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On Linux, the CPU affinity of a process can be altered with the taskset(1) program [3] and the sched_setaffinity(2) system call. The affinity of a thread can be altered with one of the library functions: pthread_setaffinity_np(3) or pthread_attr_setaffinity_np(3). On SGI systems, dplace binds a process to a set of CPUs. [4]
In computer science, The System Contention Scope [1] is one of two thread-scheduling schemes used in operating systems.This scheme is used by the kernel to decide which kernel-level thread to schedule onto a CPU, wherein all threads (as opposed to only user-level threads, as in the Process Contention Scope scheme) in the system compete for the CPU. [2]
In computer programming, thread-local storage (TLS) is a memory management method that uses static or global memory local to a thread. The concept allows storage of data that appears to be global in a system with separate threads. Many systems impose restrictions on the size of the thread-local memory block, in fact often rather tight limits.
In a traditional CPU, each process – a program in execution – uses the various CPU registers to store data and hold the current state of the running process. However, in a multitasking operating system, the operating system switches between processes or threads to allow the execution of multiple processes simultaneously. [ 2 ]
A process with two threads of execution, running on one processor Program vs. Process vs. Thread Scheduling, Preemption, Context Switching. In computer science, a thread of execution is the smallest sequence of programmed instructions that can be managed independently by a scheduler, which is typically a part of the operating system. [1]
Schematic representation of how threads work under GIL. Green - thread holding GIL, red - blocked threads. A global interpreter lock (GIL) is a mechanism used in computer-language interpreters to synchronize the execution of threads so that only one native thread (per process) can execute basic operations (such as memory allocation and reference counting) at a time. [1]
The non-Python library being called to perform the CPU-intensive task is not subject to the GIL and may concurrently execute many threads on multiple processors without restriction. Concurrency of Python code can only be achieved with separate CPython interpreter processes managed by a multitasking operating system .
A task (i.e., a synonym for thread) is the minimal entity that Linux can schedule. However, it can also manage groups of threads, whole multi-threaded processes, and even all the processes of a given user. This design leads to the concept of schedulable entities, where tasks are grouped and managed by the scheduler as a whole.