Implementation of goroutines

I have been reading up on concurrency in Go. In particular, I have been wondering about the statement from a presentation by Brad Fitzpatrick:
n, err := io.Copy(dst, src)

copies n bytes from dst to src
synchronous (blocks)
Go runtime deals with making blocking efficient

In virtually all languages I have worked with (Java, Scala, javascript, ...), a call that blocks the execution of the current function also blocks the current thread. The only exception is C# with its rather complex async/await feature implemented in the compiler.

Now in Go, if you make a call that blocks the current execution, you are (usually) only blocking the current goroutine, not a thread. The Go runtime multiplexes goroutines on fewer OS threads.

The question therefore is: What are the fundamental differences in the implementation of goroutines compared to OS threads that make goroutines so much more lightweight?

I have asked this question on the Go mailing list and the members of the Go team (notably Dmitry Vyukov and Ian Lance Taylor) have been incredibly helpful.

The summary is:

stack that grows and shrinks on demand
smaller context, easier to switch
cooperative scheduling at known points is less work (can make assumptions about CPU state)
scheduling in user space

Here is the discussion: enjoy!

Note: There are other languages (such as Haskell and Erlang) that also have the concept of lightweight "processes" that allow for blocking calls without blocking OS threads. The concept is sometimes referred to as green threads.

Posted by Martin Konicek on 11:21 AM

203 comments:

«Oldest ‹Older 1 – 200 of 203 Newer› Newest»

Pedro Pedruzzi said...: Thanks for the nice post about go's novel approach to concurrency. It is awesome that go seem to have implemented this very efficiently and it is automatically used on the most frequent blocking situations: socket operations and locking (eg. using in-memory message queues)

It's worth mentioning that this concept is also known as fibers or lightweight threads. Some related links:
await implementation for Java:
https://github.com/electronicarts/ea-async
Fiber implementation for the JVM
http://docs.paralleluniverse.co/quasar/
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Martin Konicek said...: Those are very good links, thank you Pedro! Ah yes, I remember hearing the name fibers too. I've been recently using the Hack language at fb which has the async / await feature similar to C#. My guess is the Hack runtime / libraries do something similar to Go under the hood, you can e.g. spawn a 1000 async operations and await all of them.; August 3, 2016 at 10:32 AM
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IIM Skills(Neha Tiwari) said...: Great explanation of how goroutines differ from OS threads—lightweight, efficient, and perfect for concurrency in Go! Thanks for sharing this insight.

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IIM Skills said...: Your explanation of Goroutines is both concise and insightful. Concurrency can be tricky for newcomers, but you’ve made it approachable by combining code snippets with clear reasoning on why Goroutines are efficient. The discussion on how they differ from traditional threads, and how Go’s scheduler handles them, adds great value for developers looking to scale applications. I particularly appreciated the examples on channel communication — that’s where many tutorials fall short, but you nailed it. It’s refreshing to see real-world coding practices explained in such a simple manner without skipping over the underlying concepts.
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Sohail Digi said...: The concept of lightweight goroutines with dynamically growing stacks and user-space scheduling truly sets Go apart from traditional thread-based models. I especially appreciate the point about cooperative scheduling—it's fascinating how the Go runtime can make smart assumptions about the CPU state at known blocking points, making context switches so much cheaper. It’s clear why Go is such a great fit for highly concurrent applications. Thanks for sharing the insights from the mailing list—super helpful!

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Nilabh said...: This article provides a comprehensive explanation of how Go's goroutines differ from traditional OS threads, highlighting their lightweight nature and efficient scheduling. The insights into stack management and cooperative scheduling offer a deeper understanding of Go's concurrency model. A must-read for developers looking to optimize concurrent programming in Go.
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IIM Skills said...: The implementation of goroutines in Go is such an important concept when it comes to writing efficient, concurrent programs. Your explanation here is simple yet powerful. Goroutines allow developers to handle multiple tasks simultaneously without blocking the main execution, which is a huge plus for building scalable systems. This blog will definitely help developers looking to move from synchronous to concurrent programming, especially in backend or systems development.
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Nilabh said...: "This post offers a clear explanation of Go's lightweight goroutines, highlighting their efficiency through features like dynamic stack sizes and user-space scheduling. A valuable read for concurrency enthusiasts.
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umangv maneuvers said...: This article provides a clear explanation of Go’s goroutine implementation and how it differs from threads in languages like Java. I appreciate how you explain that goroutines have lightweight stacks that grow and shrink dynamically and that the runtime multiplexes many goroutines onto a few OS threads. The discussion on how blocking calls yield the goroutine while the runtime monitors events shows why Go’s concurrency is efficient. Thanks for summarizing the key points in such a straightforward way. financial modeling courses in delhi; August 14, 2025 at 10:17 AM
IIM Skills(Shreya Saha) said...: Really nice summary of why goroutines feel “cheap” compared to OS threads. The points about segmented/growing stacks and user-space scheduling capture most of the magic, and the “known yield points” bit explains why context switches can be so fast. It might be worth calling out how the runtime’s netpoller lets many goroutines block on I/O without tying up threads, and how true blocking syscalls (or cgo) can still consume an OS thread. Overall, great primer that connects the theory to what we feel when writing Go.
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IIM Skills(Shreya Saha) said...: This is a very clear and concise explanation of why goroutines are so much lighter than OS threads. The breakdown of stack management, context switching, and user-space scheduling really highlights the elegance of Go’s design. Great summary, thanks for sharing the mailing list discussion too—it makes the concepts much easier to grasp!
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iim.skills said...: This post gives a simple look at how Go uses goroutines to handle concurrency. It shows how lightweight they are by pointing out features like dynamic stack sizes and user-space scheduling. The explanation makes their efficiency easy to see and offers clear value for anyone interested in writing faster, scalable programs.
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indu said...: Great explanation of goroutines! I like how you broke down their lightweight nature compared to traditional threads. It’s impressive how Go manages concurrency so efficiently through the scheduler, making it easy to scale applications without complex thread management. Looking forward to seeing more examples on how goroutines work with channels in real-world use cases.”
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Generativeaimasters said...: “Thank you for this clear and deep dive into how goroutines work. Your breakdown of stack growth, lightweight scheduling, and user-space multiplexing makes the concept accessible. This post really helps bridge theory and practice in Go’s concurrency model.

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littu said...: Thanks for writing this — your explanation of how goroutines are implemented under the hood (stack that grows/shrinks, user-space scheduling, etc.) is really clear and enlightening. It’s exactly what helps when you’re trying to grasp why Go’s concurrency model is so lightweight compared to OS threads. For anyone balancing their Go learning with other study goals, I also recommend checking out sat coaching online from Fast Prep Academy.; November 23, 2025 at 7:24 PM
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Coding time - Martin Konicek

Implementation of goroutines

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