# Julia gets mentioned in an article about FORTRAN

**URL:** <https://discourse.julialang.org/t/julia-gets-mentioned-in-an-article-about-fortran/60605>\
**Category:** Community\
**Created:** [May 5, 2021, 8:52pm UTC](https://discourse.julialang.org/t/julia-gets-mentioned-in-an-article-about-fortran/60605 "2021-05-05T20:52:36Z")\
**Posts on this page:** 1\
**Showing post:** 44

<div class="post-metadata">

**Author:** ![lmiq](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lmiq/32/18314_2.png) [@lmiq](https://discourse.julialang.org/u/lmiq)\
**Post date:** [May 7, 2021, 1:38pm UTC](https://discourse.julialang.org/t/julia-gets-mentioned-in-an-article-about-fortran/60605/44 "2021-05-07T13:38:33Z")

</div>

> [@Skoffer](#):
>
> Can you provide an example?

Here is one example (not sure how representative it is):

Fortran:

> **Code**
>
> ```julia
> PROGRAM Parallel_Hello_World
> USE OMP_LIB
> REAL*8 :: partial_Sum, total_Sum
> !$OMP PARALLEL PRIVATE(partial_Sum) SHARED(total_Sum)
> partial_Sum = 0.d0
> total_Sum = 0.d0
> 
> !$OMP DO
> DO i=1,1000000000
> partial_Sum = partial_Sum + dsin(dble(i))
> END DO
> !$OMP END DO
> 
> !$OMP CRITICAL
> total_Sum = total_Sum + partial_Sum
> !$OMP END CRITICAL
> 
> !$OMP END PARALLEL
> PRINT *, "Total Sum: ", total_Sum
> END
> 
> ```

Result:

```julia
leandro@pitico:~/Drive/Work/JuliaPlay% gfortran -O3 omp.f95 -o omp
leandro@pitico:~/Drive/Work/JuliaPlay% time ./omp
 Total Sum: 0.42129448674541342

real 0m54,495s
user 0m54,476s
sys 0m0,004s
leandro@pitico:~/Drive/Work/JuliaPlay% gfortran -O3 -fopenmp omp.f95 -o omp
leandro@pitico:~/Drive/Work/JuliaPlay% time ./omp
 Total Sum: 0.42129448674645509

real 0m12,538s
user 1m29,020s
sys 0m0,016s

```

Julia using `FLoops`:

> **Code**
>
> ```julia
> using FLoops
> function f()
> @floop for i in 1:1000000000
> @reduce(total_Sum += sin(i))
> end
> total_Sum
> end
> println("Total sum: ",f())
> 
> ```

Result:

```julia
leandro@pitico:~/Drive/Work/JuliaPlay% time julia floop.jl
Total sum: 0.4212944867466973

real 0m40,729s
user 0m41,039s
sys 0m0,608s

leandro@pitico:~/Drive/Work/JuliaPlay% time julia -t8 floop.jl
Total sum: 0.4212944867465145

real 0m14,743s
user 1m4,074s
sys 0m0,751s

```

Julia using `@threads`:

```julia
using Base.Threads
function f()
    total_Sum = zeros(nthreads())
    @threads for i in 1:1000000000
        total_Sum[threadid()] += sin(i)
    end
    sum(total_Sum)
end
println("Total sum: ",f())

```

```julia
leandro@pitico:~/Drive/Work/JuliaPlay% time julia -t8 threads.jl 
Total sum: 0.4212944867465146

real 0m10,514s
user 1m11,253s
sys 0m0,544s

```

Note that Julia is faster than Fortran with a single thread (no idea why).

I split this in a [new thread](https://discourse.julialang.org/t/manual-reduction-much-faster-than-atomic-add-with-threads/60721), I guess I don’t really understand what is going on when using atomic operations, and now removed the initial test, where I used `atomic_add!` here because it didn’t make sense.

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