On Monday, 19 February 2018 at 14:57:22 UTC, SrMordred wrote:
On Monday, 19 February 2018 at 05:54:53 UTC, Dmitry Olshansky
wrote:
The operation is trivial and dataset is rather small. In such
cases SIMD with eg array ops is the way to go:
result[] = values[] * values2[];
Yes, absolutely
On Monday, 19 February 2018 at 05:54:53 UTC, Dmitry Olshansky
wrote:
The operation is trivial and dataset is rather small. In such
cases SIMD with eg array ops is the way to go:
result[] = values[] * values2[];
Yes, absolutely right :)
I make a simple example to understand why the threads
On Monday, 19 February 2018 at 05:49:54 UTC, Nicholas Wilson
wrote:
As SIZE=1024*1024 (i.e. not much, possibly well within L2 cache
for 32bit) it may be that dealing with the concurrency overhead
adds a significant amount of overhead.
That 'concurrency overhead' is what i´m not getting.
Since
On Sunday, 18 February 2018 at 17:54:58 UTC, SrMordred wrote:
I´m experimenting with threads and related recently.
(i´m just started so may be some terrrible mistakes here)
With this base work:
foreach(i ; 0 .. SIZE)
{
results[i] = values1[i] * values2[i];
}
and then with this 3 others
On Sunday, 18 February 2018 at 17:54:58 UTC, SrMordred wrote:
I´m experimenting with threads and related recently.
(i´m just started so may be some terrrible mistakes here)
With this base work:
foreach(i ; 0 .. SIZE)
{
results[i] = values1[i] * values2[i];
}
and then with this 3 others
On Sunday, 18 February 2018 at 17:54:58 UTC, SrMordred wrote:
I´m experimenting with threads and related recently.
(i´m just started so may be some terrrible mistakes here)
With this base work:
foreach(i ; 0 .. SIZE)
{
results[i] = values1[i] * values2[i];
}
and then with this 3 others
I´m experimenting with threads and related recently.
(i´m just started so may be some terrrible mistakes here)
With this base work:
foreach(i ; 0 .. SIZE)
{
results[i] = values1[i] * values2[i];
}
and then with this 3 others methods: parallel, spawn and Threads.
this was my results:
