On Saturday, 22 September 2018 at 02:26:41 UTC, Chris Katko wrote:
On Saturday, 22 September 2018 at 02:13:58 UTC, Chris Katko
wrote:
On Friday, 21 September 2018 at 12:15:59 UTC, Ali Çehreli
wrote:
On 09/21/2018 12:25 AM, Chris Katko wrote:
[...]
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"
Also, when I don't call .finish(true) at the end, it just sits
there forever (after running) like one of the threads won't
terminate. Requiring a control-C. But the docs and examples
don't seem to indicate I should need that...
So I looked into it. It's amap that explodes in RAM.
Per the docs, amap has "less overhead but more memory usage."
While map has more overhead but less memory usage and "avoids the
need to keep all results in memory."
But, if I make a call to map... it doesn't compile! I get:
Error: no [] operator overload for type
std.parallelism.TaskPool.map!(monte).map!(Result).map.Map
Simply changing amap to map here:
sum = taskPool.reduce!(test)
(
taskPool.map!(monte)(range)
);
