Search results
Results From The WOW.Com Content Network
The running time of LPT is dominated by the sorting, which takes O(n log n) time, where n is the number of inputs. LPT is monotone in the sense that, if one of the input numbers increases, the objective function (the largest sum or the smallest sum of a subset in the output) weakly increases. [2] This is in contrast to Multifit algorithm.
Interval scheduling is a class of problems in computer science, particularly in the area of algorithm design. The problems consider a set of tasks. Each task is represented by an interval describing the time in which it needs to be processed by some machine (or, equivalently, scheduled on some resource).
Busy-waiting itself can be made much less wasteful by using a delay function (e.g., sleep()) found in most operating systems. This puts a thread to sleep for a specified time, during which the thread will waste no CPU time. If the loop is checking something simple then it will spend most of its time asleep and will waste very little CPU time.
Earliest deadline first (EDF) or least time to go is a dynamic priority scheduling algorithm used in real-time operating systems to place processes in a priority queue. Whenever a scheduling event occurs (task finishes, new task released, etc.) the queue will be searched for the process closest to its deadline.
In computer programming, a callback is a function that is stored as data (a reference) and designed to be called by another function – often back to the original abstraction layer. A function that accepts a callback parameter may be designed to call back before returning to its caller which is known as synchronous or blocking.
The task with the highest priority for which all dependent tasks have finished is scheduled on the worker which will result in the earliest finish time of that task. This finish time depends on the communication time to send all necessary inputs to the worker, the computation time of the task on the worker, and the time when that processor ...
Objective function can be to minimize the makespan, the L p norm, tardiness, maximum lateness etc. It can also be multi-objective optimization problem. Jobs may have constraints, for example a job i needs to finish before job j can be started (see workflow). Also, the objective function can be multi-criteria. [4]
Prefix sums are trivial to compute in sequential models of computation, by using the formula y i = y i − 1 + x i to compute each output value in sequence order. However, despite their ease of computation, prefix sums are a useful primitive in certain algorithms such as counting sort, [1] [2] and they form the basis of the scan higher-order function in functional programming languages.