Abstract: The present disclosure relates to systems and methods to implement efficient high-bandwidth shared memory systems particularly suited for parallelizing and operating large scale machine learning and AI computing systems necessary to efficiently process high volume data sets and streams.

Abstract: The present disclosure relates to systems and methods to implement efficient high-bandwidth shared memory systems particularly suited for parallelizing and operating large scale machine learning and AI computing systems necessary to efficiently process high volume data sets and streams.

Abstract: Systems and methods for fully-automated contact-less biometric measurement include receiving a stream of image frames from an internet capable device. Frame data is extracted from the stream of image frames. A predictive load balancer selects a worker server based on a load prediction. An interface delivery server communicates the frame data from the internet capable device to the worker server. A set of patient face images captured by the frame data are extracted. A facial recognition machine learning model determines a patient identity associated with the set of patient face images of the frame data. A shared memory system stores the set of patient face images. The worker server determines biometric measurements based on the set of patient face images in the shared memory system using independent biometric data processing pipelines with shared access to the shared memory system for inter-process communication.

Abstract: Systems and methods for fully-automated contact-less biometric measurement include receiving a stream of image frames from an internet capable device. Frame data is extracted from the stream of image frames. A predictive load balancer selects a worker server based on a load prediction. An interface delivery server communicates the frame data from the internet capable device to the worker server. A set of patient face images captured by the frame data are extracted. A facial recognition machine learning model determines a patient identity associated with the set of patient face images of the frame data. A shared memory system stores the set of patient face images. The worker server determines biometric measurements based on the set of patient face images in the shared memory system using independent biometric data processing pipelines with shared access to the shared memory system for inter-process communication.

Abstract: The present disclosure relates to systems and methods to implement efficient high-bandwidth shared memory systems particularly suited for parallelizing and operating large scale machine learning and AI computing systems necessary to efficiently process high volume data sets and streams.