Task (computing)

About: Task (computing) is a research topic. Over the lifetime, 9718 publications have been published within this topic receiving 129364 citations.

Recognizing Assembly Tasks Through Human Demonstration

Abstract: As one of the methods for reducing the work of programming, the Learning-from-Observation (LFO) paradigm has been heavily promoted. This paradigm requires the programmer only to perform a task in front of a robot and does not require expertise. In this paper, the LFO paradigm is applied to assembly tasks by two rigid polyhedral objects. A method is proposed for recognizing these tasks as a sequence of movement primitives from noise-contaminated data obtained by a conventional 6 degree-of-freedom (DOF) object-tracking system. The system is implemented on a robot with a real-time stereo vision system and dual arms with dexterous hands, and its effectiveness is demonstrated.

The Natural Work-Stealing Algorithm is Stable

Abstract: In this paper we analyse a very simple dynamic workstealing algorithm. In the work-generation model, there are n generators which are arbitrarily distributed among a set of n processors. During each time-step, with probability \lambda, each generator generates a unit-time task which it inserts into the queue of its host processor. After the new tasks are generated, each processor removes one task from its queue and services it. Clearly, the work-generation model allows the load to grow more and more imbalanced, so, even when \lambda < 1, the system load can be unbounded.The natural work-stealing algorithm that we analyse works as follows. During each time step, each empty processor sends a request to a randomly selected other processor. Any non-empty processor having received at least one such request in turn decides (again randomly) in favour of one of the requests. The number of tasks which are transferred from the non-empty processor to the empty one is determined by the so-called work-stealing function f.We analyse the long-term behaviour of the system as a function of \lambda and f. We show that the system is stable for any constant generation rate \lambda < 1 and for a wide class of functions f. We give a quantitative description of the functions f which lead to stable systems. Furthermore, we give upper bounds on the average system load (as a function of f and n).

Methods, systems and computer program products for automatic task distribution

Abstract: Methods, systems and computer program products are provided which automatically distribute tasks associated with a telephone system and tasks associated with a computer system between a plurality of agents tracking ACD telephone status of the plurality of agents and tracking computer status of the plurality of agents. When a request for a computer task is received, an agent of the plurality of agents is assigned to the computer task corresponding to the received request based on the ACD telephone status and the computer status of the agent of the plurality of agents.

Method and apparatus for merging sorted lists in a multiprocessor shared memory system

Abstract: A system and method for merging a plurality of sorted lists using multiple processors having access to a common memory in which N sorted lists which may exceed the capacity of the common memory are merged in a parallel environment. Sorted lists from a storage device are loaded into common memory and are divided into a number of tasks equal to the number of available processors. The records assigned to each task are separately sorted, and used to form a single sorted list. A multi-processing environment takes advantage of its organization during the creation of the tasks, as well as during the actual sorting of the tasks.

Task queuing in a network communications processor architecture

Abstract: Described embodiments provide a method of assigning tasks to queues of a processing core. Tasks are assigned to a queue by sending, by a source processing core, a new task having a task identifier. A destination processing core receives the new task and determines whether another task having the same identifier exists in any of the queues corresponding to the destination processing core. If another task with the same identifier as the new task exists, the destination processing core assigns the new task to the queue containing a task with the same identifier as the new task. If no task with the same identifier as the new task exists in the queues, the destination processing core assigns the new task to the queue having the fewest tasks. The source processing core writes the new task to the assigned queue. The destination processing core executes the tasks in its queues.