Scientific computing and parallel computing C++23/C++26

Paulo Pinto pjmlp at
Wed Jan 19 07:29:23 UTC 2022

On Wednesday, 19 January 2022 at 07:24:09 UTC, M.M. wrote:
> On Wednesday, 19 January 2022 at 06:58:55 UTC, Paulo Pinto 
> wrote:
>> On Wednesday, 19 January 2022 at 04:45:20 UTC, forkit wrote:
>>> On Tuesday, 18 January 2022 at 22:21:40 UTC, Ola Fosheim 
>>> Grøstad wrote:
>>>> ...D's potential strength here is not so much in being able 
>>>> to bind to C++ in a limited fashion (like Python), but being 
>>>> able to port C++ to D and improve on it. To get there you 
>>>> need feature parity, which is what this thread is about.
>>> Not just 'feature' parity, but 'performance' parity too:
>>> "Broad adoption of high-level languages by the scientific 
>>> community is unlikely without compiler optimizations to 
>>> mitigate the performance penalties these languages 
>>> abstractions impose." - 
>> That paper is from 2008, meanwhile in 2021,
>> This is what D has to compete against, not only C++ with the 
>> existing SYSCL/CUDA tooling and their ongoing integration into 
>> ISO C++.
> I am not sure what the article tells: that Julia is now popular 
> and people use it? Or that D (and other languages) need to 
> compete against self-written PR articles?
> (Many system-programming languages can achieve the same 
> performance as what the article describes, when several 
> research institutes combine forces on just that.)
> But yes, Julia's focus on small niche, and its popularity in 
> that niche makes it attractive for contributors.

You might call it self-written PR articles, or educate yourself 
who is using it. versus

Also I did mention C++, which you glossed over on your eagerness 
to devalue Julia's market domain versus D among HPC communities.

As someone that spent two years at ATLAS TDAQ HLT, I know which 
languages those folks would be adopting, but hey it is a piece of 
self-written PR.

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