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Concept
Green thread
Summary
In computer programming, a green thread (virtual thread) is a thread that is scheduled by a runtime library or virtual machine (VM) instead of natively by the underlying operating system (OS). Green threads emulate multithreaded environments without relying on any native OS abilities, and they are managed in user space instead of kernel space, enabling them to work in environments that do not have native thread support.
Green threads refers to the name of the original thread library for the programming language Java (that was released in version 1.1 and then Green threads were abandoned in version 1.3 to native threads). It was designed by The Green Team at Sun Microsystems.
Green threads were briefly available in Java between 1997 and 2000.
Green threads share a single operating system thread through co-operative concurrency and can therefore not achieve parallelism performance gains like operating system threads. The main benefit of coroutines and green threads is ease of implementation.
On a multi-core processor, native thread implementations can automatically assign work to multiple processors, whereas green thread implementations normally cannot. Green threads can be started much faster on some VMs. On uniprocessor computers, however, the most efficient model has not yet been clearly determined.
Benchmarks on computers running the Linux kernel version 2.2 (released in 1999) have shown that:
Green threads significantly outperform Linux native threads on thread activation and synchronization.
Linux native threads have slightly better performance on input/output (I/O) and context switching operations.
When a green thread executes a blocking system call, not only is that thread blocked, but all of the threads within the process are blocked. To avoid that problem, green threads must use asynchronous I/O operations, although the increased complexity on the user side can be reduced if the virtual machine implementing the green threads spawns specific I/O processes (hidden to the user) for each I/O operation.
Official source
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