On Friday, 21 September 2018 at 12:15:59 UTC, Ali Çehreli wrote:
On 09/21/2018 12:25 AM, Chris Katko wrote:
On Thursday, 20 September 2018 at 05:51:17 UTC, Neia Neutuladh
wrote:
On Thursday, 20 September 2018 at 05:34:42 UTC, Chris Katko
wrote:
All I want to do is loop from 0 to [constant] with a for or
foreach, and have it split up across however many cores I
have.
You're looking at std.parallelism.TaskPool, especially the
amap and reduce functions. Should do pretty much exactly what
you're asking.
auto taskpool = new TaskPool();
taskpool.reduce!((a, b) => a + b)(iota(1_000_000_000_000L));
I get "Error: template instance `reduce!((a, b) => a + b)`
cannot use local __lambda1 as parameter to non-global template
reduce(functions...)" when trying to compile that using the
online D editor with DMD and LDC.
Any ideas?
You can use a free-standing function as a workaround, which is
included in the following chapter that explains most of
std.parallelism:
http://ddili.org/ders/d.en/parallelism.html
That chapter is missing e.g. the newly-added fold():
https://dlang.org/phobos/std_parallelism.html#.TaskPool.fold
Ali
Okay... so I've got it running. The problem is, it uses tons of
RAM. In fact, proportional to the working set.
T test(T)(T x, T y)
{
return x + y;
}
double monte(T)(T x)
{
double v = uniform(-1F, 1F);
double u = uniform(-1F, 1F);
if(sqrt(v*v + u*u) < 1.0)
{
return 1;
}else{
return 0;
}
}
auto taskpool = new TaskPool();
sum = taskpool.reduce!(test)(
taskpool.amap!monte(
iota(num)
) );
taskpool.finish(true);
1000000 becomes ~8MB
10000000 becomes 80MB
100000000, I can't even run because it says "Exception: Memory
Allocation failed"
