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Conceptually, it is similar to cooperative multi-tasking used in real-time operating systems, in which tasks voluntarily give up execution time when they need to wait upon some type of event. This type of multithreading is known as block, cooperative or coarse-grained multithreading.
One of the earliest examples of a barrel processor was the I/O processing system in the CDC 6000 series supercomputers. These executed one instruction (or a portion of an instruction) from each of 10 different virtual processors (called peripheral processors or PPs) before returning to the first processor. [1]
Soft real-time systems are typically used to solve issues of concurrent access and the need to keep a number of connected systems up-to-date through changing situations. Some examples of soft real-time systems: Software that maintains and updates the flight plans for commercial airliners. The flight plans must be kept reasonably current, but ...
Coarse-grain multithreading is more common for less context switch between threads. For example, Intel's Montecito processor uses coarse-grained multithreading, while Sun's UltraSPARC T1 uses fine-grained multithreading. For those processors that have only one pipeline per core, interleaved multithreading is the only possible way, because it ...
For example, concurrent processes can be executed on one core by interleaving the execution steps of each process via time-sharing slices: only one process runs at a time, and if it does not complete during its time slice, it is paused, another process begins or resumes, and then later the original process is resumed. In this way, multiple ...
Single instruction, multiple threads (SIMT) is an execution model used in parallel computing where single instruction, multiple data (SIMD) is combined with multithreading. It is different from SPMD in that all instructions in all "threads" are executed in lock-step.
In the early days of computing, CPU time was expensive, and peripherals were very slow. When the computer ran a program that needed access to a peripheral, the central processing unit (CPU) would have to stop executing program instructions while the peripheral processed the data.
Simultaneous and heterogeneous multithreading (SHMT) is a software framework that takes advantage of heterogeneous computing systems that contain a mixture of central processing units (CPUs), graphics processing units (GPUs), and special purpose machine learning hardware, for example Tensor Processing Units (TPUs).
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