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Real-time computing (RTC) is the computer science term for hardware and software systems subject to a "real-time constraint", for example from event to system response. [1] Real-time programs must guarantee response within specified time constraints, often referred to as "deadlines".
A simple version of rate-monotonic analysis assumes that threads have the following properties: No resource sharing (processes do not share resources, e.g. a hardware resource, a queue, or any kind of semaphore blocking or non-blocking ())
In computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views streams, or sequences of events in time, as the central input and output objects of computation.
This is a list of real-time operating systems (RTOSs). This is an operating system in which the time taken to process an input stimulus is less than the time lapsed until the next input stimulus of the same type.
The actor model in computer science is a mathematical model of concurrent computation that treats an actor as the basic building block of concurrent computation. In response to a message it receives, an actor can: make local decisions, create more actors, send more messages, and determine how to respond to the next message received.
A sample UML class and sequence diagram for the observer design pattern. [6] In this UML class diagram, the Subject class does not update the state of dependent objects directly. Instead, Subject refers to the Observer interface (update()) for updating state, which makes the Subject independent of how the state of dependent objects is updated.
Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.
Earliest deadline first (EDF) or least time to go is a dynamic scheduling algorithm used in real-time operating systems to place processes in a priority queue. Whenever a scheduling event occurs (a task finishes, new task is released, etc.), the queue will be searched for the process closest to its deadline, which will be the next to be ...