Abstract: Apparatuses, systems, and techniques to perform neural networks. In at least one embodiment, one or more neural networks are used to predict one or more characteristics of one or more first circuits based, at least in part, on one or more characteristics of one or more second circuits.

Abstract: Disclosed are a boom correction method and a boom correction device for a working machine. The method includes: inputting an actual displacement value of a boom of a target working machine at a current moment and a first operating parameter of the target working machine at the current moment into a prediction model, and outputting a predicted displacement value of the boom at a next moment of the current moment; and calculating a difference between the predicted displacement value of the boom and a preset displacement value, and in response to that the difference is greater than a first preset threshold, adjusting a second operating parameter of the target working machine according to the difference to correct the boom of the target working machine; both the first operating parameter and the second operating parameter are related to a displacement of the boom.

Abstract: Disclosed are a boom correction method and a boom correction device for a working machine. The method includes: inputting an actual displacement value of a boom of a target working machine at a current moment and a first operating parameter of the target working machine at the current moment into a prediction model, and outputting a predicted displacement value of the boom at a next moment of the current moment; and calculating a difference between the predicted displacement value of the boom and a preset displacement value, and in response to that the difference is greater than a first preset threshold, adjusting a second operating parameter of the target working machine according to the difference to correct the boom of the target working machine; both the first operating parameter and the second operating parameter are related to a displacement of the boom.

Abstract: Embodiments are provided for partially replicating endpoint routing information, and comprise calculating a first shard interval of a key space based, at least in part, on capacities of a plurality of spine nodes in a network fabric. Embodiments also include mapping the first shard interval to a first spine node of the plurality of spine nodes, communicating shard mapping information associated with the mapping to a set of leaf nodes in the network fabric, and populating an endpoint repository in the first spine node with routing information for one or more endpoints corresponding to the first shard interval. More specific embodiments include calculating respective shard intervals for other spine nodes of the plurality of spine nodes based, at least in part, on the capacities of the plurality of spine nodes. In specific embodiments, the calculating the first shard interval is based, in part, on one or more dynamic parameters.

Abstract: Systems and methods for determining molecular structures based on molecular-orbital-based (MOB) features are described. MOB features can be utilized in combination with machine-learning methods to predict accurate properties, such as quantum mechanical energy, of molecular systems.

Abstract: Embodiments are provided for partially replicating endpoint routing information, and comprise calculating a first shard interval of a key space based, at least in part, on capacities of a plurality of spine nodes in a network fabric. Embodiments also include mapping the first shard interval to a first spine node of the plurality of spine nodes, communicating shard mapping information associated with the mapping to a set of leaf nodes in the network fabric, and populating an endpoint repository in the first spine node with routing information for one or more endpoints corresponding to the first shard interval. More specific embodiments include calculating respective shard intervals for other spine nodes of the plurality of spine nodes based, at least in part, on the capacities of the plurality of spine nodes. In specific embodiments, the calculating the first shard interval is based, in part, on one or more dynamic parameters.

Abstract: Embodiments are provided for partially replicating endpoint routing information, and comprise calculating a first shard interval of a key space based, at least in part, on capacities of a plurality of spine nodes in a network fabric. Embodiments also include mapping the first shard interval to a first spine node of the plurality of spine nodes, communicating shard mapping information associated with the mapping to a set of leaf nodes in the network fabric, and populating an endpoint repository in the first spine node with routing information for one or more endpoints corresponding to the first shard interval. More specific embodiments include calculating respective shard intervals for other spine nodes of the plurality of spine nodes based, at least in part, on the capacities of the plurality of spine nodes. In specific embodiments, the calculating the first shard interval is based, in part, on one or more dynamic parameters.

Abstract: An example method for to inter-pod traffic redirection and handling in a multi-pod network environment is provided and includes receiving a packet with an overlay header outgoing from a first pod, identifying the packet as redirected based on a source address in the overlay header indicating a second pod and a destination address in the overlay header indicating a third pod, the first pod being distinct from the second pod and the third pod, setting a redirection bit in the overlay header tagging the packet as redirected, and transmitting the packet to the third pod.

Abstract: Internet Group Management Protocol (IGMP) snooping includes flooding an IGMP query received at a border leaf switch from a multicast router connected to the multicast router to all host devices in a given bridge domain through leaf switches in the bridge domain, and receiving multiple join requests from the connected host devices at the leaf switches. The IGMP snooping also includes consolidating the multiple join requests received at the leaf switches into a multicast groups membership repository to indicate for each leaf switch the multicast group membership of interest in the given bridge domain, and sending the repository to the border leaf switch to enable the border leaf switch to send a consolidated IGMP proxy report on behalf of the leaf switches to the multicast router based on the repository and that indicates the multicast membership of interest in the given bridge domain.

Abstract: Embodiments are provided for partially replicating endpoint routing information, and comprise calculating a first shard interval of a key space based, at least in part, on capacities of a plurality of spine nodes in a network fabric. Embodiments also include mapping the first shard interval to a first spine node of the plurality of spine nodes, communicating shard mapping information associated with the mapping to a set of leaf nodes in the network fabric, and populating an endpoint repository in the first spine node with routing information for one or more endpoints corresponding to the first shard interval. More specific embodiments include calculating respective shard intervals for other spine nodes of the plurality of spine nodes based, at least in part, on the capacities of the plurality of spine nodes. In specific embodiments, the calculating the first shard interval is based, in part, on one or more dynamic parameters.

Abstract: An example method for to inter-pod traffic redirection and handling in a multi-pod network environment is provided and includes receiving a packet with an overlay header outgoing from a first pod, identifying the packet as redirected based on a source address in the overlay header indicating a second pod and a destination address in the overlay header indicating a third pod, the first pod being distinct from the second pod and the third pod, setting a redirection bit in the overlay header tagging the packet as redirected, and transmitting the packet to the third pod.