Abstract: Duration information indicative of an amount of time taken by each of one or more tasks of a distributed compute phase of a distributed compute job in a distributed compute cluster to execute is obtained. The one or more tasks are sorted into one or more groups based on the duration information and a resource requirement is determined for each of the one or more groups. A time-varying allocation of resources of the distributed compute cluster for the phase is determined based on the resource requirement for each of the one or more groups.

Abstract: A first quality of service identifier is assigned to each subtask associated with each node of a compute workflow, the first quality of service identifier indicative of a level of quality of service associated with each node. A planned resource requirement is assigned to each subtask, the planned resource requirement indicative of a total amount of system resources required to complete each subtask. A resource allocation plan is generated for each subtask, the resource allocation plan indicative of a distribution of the system resources over time in at least one resource manager. The resource allocation plan and the first quality of service identifier are output to the at least one resource manager for enforcement of the level of quality of service on one or more jobs submitted for each node through at least one workflow orchestrator external to the at least one resource manager.

Abstract: Duration information indicative of an amount of time taken by each of one or more tasks of a distributed compute phase of a distributed compute job in a distributed compute cluster to execute is obtained. The one or more tasks are sorted into one or more groups based on the duration information and a resource requirement is determined for each of the one or more groups. A time-varying allocation of resources of the distributed compute cluster for the phase is determined based on the resource requirement for each of the one or more groups.

Abstract: Processes, systems, and devices for occlusion detection for video-based object tracking (VBOT) are described herein. Embodiments process video frames to compute histogram data and depth level data for the object to detect a subset of video frames for occlusion events and generate output data that identifies each video frame of the subset of video frames for the occlusion events. Threshold measurement values are used to attempt to reduce or eliminate false positives to increase processing efficiency.

Abstract: A first quality of service identifier is assigned to each subtask associated with each node of a compute workflow, the first quality of service identifier indicative of a level of quality of service associated with each node. A planned resource requirement is assigned to each subtask, the planned resource requirement indicative of a total amount of system resources required to complete each subtask. A resource allocation plan is generated for each subtask, the resource allocation plan indicative of a distribution of the system resources over time in at least one resource manager. The resource allocation plan and the first quality of service identifier are output to the at least one resource manager for enforcement of the level of quality of service on one or more jobs submitted for each node through at least one workflow orchestrator external to the at least one resource manager.

Abstract: Processes, systems, and devices for occlusion detection for video-based object tracking (VBOT) are described herein. Embodiments process video frames to compute histogram data and depth level data for the object to detect a subset of video frames for occlusion events and generate output data that identifies each video frame of the subset of video frames for the occlusion events. Threshold measurement values are used to attempt to reduce or eliminate false positives to increase processing efficiency.