Abstract: Query processing systems and methods are disclosed herein. In an example system, query information is received over a network for processing a query. A first processing architecture loads a set of data associated with the query into a shared memory. A second processing architecture accesses the set of data from the shared memory. In one example, the first and second processing architectures and the shared memory are integrated in a hardware chip (e.g., a chiplet containing several processor architectures, such as CPU and a graphics processing unit (GPU)). The query is processed based on the set of data accessed from the shared memory using the second processing architecture to generate a query result. The query result is provided over the network. In this manner, a computing device may execute a query based on different processing systems contained therein.

Abstract: A user interface automatically retrieves the preference of a user when a user interacts with a system by detecting his/her image and matching the user image database. The image database stores the physical features of users of a system, which can differentiate between the users of the system. A user registration method transparently registers user into the image database through clustering using learned distance metric from user images. A method of learning a distance metric identifies pair-wise constraints from data points and maximizes the margin between the distances of a first set of pairs and a second set of pairs, which can be further solved via semi-positive definite programming.