A 100-long vector is way too short to show any benefit. goroutines have
start-up, scheduling, and shut-down costs. What happens if you try to
square the largest matrix you can fit into memory (10,000 by 10000?)
On Fri, Feb 19, 2021 at 9:46 AM Yuwen Dai <yuw...@gmail.com> wrote:
> Hi experts,
>
> I'm a newbie to golang. One of my first ideas to use goroutine is to
> write a matrix multiplying programme: C = A*B. I though the calculating
> of every element of C: c[i][j] = row i of A * column j of B could be
> run by a goroutine. This is the skeleton of the code:
>
> t1 := time.Now().UnixNano() //benchmark
> rand.Seed(t1)
> for i := 0; i < n; i++ {
> ai,_ := get_row(a,i)
> for j := 0; j < t; j ++ {
> bj, _ := get_column(b,j)
> // c[i][j],_ = dot_product(ai, bj)
> go func(element *int, ai,bj []int) {
> *element,_ = dot_product(ai,bj)
> wg.Done()
> }(&c[i][j], ai, bj)
> }
> }
>
> wg.Wait() // waiting for all the elements have been calculated
> t2 := time.Now().UnixNano()
> fmt.Printf("the dot_product using goroutine costs %v\n", t2 - t1)
>
> As the goroutines will run "concurrently" on my laptop with 8 CPU cores to
> calculate the element of matrix, I thought the code would ran faster than
> not using goroutine. In fact, it ran slowlier than not using goroutine.
> Any explanation of this? By the way, the dimension of matrix is
> 100x100.
>
> Best regards,
> Yuwen
>
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