sliced().array compatibility with parallel?

[Ilya Yaroshenko via Digitalmars-d-learn]

On Saturday, 9 January 2016 at 23:20:00 UTC, Jay Norwood wrote:
> I'm playing around with win32, v2.069.2 dmd and 
> "dip80-ndslice": "~>0.8.8".  If I convert the 2D slice with 
> .array(), should that first dimension then be compatible with 
> parallel foreach?
>
> I find that without using parallel, all the means get computed, 
> but with parallel, only about  half of them are computed in 
> this example.  The others remain NaN, examined in the debugger 
> in Visual D.
>
> import std.range : iota;
> import std.array : array;
> import std.algorithm;
> import std.datetime;
> import std.conv : to;
> import std.stdio;
> import std.experimental.ndslice;
>
> enum testCount = 1;
> double[1000] means;
> double[] data;
>
> void f1() {
>  import std.parallelism;
>  auto sl = data.sliced(1000,100_000);
>  auto sla = sl.array();
>  foreach(i,vec; parallel(sla)){
>   double v=vec.sum(0.0);
>   means[i] = v / 100_000;
>  }
> }
>
> void main() {
>  data = new double[100_000_000];
>  for(int i=0;i<100_000_000;i++){ data[i] = i/100_000_000.0;}
>  auto r = benchmark!(f1)(testCount);
>  auto f0Result = to!Duration(r[0] / testCount);
>  f0Result.writeln;
>  writeln(means[0]);
> }

This is a bug in std.parallelism :-)

Proof:

import std.range : iota;
import std.array : array;
import std.algorithm;
import std.datetime;
import std.conv : to;
import std.stdio;
import mir.ndslice;

import std.parallelism;

enum testCount = 1;

double[1000] means;
double[] data;

void f1() {
	//auto sl = data.sliced(1000, 100_000);
	//auto sla = sl.array();
	auto sla = new double[][1000];
	foreach(i, ref e; sla)
	{
		e = data[i * 100_000 .. (i+1) * 100_000];
	}
	foreach(i,vec; parallel(sla))
	{
		double v = vec.sum;
		means[i] = v / vec.length;
	}
}

void main() {
	data = new double[100_000_000];
	foreach(i, ref e; data){
		e = i / 100_000_000.0;
	}
	auto r = benchmark!(f1)(testCount);
	auto f0Result = to!Duration(r[0] / testCount);
	f0Result.writeln;
	writeln(means);
}

Prints:
[0.000499995, 0.0015, 0.0025, 0.0035, 0.00449999, 0.00549999, 
0.00649999, 0.00749999, 0.00849999, 0.00949999, 0.0105, 0.0115, 
0.0125, 0.0135, 0.0145, 0.0155, 0.0165, 0.0175, 0.0185, 0.0195, 
0.0205, 0.0215, 0.0225, 0.0235, 0.0245, 0.0255, 0.0265, 0.0275, 
0.0285, 0.0295, 0.0305, 0.0315, 0.0325, 0.0335, 0.0345, 0.0355, 
0.0365, 0.0375, 0.0385, 0.0395, 0.0405, 0.0415, 0.0425, 0.0435, 
0.0445, 0.0455, 0.0465, 0.0475, 0.0485, 0.0495, 0.0505, 0.0515, 
0.0525, 0.0535, 0.0545, 0.0555, 0.0565, 0.0575, 0.0585, 0.0595, 
0.0605, 0.0615, 0.0625, nan, nan, nan, nan, nan, nan, nan, nan, 
nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 
nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 
nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 
nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 
nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 
nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan ....