In what cases is it recommended to use parallel computing for solving problems?

Parallel computing is recommended in the following cases:

• Tasks that can be divided into independent sub-tasks. For example, processing array elements or performing similar operations on different data.
• Compute-intensive operations, where execution time significantly reduces due to parallelization.
• Processing large volumes of data, when sequential execution takes too long.
• Tasks with high I/O latency, where parallelism allows efficient use of waiting time.

In Go, goroutines and channels are often used for parallel computations, simplifying concurrent code.

Example of simple parallel sum of elements using goroutines:

func sum(nums []int, c chan int) {
    total := 0
    for _, v := range nums {
        total += v
    }
    c <- total
}

func main() {
    nums := []int{1,2,3,4,5,6,7,8}
    c := make(chan int)
    go sum(nums[:len(nums)/2], c)
    go sum(nums[len(nums)/2:], c)
    x, y := <-c, <-c
    fmt.Println("Total sum:", x+y)
}

Thus, parallel computations are effective when tasks can be parallelized without complex synchronization and when it truly speeds up execution.