Task (computing) in the context of Preemption (computing)

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalise to unseen data, and thus perform tasks without explicit instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance.

ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics.

In computing, scheduling is the action of assigning resources to perform tasks. The resources may be processors, network links or expansion cards. The tasks may be threads, processes or data flows.

The scheduling activity is carried out by a mechanism called a scheduler. Schedulers are often designed so as to keep all computer resources busy (as in load balancing), allow multiple users to share system resources effectively, or to achieve a target quality-of-service.

In computers, lag is delay (latency) between the action of the user (input) and the reaction of the server supporting the task, which has to be sent back to the client.

The player's ability to tolerate lag depends on the type of game being played. For instance, a strategy game or a turn-based game with a slow pace may have a high threshold or even be mostly unaffected by high lag. A game with twitch gameplay such as a first-person shooter or a fighting game with a considerably faster pace may require a significantly lower lag to provide satisfying gameplay.

In computing, preemption is the act performed by an external scheduler — without assistance or cooperation from the task — of temporarily interrupting an executing task, with the intention of resuming it at a later time. This preemptive scheduler usually runs in the most privileged protection ring, meaning that interruption and then resumption are considered highly secure actions. Such changes to the currently executing task of a processor are known as context switching.

In computing, load balancing is the process of distributing a set of tasks over a set of resources (computing units) with the aim of making their overall processing more efficient. Load balancing can optimize response time and avoid unevenly overloading some compute nodes while other compute nodes are left idle.

Load balancing is the subject of research in the field of parallel computers. Two main approaches exist: static algorithms, which do not take into account the state of the different machines, and dynamic algorithms, which are usually more general and more efficient but require exchanges of information between the different computing units, at the risk of a loss of efficiency.