Performance optimization techniques in Go concurrent programming

Performance optimization tips for Go concurrent programming include: using a Goroutine pool to avoid the overhead of creating and destroying goroutines. Use channels to pass data instead of shared memory to prevent data races. Avoid using heavy locks and consider using lock-free data structures to reduce contention. Execute tasks in parallel and take advantage of Go's concurrency features.

Performance Optimization Tips in Go Concurrent Programming

In Go, concurrent programming is widely used to improve application performance. However, when implementing concurrency, you need to pay attention to some key performance optimization tips to avoid unnecessary performance overhead.

1. Using Goroutine Pool

There may be overhead when creating a new goroutine. By using a goroutine pool, you avoid the cost of repeatedly creating and destroying goroutines.

package main

import "sync"

var wg sync.WaitGroup
var pool = sync.Pool{
    New: func() interface{} {
        return new(func() {})
    },
}

func main() {
    for i := 0; i < 10000; i++ {
        fn := pool.Get().(func())
        go fn()
        wg.Add(1)
        go func() {
            defer wg.Done()
            pool.Put(fn)
        }()
    }

    wg.Wait()
}

2. Use channels to pass data instead of shared memory

Sharing memory between goroutines may cause data races and unpredictable behavior. Instead, passing data using channels is safer and more scalable.

package main

import (
    "fmt"
    "sync"
    "time"
)

var wg sync.WaitGroup
var ch = make(chan int)

func main() {
    for i := 0; i < 10000; i++ {
        go func(i int) {
            defer wg.Done()
            ch <- i
        }(i)
    }

    for i := 0; i < 10000; i++ {
        fmt.Println(<-ch)
    }

    close(ch)
    wg.Wait()
}

3. Avoid using heavy locks

Locks are crucial in concurrent programming, but overuse can lead to performance degradation. Consider using lock-free data structures (such as atomic values ​​or lock-free queues) to reduce contention.

package main

import (
    "sync/atomic"
    "unsafe"
)

var (
    count int32
    ptr unsafe.Pointer
)

func main() {
    for i := 0; i < 10000; i++ {
        atomic.AddInt32(&count, 1)
        atomic.StorePointer(&ptr, nil)
    }
}

4. Execute tasks in parallel

Take full advantage of the concurrency features of Go by using goroutine to execute tasks in parallel instead of serial execution.

package main

import (
    "fmt"
    "sync"
)

func main() {
    var wg sync.WaitGroup
    wg.Add(3)
    go func() {
        for i := 0; i < 10000; i++ {
            fmt.Println(i)
        }
        wg.Done()
    }()

    go func() {
        for i := 10000; i < 20000; i++ {
            fmt.Println(i)
        }
        wg.Done()
    }()

    go func() {
        for i := 20000; i < 30000; i++ {
            fmt.Println(i)
        }
        wg.Done()
    }()

    wg.Wait()
}

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