Runtime System

Scheduler Activations

  • Instead of relying on the Kernel for every thread management decision, the Runtime System is responsible for scheduling Thread
  • Mitigates inefficiency from Kernel


  • User Thread managed by the Go runtime. This design decision allows goroutines to be lightweight(2kb) and efficiently multiplexed onto a smaller number of Kernel Thread
  • The Go runtime scheduler handles the mapping of goroutines to kernel threads, utilizing techniques like multiplexing and asynchronous I/O to optimize performance
  • Refer to here for more information

Spinning up Goroutine

  • go <function_call> - creates a User Thread managed by Go runtime
  • The program below simulates retrieving data from a Database. Each retrieval takes 500ms. But the total execution time is around 10µs. Continue reading to find out why :). You can remove the go keyword to see the performance boost goroutine brings

Program exits before other goroutines finish!

We need to introduce Synchronization (同步) mechanism here to ensure the program only exists when all other goroutines finish running. Uncomment the code blocks in the editor above to add in the synchronization mechanism.

sync.WaitGroup - a Synchronization mechanism used to coordinate the completion of multiple goroutines. It acts like a counter that multiple goroutines can interact with.

Add(int) - increments the counter by a specified value, indicating the number of goroutines you will be waiting for

Done() - decrements the counter. Used by each goroutine when it finishes

Wait() - blocks the current goroutine until the counter reaches zero, signaling that all tracked goroutines have completed

Regarding the performance gainz

The above example shows a significant performance gainz - 5 iterations that take 500ms each finish in 500ms! If you increase the number of iterations, it should still complete in about 500ms. Give it a try! This thanks to Concurrency (并发) and the lightweight nature of User Thread.

However, this performance gainz are only for not CPU-bounded tasks like Async IO. The performance gainz declines gradually as the tasks require more CPU power to complete. For non CPU-bounded tasks, they can run in concurrently without needing attention from the CPU. In the code editor below, change the value of i in the main() from 100 to 1000, you should observe the time taken 10X!