Parallel Processing in Golang: Leveraging Concurrency for Performance

Consider the provided code, which showcases parallel processing with goroutines. However, it raises questions about the potential for concurrent execution and the optimal approach for achieving parallelism.

Concurrent Execution of dowork

The premise that dowork will execute in parallel is not guaranteed. While goroutines provide a lightweight concurrency mechanism, the OS scheduler determines the actual execution sequence. GOMAXPROCS, as per Go 1.5's release notes, typically aligns with the available cores.

Suggested Approach: Deadlock Prevention and Concurrency Control

Regarding maintaining the main function's execution, fmt.Scanln can be unreliable, especially in production environments. Instead, consider implementing a sync.WaitGroup to ensure all goroutines complete before exiting. Additionally, to enhance concurrency control and ensure proper resource utilization for parallel tasks, it's recommended to utilize channels separate dowork workers for each goroutine.

Utility Function for Parallel Function Execution

To simplify parallel function execution, one can leverage an existing utility function like the following:

import "sync"

// Parallelize parallelizes function calls
func Parallelize(functions ...func()) {
    var waitGroup sync.WaitGroup
    waitGroup.Add(len(functions))

    defer waitGroup.Wait()

    for _, function := range functions {
        go func(f func()) {
            defer waitGroup.Done()
            f()
        }(function)
    }
}

Applying this function to the code snippet:

func1 := func() { f(0) }
func2 := func() { f(1) }
func3 := func() { f(2) }

Parallelize(func1, func2, func3)