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CPU time (or process time) is the amount of time that a central processing unit (CPU) was used for processing instructions of a computer program or operating system. CPU time is measured in clock ticks or seconds. Sometimes it is useful to convert CPU time into a percentage of the CPU capacity, giving the CPU usage.
Delta time or delta timing is a concept used amongst programmers in relation to hardware and network responsiveness. [1] In graphics programming, the term is usually used for variably updating scenery based on the elapsed time since the game last updated, [2] (i.e. the previous "frame") which will vary depending on the speed of the computer, and how much work needs to be done in the program at ...
In theoretical computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to ...
Minimizing the depth/span is important in designing parallel algorithms, because the depth/span determines the shortest possible execution time. [8] Alternatively, the span can be defined as the time T ∞ spent computing using an idealized machine with an infinite number of processors. [9] The cost of the computation is the quantity pT p. This ...
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.
This change to lazy evaluation saves execution time for large ranges which may never be fully referenced and memory usage for large ranges where only one or a few elements are needed at any time. In Python 2.x is possible to use a function called xrange() which returns an object that generates the numbers in the range on demand.
T is the execution time of the task; W is the execution workload of the task. Throughput of an architecture is the execution rate of a task: = = =, where ρ is the execution density (e.g., the number of stages in an instruction pipeline for a pipelined architecture);
Flow Shop Ordonnancement. Flow-shop scheduling is an optimization problem in computer science and operations research.It is a variant of optimal job scheduling.In a general job-scheduling problem, we are given n jobs J 1, J 2, ..., J n of varying processing times, which need to be scheduled on m machines with varying processing power, while trying to minimize the makespan – the total length ...