On Sunday, 10 January 2016 at 01:16:43 UTC, Ilya Yaroshenko wrote:
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
On Sun, 2016-01-10 at 01:46 +, Jay Norwood via Digitalmars-d-learn
wrote:
>
[…]
> // processed non-parallel works ok
> foreach( dv; dv2){
> if(dv != dv){ // test for NaN
> return 1;
> }
> }
>
> // calculated parallel leaves out processing of
On Sunday, 10 January 2016 at 11:21:53 UTC, Marc Schütz wrote:
I'd say, if `shared` is required, but it compiles without, then
it's still a bug.
Yeah, probably so. Interestingly, without 'shared' and using a
simple assignment from a constant (means[i]= 1.0;), instead of
assignment from
On Sunday, 10 January 2016 at 03:23:14 UTC, Ilya wrote:
I will add significantly faster pairwise summation based on
SIMD instructions into the future std.las. --Ilya
Wow! A lot of overhead in the debug build. I checked the
computed values are the same. This is on my laptop corei5.
dub -b
On Sunday, 10 January 2016 at 12:11:39 UTC, Russel Winder wrote:
foreach( dv; dvp){
if(dv != dv){ // test for NaN
return 1;
}
}
return(0);
}
I am not convinced these "Tests for NaN" actually test for NaN.
I
believe you have to use isNan(dv).
I
On Sunday, 10 January 2016 at 00:41:35 UTC, Ilya Yaroshenko wrote:
It is a bug (Slice or Parallel ?). Please fill this issue.
Slice should work with parallel, and array of slices should
work with parallel.
Ok, thanks, I'll submit it.
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
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
for example,
means[63] through means[251] are consistently all NaN when using
parallel in this test, but are all computed double values when
parallel is not used.
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?
[...]
It is a bug (Slice or Parallel
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?
[...]
Oh... there is no bug.
means
On Sunday, 10 January 2016 at 01:54:18 UTC, Jay Norwood wrote:
ok, thanks. That works. I'll go back to trying ndslice now.
The parallel time for this case is about a 2x speed-up on my
corei5 laptop, debug build in windows32, dmd.
D:\ec_mars_ddt\workspace\nd8>nd8.exe
parallel time msec:2495
On Sunday, 10 January 2016 at 02:43:05 UTC, Jay Norwood wrote:
On Sunday, 10 January 2016 at 01:54:18 UTC, Jay Norwood wrote:
[...]
The parallel time for this case is about a 2x speed-up on my
corei5 laptop, debug build in windows32, dmd.
[...]
I will add significantly faster pairwise
On Sunday, 10 January 2016 at 01:16:43 UTC, Ilya Yaroshenko wrote:
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
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