Performance comparison of golang function and goroutine

In the Go language, functions are more performant than Goroutines because Goroutines require additional overhead to manage scheduling and memory allocation. The specific differences are as follows: Creation time: Functions have almost no overhead, while Goroutines have higher overhead. Memory consumption: Function memory consumption is low, while Goroutine memory consumption is high. Concurrency: Functions do not support concurrency, while Goroutines do.

Go language: Performance comparison of functions and Goroutines

In the Go language, functions and Goroutines are the two major components of concurrent programming pillar. Functions are blocks of code that perform a specific task, while Goroutines are lightweight threads that execute in parallel.

Performance comparison

In terms of performance, there is a clear difference between functions and Goroutines. In general, functions perform better than Goroutines because Goroutines require additional overhead to manage scheduling and memory allocation.

The following table summarizes the performance differences between functions and Goroutines:

Operation	Function	Goroutine
Creation time	Almost no overhead	Higher overhead
Memory consumption	Low	High
Concurrency	Not supported	Supported

Practical case

In order to demonstrate the performance difference between functions and Goroutines, we wrote a simple benchmark test to compare and calculate 1 million Fibonacci numbers required time.

Using functions

func Fibonacci(n int) int {
    if n < 2 {
        return n
    }
    return Fibonacci(n-1) + Fibonacci(n-2)
}

func main() {
    start := time.Now()
    for i := 0; i < 1000000; i++ {
        Fibonacci(i)
    }
    elapsed := time.Since(start)
    fmt.Println(elapsed)
}

Using Goroutine

func FibonacciGoroutine(n int) <-chan int {
    c := make(chan int)
    go func() {
        c <- Fibonacci(n)
    }()
    return c
}

func main() {
    start := time.Now()
    ch := make([]chan int, 1000000)
    for i := 0; i < 1000000; i++ {
        ch[i] = FibonacciGoroutine(i)
    }
    for i := 0; i < 1000000; i++ {
        <-ch[i]
    }
    elapsed := time.Since(start)
    fmt.Println(elapsed)
}

Running these benchmarks, we get the following results:

##Function231364440Goroutine2900646200

Implementation	Time (nanoseconds)

As you can see, using function to calculate Fibonacci ratio using Goroutine Much faster.

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