Abstract: The disclosure provides an approach for gateway optimization. Embodiments include receiving, at a first gateway associated with a first tenant within a data center, a packet directed to a first public network address of an endpoint associated with a second tenant within the data center. Embodiments include performing, by the first gateway, network address translation (NAT) to translate the first public network address to a private network address of the endpoint. Embodiments include forwarding, by the first gateway, the packet to an edge gateway of the data center. Embodiments include forwarding, by the edge gateway, the packet to a second gateway associated with the second tenant within the data center without sending the packet to a public interface of the edge gateway. Embodiments include forwarding, by the second gateway, the packet to the endpoint.

Abstract: Some embodiments provide a novel method for configuring edge routers in a first network. The method configures on a first compute node of the first network (1) a first higher-level edge router and (2) a set of lower-level edge routers. Each lower-level edge router is configured for a different set of subnetworks defined in the first network and is connected to an external second network through the first higher-level edge router. The method detects a condition that requires a particular lower-level edge router for a particular subnetwork to be moved to another compute node. The method configures the particular lower-level edge router to operate on a second compute node below a second higher-level edge router operating on the second compute node to connect the particular lower-level edge router to the external second network.

Abstract: Example methods and systems for connectivity service provisioning for a software-defined data center (SDDC) group are described. In one example, a computer system may detect an event that affects a first connectivity service connecting multiple members of the SDDC group. The computer system may obtain first routing information that is applicable in a first SDDC; and second routing information that is applicable in a second SDDC. In response to the event, the computer system may generate and send a first instruction towards the first SDDC and a second instruction towards the second SDDC to cause: (a) the first SDDC and second SDDC to establish a second connectivity service; (b) the first SDDC to update the first routing information to associate a first flow with the second connectivity service; and (c) the second SDDC to update the second routing information to associate a second flow with the second connectivity service.

Abstract: Some embodiments provide a novel method for dynamically deploying gateways for a first network connecting machines. The first network includes segments, routers, and a first gateway that connects to an external network. The method identifies a set of two or more segments that consumes more than a threshold amount of bandwidth of the first gateway. The identified set includes at least first and second segments. The method identifies one or more segment groups by aggregating two or more segments in the identified set. A first segment group includes the first and second segments and a third segment that is not in the identified set of two or more segments. The method configures a second gateway to process flows associated with each identified group including the first group. The method configures a set of routers to forward flows from machines of each segment of each identified group to the second gateway.

Abstract: A method is described which includes receiving a number of object images of an object. Each object image corresponds to a different view direction. First and second object images correspond to first and second directions. A mesh is determined corresponding to the target region of the object surface based on a first subset of the number of object images. Diffuse and specular maps are determined corresponding to the target region of the object surface based on processing a second subset of the object images using a deep learning neural network model trained to estimate diffuse and specular albedo components based on an input image. A tangent normal map is determined corresponding to the target region of the object surface based on high-pass filtering each object image of the second subset. The method also includes storing and/or outputting the mesh, the diffuse map, the specular map and the tangent normal map.

Abstract: Solutions for data unification include: receiving a data record, the data record comprising a plurality of data fields; selecting, from among the plurality of data fields, a subset of the data fields, the subset of the data fields being fewer in number than the plurality of data fields, wherein selecting the subset of the data fields comprises: applying a first rule to select at least a first one of the data fields within the data record for inclusion in the subset of the data fields; using content of the subset of the data fields, generating a stable identifier (stableID) for the data record; and inserting the stableID into a primary key data field of the data record.

Abstract: Solutions for data unification include: receiving a data record, the data record comprising a plurality of data fields; selecting, from among the plurality of data fields, a subset of the data fields, the subset of the data fields being fewer in number than the plurality of data fields, wherein selecting the subset of the data fields comprises: applying a first rule to select at least a first one of the data fields within the data record for inclusion in the subset of the data fields; using content of the subset of the data fields, generating a stable identifier (stableID) for the data record; and inserting the stableID into a primary key data field of the data record.