golang multi-core settings

Golang is a modern, high-performance programming language that is widely used in network services, cloud computing, data analysis and other fields. Golang is a cross-platform language with excellent concurrency performance, and its default concurrency mechanism is also very powerful. By default, Golang uses Goroutine coroutines to achieve concurrency and can easily handle thousands of concurrent connections. However, if you need to run Golang programs on multi-core CPUs, you need to make some additional settings.

This article will introduce how to set up multi-core in Golang to improve the concurrency performance of the program.

1. What is multi-core setting?

Multi-core setting (or multi-processor setting) refers to setting some operating parameters when running a Golang program on a multi-core CPU, so that the program can fully utilize the processing power of the multi-core CPU, thereby improving the concurrency performance of the program.

By default, Golang's concurrency mechanism will only use a single core. This is because the scheduler (Scheduler) used by Golang is based on cooperative scheduling (Cooperative Scheduling), that is, only when the current Goroutine actively gives up the processor, it will switch to other Goroutine, thus ensuring that there is only one Goroutine at the same time. In execution. Although this mechanism is simple and efficient, it can only use a single core and cannot fully utilize the performance advantages of multi-core CPUs.

Therefore, when setting up multi-core, some special settings are needed to enable Golang's scheduler to schedule Goroutine on multiple cores and balance the load on different cores, thereby improving program concurrency. performance.

2. How to set up multi-core?

Multi-core settings in Golang require the use of system calls, which mainly include the following three functions:

1. runtime.GOMAXPROCS(n int)

This The function is used to set the maximum number of CPU cores used when the code is running. Its default value is 1, which uses only a single core. If set to a value greater than 1, Golang will run Goroutine on multi-core processors. For example:

runtime.GOMAXPROCS(4) //Use 4 cores to run the program

2. runtime.LockOSThread()

This function is used to The current Goroutine is locked to the current thread, preventing the scheduler from switching it to run on other threads, thus reducing the overhead of thread switching. For example:

func loop() {

runtime.LockOSThread()  //锁定当前协程到当前线程
//进行一些处理

}

3. runtime.UnlockOSThread()

This function is used to Goroutine is unlocked from the current thread so that it can be switched by the scheduler to run on other threads. For example:

func loop() {

//进行一些处理
runtime.UnlockOSThread()  //解锁当前协程

}

If the UnlockOSThread function is not called, the current coroutine will never be able to switch out of the current thread.

3. How to evaluate the effect of multi-core settings?

Before making multi-core settings, you need to evaluate the performance of the current program in single-core and multi-core environments, so that you can improve the performance of the program through multi-core settings.

To evaluate the performance of a program, you can use Go's own performance analysis tool pprof. pprof can analyze the CPU and memory usage of the program to find out the performance bottlenecks in the code.

1. Install pprof

First you need to install pprof:

go get -u github.com/google/pprof

2. Run pprof

To use pprof to analyze the performance of the program, you need to add profiling code to the program and turn it on:

package main

import (

"math/rand"
"os"
"runtime/pprof"
"time"

)

func main() {

pprofFile, err := os.Create("cpu.prof")
if err != nil {
    panic(err)
}
pprof.StartCPUProfile(pprofFile)
defer pprof.StopCPUProfile()

rand.Seed(time.Now().UnixNano())
for i := 0; i < 10; i++ {
    go func() {
        for {
            num := rand.Intn(1000000000)
            _ = num * num
        }
    }()
}

time.Sleep(10 * time.Second)

}

After the program is run, a cpu.prof file will be generated in the current directory, including the CPU usage of the program Condition. You can use the following command for analysis:

pprof -http=:9999 cpu.prof

This command will start a Web server, which can be accessed in the browser through http://localhost:9999 /access. On the web page, you can view the program's CPU usage, function call relationships, and call times to identify performance bottlenecks.

3. Compare single-core and multi-core performance

With the pprof tool, you can run programs in single-core and multi-core environments and compare their performance.

To compare single-core and multi-core performance, you need to set the GOMAXPROCS parameter when running the program:

go run -race -p=1 main.go //Single-core operation
go run -race -p=4 main.go //Four-core running

Use pprof to perform performance analysis on the program running twice and compare their CPU usage and number of function calls. By comparing performance analysis results, performance bottlenecks in the program can be found and optimized.

4. Summary

Golang runs Goroutine on a single core by default, which cannot fully utilize the processing power of multi-core CPUs. Running Golang programs on multi-core CPUs requires multi-core settings, including setting GOMAXPROCS parameters and using the LockOSThread and UnlockOSThread functions.

In order to evaluate the effect of multi-core settings, you can use Go's own performance analysis tool pprof to find out the performance bottlenecks in the program and optimize them.

Through multi-core settings, you can make full use of the processing power of multi-core CPUs, thereby improving the concurrent performance of the program.

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