Multi-process and multi-core processing technology in Go language

With the continuous upgrading and development of computer hardware, software development is also constantly changing from single-core to multi-core. With the emergence of multi-core processing technology, software developers have gradually begun to pay attention to how to process data on multi-core processors.

Go language is a programming language developed by Google. Its design goal is to handle concurrency and multi-core performance. In Go language, multi-process and multi-core processing techniques can be used to effectively utilize multi-core CPUs. This article will introduce the ways and methods to implement multi-process and multi-core processing technology in Go language.

1. Multi-process

Multi-process technology refers to running multiple processes on the same computer. These processes can run in parallel to improve computer performance. In the Go language, multi-processing is implemented by using goroutine.

Goroutine is a lightweight thread that can be created and destroyed in the stack of the Go language runtime and does not need to occupy too many system resources like operating system threads. In the Go language, a goroutine can be started through the go keyword.

The following is a simple example:

func main() {
    go func() {
        fmt.Println("goroutine")
    }()
    fmt.Println("main function")
}

In this example, we use the go keyword to start a goroutine and print a message in the goroutine. At the same time, a message is also printed in the main function.

When this code runs, "main function" is output first, and then "goroutine". This is because after starting the goroutine, the program does not wait for the execution of the goroutine, but continues to execute the main function.

If you want the main function to wait for the execution of goroutine, you can use WaitGroup in the sync package. The following is an example of using WaitGroup to implement multiple goroutine collaboration:

import (
    "fmt"
    "sync"
)

func main() {
    var wg sync.WaitGroup
    for i := 0; i < 10; i++ {
        wg.Add(1)
        go func(i int) {
            fmt.Println(i)
            wg.Done()
        }(i)
    }
    wg.Wait()
    fmt.Println("done")
}

In this example, we first create a WaitGroup object, and then use the Add method to add tasks to the WaitGroup. In the task, we print the goroutine number and use the Done method to tell the WaitGroup that the task is completed.

Finally, we use the Wait method to wait for all tasks to be completed before exiting the main thread. This ensures that all goroutines are executed.

2. Multi-core processing

Multi-core processing refers to running multiple cores on the same computer, and each core can run one or more threads. The Go language implements automatic multi-core processing by using the runtime package.

In the Go language, you can set the number of cores used by the program through the GOMAXPROCS environment variable. The default value of GOMAXPROCS is the number of system CPU cores.

The following is an example of using Go language to implement multi-core processing:

import (
    "runtime"
)

func main() {
    runtime.GOMAXPROCS(2) // 设置使用的核心数为2
    // ...
}

In this example, we use the GOMAXPROCS method in the runtime package to set the number of cores used by the program to 2. In this case, the program automatically distributes tasks between the two cores.

3. Comprehensive application of multi-process and multi-core

In actual applications, multi-process and multi-core processing are usually used at the same time. For example, in a computationally intensive task, we can start multiple goroutines and assign them to different cores for execution to improve computer performance.

The following is an example:

import (
    "runtime"
    "sync"
)

const taskCount = 10

func worker(wg *sync.WaitGroup, taskCh chan int) {
    for task := range taskCh {
        // 处理任务
        runtime.Gosched() // 让出CPU时间片
        wg.Done()
    }
}

func main() {
    runtime.GOMAXPROCS(2)

    taskCh := make(chan int, taskCount)
    for i := 0; i < runtime.NumCPU(); i++ {
        go worker(&wg, taskCh)
    }

    for i := 0; i < taskCount; i++ {
        wg.Add(1)
        taskCh <- i
    }

    close(taskCh)
    wg.Wait()
    fmt.Println("done")
}

In this example, we start multiple goroutines and assign them to different cores for execution. At the same time, we also use WaitGroup and channel to collaborate on multiple tasks.

Conclusion

By using multi-process and multi-core processing technology in the Go language, faster and more efficient data processing can be achieved. In practical applications, you can choose to use multi-process, multi-core processing or a combination of the two according to the nature of the task and the hardware configuration of the computer. In the Go language, the implementation of these technologies is very simple and convenient, and developers can easily take advantage of the multi-core performance of the computer to improve the performance of the program.

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