Abstract: This document relates to automated generation of machine learning models, such as neural networks. One example method involves obtaining a first machine learning model having one or more first inference operations. The example method also involves identifying a plurality of second inference operations that are supported by an inference hardware architecture. The example method also involves generating second machine learning models by modifying the first machine learning model to include individual second inference operations that are supported by the inference hardware architecture. The example method also involves selecting a final machine learning model from the second machine learning models based on one or more metrics.

Abstract: Examples are disclosed that relate to a multi-port synchronous dynamic random access memory (SDRAM). One example provides a multi-port SDRAM comprising a first port, a second port, a first memory portion, and a second memory portion. At least the first memory portion is configured as shared such that the first memory portion is accessible at the first port and not the second port in a first mode, and the first memory portion is accessible at the second port and not the first port in a second mode. The multi-port SDRAM further comprises a mode controller controllable to selectively change the multi-port SDRAM between at least the first mode and the second mode.

Abstract: Examples are disclosed that relate to a multi-port synchronous dynamic random access memory (SDRAM). One example provides a multi-port SDRAM comprising a first port, a second port, a first memory portion, and a second memory portion. At least the first memory portion is configured as shared such that the first memory portion is accessible at the first port and not the second port in a first mode, and the first memory portion is accessible at the second port and not the first port in a second mode. The multi-port SDRAM further comprises a mode controller controllable to selectively change the multi-port SDRAM between at least the first mode and the second mode.

Abstract: Some demonstrative embodiments include apparatuses, systems and/or methods of establishing an Internet connection. For example, a server may perform operations including storing relay account information corresponding to at least one relay station to provide Internet access, and client account information of at least one client, the client account information comprising credit information indicating a credit balance of the client; processing a connection request received from a wireless station via the relay station, the connection request to request an Internet connection via the relay station, the connection request comprising a client identifier of the client; sending to the wireless station via the relay station connection establishment information to establish the Internet connection via the relay station; and updating the credit balance based on usage information from the relay station, the usage information indicating a usage of the Internet connection by the wireless station.

Abstract: Some demonstrative embodiments include apparatuses, systems and/or methods of establishing an Internet connection. For example, a server me perform operations including storing relay account information corresponding to least one relay station to provide Internet access, and client account information of at least one client, the client account information comprising credit information indicating a credit balance of the client; processing a connection request received from a wireless station via the relay station, the connection request to request an Internet connection via the relay station, the connection request comprising a client identifier of the client; sending to the wireless station via the relay station connection establishment information to establish the Internet connection via the relay station; and updating the credit balance based on usage information from the relay station, the usage information indicating a usage of the Internet connection by the wireless station.

Abstract: This disclosure relates to a serving entities control entity for controlling a communication network comprised of a plurality of communication clients which are connectable via a plurality of serving entities, the serving entities control entity comprising: a traffic monitor, configured to monitor data traffic of at least one transmission queue of each serving entity of the plurality of serving entities; and a serving entities controller, configured to allocate resources to each serving entity of the plurality of serving entities based on the monitored data traffic and according to quality of service requirements of each of the communication clients.

Abstract: Described herein are technologies related to an implementation of improving power and performance of a portable device by controlling background traffic of one or more device applications based upon a determined and measured radio link condition.

Abstract: A network controller of a communication network that serves one or more communication devices controls placement of one or more communication devices, such as a range extender, in the communication network. The network controller can control a communication device (e.g., a mobile device) and an access point serving the communication device to measure one or more wireless characteristics to generate first and second measurement information, respectively. The network controller can determine a placement score based on the first measurement information and the second measurement, and determine a placement location of the ranger extender within the communication network based on the placement score. The network controller can provide the placement location to the communication device and/or the range extender to indicate the placement location in which the range extender is to be positioned within the communication network.

Abstract: A communication manager of a communication network can include a transceiver configured to communicate with communication stations and one or more clients of the communication network, and a controller. The controller can be configured to: generate a management packet and provide, using the transceiver, the management packet to the communication stations to control the communication stations to monitor a communication from the client of the one or more clients and measure the client communication; obtain respective measurements from the communication stations using the transceiver; and control the client of the one or more clients to select a communication station from the communication stations to serve the client based on the respective measurements.

Abstract: A network controller of a communication network that serves one or more communication devices controls placement of one or more communication devices, such as a range extender, in the communication network. The network controller can control a communication device (e.g., a mobile device) and an access point serving the communication device to measure one or more wireless characteristics to generate first and second measurement information, respectively. The network controller can determine a placement score based on the first measurement information and the second measurement, and determine a placement location of the ranger extender within the communication network based on the placement score. The network controller can provide the placement location to the communication device and/or the range extender to indicate the placement location in which the range extender is to be positioned within the communication network.

Abstract: A communication manager of a communication network can include a transceiver configured to communicate with communication stations and one or more clients of the communication network, and a controller. The controller can be configured to: generate a management packet and provide, using the transceiver, the management packet to the communication stations to control the communication stations to monitor a communication from the client of the one or more clients and measure the client communication; obtain respective measurements from the communication stations using the transceiver; and control the client of the one or more clients to select a communication station from the communication stations to serve the client based on the respective measurements.

Abstract: Multi-layered video structures are scaled over a range of perceived quality levels. An estimated Mean Opinion Score (eMOS)-based encoder control loop is utilized to determine one or more encoder key performance index (KPI) associated with a particular perceived quality level. A KPI-based encoder control loop is then utilized to guide generation of a hierarchical structure having quality and/or temporal and/or spatial enhancement layers, without recalculating eMOS for the scalable structure. In addition, eMOS is used to guide the generation of a hierarchical structure at best-perceived quality levels for a given bitrate budget. Rate adaptation may occur by dropping segments, changing hierarchical structure, or changing the KPI target values. With the structure scaled as a function of perceived quality, perceived quality is impacted predictably as the encoding rate is adapted.

Abstract: Described herein are technologies related to an implementation of improving power and performance of a portable device by controlling background traffic of one or more device applications based upon a determined and measured radio link condition.

Abstract: Multi-layered video structures are scaled over a range of perceived quality levels. An estimated Mean Opinion Score (eMOS)-based encoder control loop is utilized to determine one or more encoder key performance index (KPI) associated with a particular perceived quality level. A KPI-based encoder control loop is then utilized to guide generation of a hierarchical structure having quality and/or temporal and/or spatial enhancement layers, without recalculating eMOS for the scalable structure. In addition, eMOS is used to guide the generation of a hierarchical structure at best-perceived quality levels for a given bitrate budget. Rate adaptation may occur by dropping segments, changing hierarchical structure, or changing the KPI target values. With the structure scaled as a function of perceived quality, perceived quality is impacted predictably as the encoding rate is adapted.