Discuss the differences and connections between concurrency and parallelism in Go language

Go language is a programming language developed by Google and is known for its concurrent programming features. In Go language, there are two important concepts - concurrency and parallelism. Although the two concepts look similar, there are subtle differences and connections between them. This article will explore the differences between concurrency and parallelism in the Go language and explain their connection through specific code examples.

First, let’s understand the concepts of concurrency and parallelism. Concurrency refers to the existence of multiple independent execution units in the system. These execution units overlap in time, but there is only one execution at any time. In other words, concurrency refers to the state of a system with multiple activities active at the same time. Parallelism refers to the simultaneous existence of multiple independent execution units in the system, and these execution units actually run simultaneously on multiple processors. In the case of parallelism, multiple tasks can be executed simultaneously, improving the overall performance of the program.

In the Go language, we can achieve concurrency through goroutine. Goroutine is a lightweight thread that is managed by the runtime environment of the Go language and can be easily created in the program. The following is a simple sample code that shows how to use goroutine to execute tasks concurrently:

package main

import (
    "fmt"
    "time"
)

func task() {
    for i := 0; i < 5; i++ {
        fmt.Println("Executing task ", i)
        time.Sleep(time.Second)
    }
}

func main() {
    go task()
    time.Sleep(3 * time.Second)
    fmt.Println("Main goroutine exits")
}

In the above code, we define a task function, which will output a series of Number, and will sleep for 1 second after each output. In the main function, we start a new goroutine to execute the task function through go task(). In this way, the task function will be executed concurrently in a separate goroutine, while the main goroutine will continue to execute subsequent code. In this way, we achieve the effect of executing tasks concurrently.

Next, let’s look at a sample code that shows how to use the parallel features of the Go language to improve the execution efficiency of the program:

package main

import (
    "fmt"
    "runtime"
    "sync"
)

func parallelTask(wg *sync.WaitGroup, id int) {
    defer wg.Done()
    fmt.Println("Executing parallel task ", id)
}

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

    var wg sync.WaitGroup

    for i := 0; i < numCPU; i++ {
        wg.Add(1)
        go parallelTask(&wg, i)
    }

    wg.Wait()
    fmt.Println("All parallel tasks have completed")
}

In the above code, we used sync.WaitGroup to wait for the completion of all parallel tasks. By setting runtime.GOMAXPROCS(numCPU), we ensure that the program will use all CPU cores to execute the parallelTask function in parallel. In the main function, we create the same number of goroutines as the number of CPU cores and execute the parallelTask function concurrently. Finally, wait for the completion of all goroutines through wg.Wait(). In this way, we achieve the effect of executing tasks in parallel and improve the execution efficiency of the program.

To sum up, the concurrency and parallelism of Go language are one of its unique features. Through goroutine and parallel execution mechanism, concurrent and parallel programming can be easily realized. Although there are subtle differences between concurrency and parallelism, in actual programming they are often used in conjunction with each other to improve program performance. I hope that through the discussion and code examples in this article, readers can more clearly understand the connection and difference between concurrency and parallelism in the Go language.

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