other network device. A data collector within the network device collects state information and/or data unit information from various device components, such as traffic managers and packet processors. The data collector, which may optionally generate additional state information by performing various calculations on the information it receives, is configured to then provide at least some of the state information to an analyzer device connected to an analyzer interface. The analyzer device, which may be a separate device, performs various analyses on the state information, depending on how it is configured. The analyzer device outputs reports that identify statuses, errors, misconfigurations, and/or suggested actions to take to improve operation of the network device.

Abstract: Distributed machine learning systems and other distributed computing systems are improved by embedding compute logic at the network switch level to perform collective actions, such as reduction operations, on gradients or other data processed by the nodes of the system. The switch is configured to recognize data units that carry data associated with a collective action that needs to be performed by the distributed system, referred to herein as “compute data,” and process that data using a compute subsystem within the switch. The compute subsystem includes a compute engine that is configured to perform various operations on the compute data, such as “reduction” operations, and forward the results back to the compute nodes. The reduction operations may include, for instance, summation, averaging, bitwise operations, and so forth. In this manner, the network switch may take over some or all of the processing of the distributed system during the collective phase.

Abstract: Embodiments provide for an impact force gauge that includes a track and a shell that is designed to flex from a first state to a second state when a force exceeding a predetermined threshold is applied along a given axis and that is designed to return to the first state when the force falls below the predetermined threshold along the given axis. A roller is located in the shell and has a diameter such the roller is allowed or blocked from moving to different locations in the impact force gauge based on the force applied thereto. Based on the presence or absence of the roller along different portions of the track, the force gauge wirelessly transmits an indication of whether the force gauge has been exposed to a force that exceeds the predetermined threshold.

Abstract: Distributed machine learning systems and other distributed computing systems are improved by embedding compute logic at the network switch level to perform collective actions, such as reduction operations, on gradients or other data processed by the nodes of the system. The switch is configured to recognize data units that carry data associated with a collective action that needs to be performed by the distributed system, referred to herein as “compute data,” and process that data using a compute subsystem within the switch. The compute subsystem includes a compute engine that is configured to perform various operations on the compute data, such as “reduction” operations, and forward the results back to the compute nodes. The reduction operations may include, for instance, summation, averaging, bitwise operations, and so forth. In this manner, the network switch may take over some or all of the processing of the distributed system during the collective phase.

Abstract: A method, computer program product, and system to perform a sale transaction are provided. The method includes identifying each item of a plurality of items, based on at least one image of the plurality of items, determining a cost for each item, optionally identifying a person based on an image of the person, adding each of the items and each of the costs to a sale transaction, and charging the person for the sale transaction.

Abstract: When a measure of buffer space queued for garbage collection in a network device grows beyond a certain threshold, one or more actions are taken to decreasing an enqueue rate of certain classes of traffic, such as of multicast traffic, whose reception may have caused and/or be likely to exacerbate garbage-collection-related performance issues. When the amount of buffer space queued for garbage collection shrinks to an acceptable level, these one or more actions may be reversed. In an embodiment, to more optimally handle multi-destination traffic, queue admission control logic for high-priority multi-destination data units, such as mirrored traffic, may be performed for each destination of the data units prior to linking the data units to a replication queue. If a high-priority multi-destination data unit is admitted to any queue, the high-priority multi-destination data unit can no longer be dropped, and is linked to a replication queue for replication.

Abstract: To more efficiently utilize buffer resources, schedulers within a traffic manager may generate and queue read instructions for reading buffered portions of data units that are ready to be sent to the egress blocks. The traffic manager may be configured to select a read instruction for a given buffer bank from the read instruction queues based on a scoring mechanism or other selection logic. To avoid sending too much data to an egress block during a given time slot, once a data unit portion has been read from the buffer, it may be temporarily stored in a shallow read data cache. Alternatively, a single, non-bank specific controller may determine all of the read instructions and write operations that should be executed in a given time slot. The read instruction queue architecture may be duplicated for link memories and other memories in addition to the buffer memory.

Abstract: A logical bank may comprise multiple physical banks across which logical blocks, such as buffer entries, are striped. Data structures are stored in the logical blocks, with each logical block storing no more than one data structure. When writing a data structure, if the data structure is less than half the logical block size, one or more duplicate copies of the data structure may be stored in the otherwise unused physical blocks of the logical block. Before executing a first read instruction to read a first data structure from a first logical block, if the first data structure can be read without accessing one or more of the physical banks, a second read instruction for a second data structure may be analyzed to determine if there is a copy of a second data structure within the one or more unneeded physical banks. If so, the two read instructions are consolidated.

Abstract: A method, computer program product, and system to perform a sale transaction are provided. The method includes identifying each item of a plurality of items, based on at least one image of the plurality of items, determining a cost for each item, optionally identifying a person based on an image of the person, adding each of the items and each of the costs to a sale transaction, and charging the person for the sale transaction.

Abstract: Methods, computer program products, and systems for operating a retail environment using unmanned vehicles are provided. The methods include observing a person interacting with one or more items with a camera carried by an unmanned vehicle, identifying the one or more items based on data received from the unmanned vehicle, and adding each identified item to a transaction for the person. The methods can further include charging the person for the transaction, presenting promotions, retrieving a desired item, answering questions, following a person, guiding a customer to a location, and showing images of inventory items.