Programming Language Support
Many programming languages support threading in some capacity. Many implementations of C and C++ provide support for threading on their own, but also provide access to the native threading APIs provided by the operating system. Some higher level (and usually cross platform) programming languages such as Java, Python, and .NET, expose threading to the developer while abstracting the platform specific differences in threading implementations in the runtime to the developer. A number of other programming languages also try to abstract the concept of concurrency and threading from the developer altogether (Cilk, OpenMP, MPI). Some languages are designed for parallelism (Ateji PX, CUDA).
A few interpreted programming languages such as Ruby and (the CPython implementation of) Python support threading, but have a limitation that is known as a Global Interpreter Lock (GIL). The GIL is a mutual exclusion lock held by the interpreter that can prevent the interpreter from concurrently interpreting the applications code on two or more threads at the same time, which effectively limits the concurrency on multiple core systems (mostly for processor-bound threads, and not much for network-bound ones).
Event-driven programming hardware description languages like Verilog have a different threading model which supports extremely large numbers of threads (for modeling hardware).
Read more about this topic: Thread (computing)
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