Performance tuning of Golang coroutines

To improve the performance of Go coroutines, the following measures can be taken: Limit the number of coroutines to avoid context switching overhead. Use a coroutine pool to manage coroutine reuse to reduce creation and destruction overhead. Use non-blocking I/O operations such as channels to avoid blocking coroutine execution. Use select statements to receive messages from multiple channels to improve the efficiency of waiting for events to occur. Set CPU affinity to bind coroutines to specific CPU cores to reduce context switching overhead.

Performance Tuning of Go Coroutines

Introduction

Go Coroutines It is a lightweight thread that can be used to write highly concurrent and scalable applications. Optimizing coroutine performance is critical and can improve the overall efficiency and responsiveness of your application. This article will explore some practical techniques to improve the performance of Go coroutines.

1. Limit the number of coroutines

Creating too many coroutines will cause increased context switching overhead, thus slowing down the application. Ideally, create coroutines proportional to the number of CPU cores. You can use the runtime.NumCPU() function to get the number of CPU cores.

func Main() {
    // 限制协程数量为 CPU 内核数
    runtime.GOMAXPROCS(runtime.NumCPU())
}

2. Using coroutine pool

Creating coroutines is an expensive operation. Repeatedly creating and destroying coroutines reduces performance. Instead, coroutine pools can be used to manage coroutine reuse. The coroutine pool can pre-allocate a certain number of coroutines, allocate and deallocate them when needed.

import (
    "sync"
    "time"
)

type WorkFunc func()

type GoroutinePool struct {
    mu      sync.Mutex
    maxSize int
    pool    chan WorkFunc
}

func NewGoroutinePool(maxSize int) *GoroutinePool {
    return &GoroutinePool{
        maxSize: maxSize,
        pool:    make(chan WorkFunc, maxSize),
    }
}

func (p *GoroutinePool) Submit(workFunc WorkFunc) {
    p.mu.Lock()
    if len(p.pool) < p.maxSize {
        p.pool <- workFunc
    } else {
        go workFunc()
    }
    p.mu.Unlock()
}

func (p *GoroutinePool) Close() {
    close(p.pool)
}

3. Avoid blocking operations

Blocking operations (such as I/O operations) will prevent the coroutine from executing. Use non-blocking I/O such as channels or sync.Cond when possible.

// 阻塞 I/O
func BlockingIORead(file *os.File) []byte {
    data := make([]byte, 1024)
    n, err := file.Read(data)
    if err != nil {
        return nil
    }
    return data[:n]
}

// 非阻塞 I/O
func NonBlockingIORead(file *os.File) <-chan []byte {
    ch := make(chan []byte)
    go func() {
        data, err := file.Read(make([]byte, 1024))
        if err != nil {
            close(ch)
        } else {
            ch <- data
        }
    }()
    return ch
}

4. Using the select

select statement can be used to receive messages from multiple communication channels. This allows the coroutine to wait for events to occur in the most efficient way.

func MultipleWorkers() {
    ch1 := make(chan int)
    ch2 := make(chan int)

    go func() {
        // 从通道 ch1 接收消息
        for {
            select {
            case msg := <-ch1:
                // 处理消息
            }
        }
    }()

    go func() {
        // 从通道 ch2 接收消息
        for {
            select {
            case msg := <-ch2:
                // 处理消息
            }
        }
    }()
}

5. Enable CPU affinity

CPU affinity allows coroutines to be bound to specific CPU cores. This can reduce context switching overhead and improve cache hit ratio.

import "runtime"

func SetCPUAffinity() {
    runtime.LockOSThread()
    runtime.SchedSetAffinity(0, [byte(1 << runtime.NumCPU()) - 1])
}

The above is the detailed content of Performance tuning of Golang coroutines. For more information, please follow other related articles on the PHP Chinese website!