How Do Goroutines, User Threads, and Kernel Threads Interact in Go's Concurrency Model?-Golang-php.cn

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How Do Goroutines, User Threads, and Kernel Threads Interact in Go's Concurrency Model?

Linda Hamilton

Dec 11, 2024 am 01:55 AM

How Do Goroutines, User Threads, and Kernel Threads Interact in Go's Concurrency Model?

Goroutine and Thread Relationships in Operating System and User Space

Understanding Goroutine, User Thread, and Kernel Thread

When working with concurrency in Go, it's crucial to comprehend the distinctions between goroutines, user threads, and kernel threads. Goroutines are lightweight user threads managed by Go's runtime environment. User threads, in contrast, are implemented by the operating system and can interact directly with the kernel. Kernel threads, on the other hand, are managed entirely by the kernel and provide the lowest level of parallelism.

Goroutines Mapped to OS Threads

Go's scheduler utilizes a concept known as processor or scheduling context (P) to map multiple goroutines to multiple OS threads (M). The number of Ps defaults to the number of CPUs detected by Go, but this can be adjusted using the GOMAXPROCS environment variable. This mapping ensures that goroutines can efficiently utilize available CPU resources without creating an excessive number of kernel threads.

Number of Kernel Threads

The number of kernel threads generated by the operating system depends on the requirements of the running programs. Kernel threads are created as needed to handle system tasks and execute user-initiated processes. Therefore, the number of kernel threads can vary dynamically based on system load and the number of concurrent processes.

Implications for Concurrency

While goroutines provide a user-friendly abstraction for concurrency, it's important to remember that they are still constrained by the underlying operating system resources. Even though Go programs may utilize all available CPUs, other system processes will still have access to CPU time, due to the kernel's scheduling algorithm. This is especially important to consider when developing highly concurrent applications that require a consistent level of performance.

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