Directing a video player to a video source is disclosed. An indication that a client requires video streaming instructions is received. A past download performance for a plurality of clients that or correlated to the client requiring video streaming instructions is determined. At least one of: a content source, and a bitrate, is selected, based at least in part on the determined past download performance of the plurality of correlated clients. The client is provided with instructions based at least in part on the selection.

Source assignment based on network partitioning

Provided are a multimedia data processing system and a selective caching method. The selective caching method in the multimedia data processing system includes inserting cacheability indicator information into an address translation table descriptor undergoing memory allocation to a graphics resource when the graphics resource needs to be cached and selectively controlling whether or not to prefetch multimedia data of the graphics resource present in a main memory to a system level cache memory, with reference to cacheability indicator information during an address translation operation of a graphic processing unit (GPU). The inventive concept can be implemented in a wide variety of computer-based systems having a graphical output, such as cell phones, laptops, tablets, and personal computers, as only a few examples.

Method for caching gpu data and data processing system therefor

The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. In some embodiments, the IRIS comprises or consists of one of more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicle onboard unit (OBU), (4) traffic operations centers (TOCs), and (5) cloud information and computing services. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.

Intelligent road infrastructure system (iris): systems and methods

An intersection information acquisition unit acquires detection information by an object detection sensor including at least one of a vehicle detection sensor and a human detection sensor. A support processor performs driving support processing for outputting an alarm when the support processor determines that an own vehicle intends to cross the opposite lane and determines based on the acquired detection information that an object exists or the object is approaching in a direction in which the own vehicle travels to cross the opposite lane at the intersection. The support processor performs the driving support processing when the intersection information acquisition unit acquires detection information by the vehicle detection sensor. On the other hand, the support processor does not perform the driving support processing when the intersection information acquisition unit acquires detection information by the human detection sensor and does not acquire detection information by the vehicle detection sensor.

Driving support device

A system on chip (SoC) having an integrated circuit (IC) integrating into a single chip advance driver assistance systems (ADAS) processing unit(s), application processing unit(s), at least one memory storing ADAS code comprising ADAS computer instructions adapted to be executed on the ADAS processing unit(s) for processing vehicle sensor data and VM code for executing VM(s) on the application processing unit(s) and a hypervisor which manages an execution of at least one operation system of the VM(s) and an access to a processor shared memory of the ADAS processing unit(s) for acquiring an outcome of executing the ADAS computer instructions for the completion of an ADAS enhancing function by the execution of the VM(s) on the application processing unit(s).

Enhanced advanced driver assistance system (adas) system on chip

A vehicle interface system includes a graphics processing unit and a plurality of processing domains. The processing domains execute vehicle applications and generate tasks for the graphics processing unit. The system further includes a task scheduler configured to receive the tasks generated by the processing domains and to determine an order in which to send the tasks to the graphics processing unit. The graphics processing unit processes the tasks in the order determined by the task scheduler and generates display data based on the tasks. The system further includes an electronic display configured to receive the display data generated by the graphics processing unit and to present the display data to a user.

Markus Pabst

Papers

Vehicle with multiple user interface operating domains