What is the parallel writing method in golang?

In modern software development, efficient use of computer hardware resources is crucial. Parallel programming is a programming method that can maximize the use of multi-core CPUs. Compared with other programming languages, Go language (also called Golang) has built-in tools and mechanisms to support concurrent programming, so it has been widely used and recognized in the field of parallel programming.

This article will introduce some methods and technologies to implement parallel programming in Golang, as well as their applicable scenarios and precautions.

1. Goroutine and Channel

Goroutine is a parallel programming model that Golang borrows from other programming languages. It's called a lightweight thread and makes more efficient use of your computer's multi-core processing power. Each Goroutine is automatically managed by Golang's runtime system, and developers only need to create a Goroutine by running the go keyword.

For example:

func main() {
    go func() {
        fmt.Println("Hello, Goroutine!")
    }()
    fmt.Println("Hello, World!")
}

In this code, we create an anonymous function and convert it into a Goroutine using the go keyword. The program will output "Hello, World!" and "Hello, Goroutine!" at the same time.

Channel is the mechanism used for communication between Goroutines in Golang. Channel can be used to transmit any type of data, so data and control information can be passed between different Goroutines.

For example:

func worker(id int, jobs <-chan int, results chan<- int) {
    for j := range jobs {
        fmt.Println("worker", id, "started  job", j)
        time.Sleep(time.Second)
        fmt.Println("worker", id, "finished job", j)
        results <- j * 2
    }
}

func main() {
    jobs := make(chan int, 100)
    results := make(chan int, 100)
    for w := 1; w <= 3; w++ {
        go worker(w, jobs, results)
    }
    for j := 1; j <= 9; j++ {
        jobs <- j
    }
    close(jobs)
    for a := 1; a <= 9; a++ {
        <-results
    }
}

In this code, we define a worker function that receives two Channels: one for receiving tasks and the other for returning task results. We created three Goroutines. Each Goroutine will obtain tasks from the jobs Channel and write the processing results to the results Channel. Finally, we use a for loop to send 9 tasks to the jobs Channel and output the values ​​of the results Channel to the standard output. Note that we need to close the jobs Channel after the for loop so that the worker function terminates.

2. Sync package

In Golang, the Sync package provides some synchronization tools necessary for parallel programming, such as:

· WaitGroup: Wait for a group of Goroutines to complete the task ;
· Mutex: implements mutually exclusive access to shared data;
· Cond: condition variable, communicates and synchronizes between multiple Goroutines.

Here we will show an example of using WaitGroup:

func worker(id int, wg *sync.WaitGroup) {
    defer wg.Done()
    fmt.Printf("Worker %d starting\n", id)

    time.Sleep(time.Second)
    fmt.Printf("Worker %d done\n", id)
}

func main() {
    var wg sync.WaitGroup

    for i := 1; i <= 5; i++ {
        wg.Add(1)
        go worker(i, &wg)
    }

    wg.Wait()
}

In this example, we define a worker function that receives a WaitGroup pointer as a parameter. After the function work is completed, we call the Done method of WaitGroup to notify the Goroutine task to which it belongs has been completed. In the main function, we create a Goroutine for each worker function and use the Add method of WaitGroup to tell WaitGroup that there is a group of Goroutines running here. Finally, we call the Wait method to wait for all Goroutines to complete their tasks.

3. Set GOMAXPROCS

In Golang, GOMAXPROCS is a number indicating how many Goroutines should be running at the same time. If this number is set too small, the parallelism of the program will be limited. If set too large, computer resources will be wasted. Therefore, we need to set the value of GOMAXPROCS according to the number of processor cores of the computer to avoid excessive or underutilization of the computer's resources.

By default, Golang's GOMAXPROCS is equal to the number of processor cores. You can use the runtime package to modify it in the program code:

import "runtime"

//...

func main() {
    numCPU := runtime.NumCPU()
    runtime.GOMAXPROCS(numCPU)

    //...
}

Here, we use the runtime package to obtain the processor cores number, and then set the value of GOMAXPROCS equal to the number of cores.

Summary

This article introduces several methods and technologies of concurrent programming in Golang, including Goroutine and Channel, Sync package, and setting GOMAXPROCS. Although concurrent programming can improve program performance and efficiency, it also brings some risks and challenges. Therefore, when performing concurrent programming, we need to choose an appropriate solution based on the actual situation, and pay attention to controlling the degree of parallelism to avoid unnecessary errors and waste of resources.

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