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

[M.M.]

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." - 
>> https://www.cs.rice.edu/~vs3/PDF/Joyner-MainThesis.pdf
>
> That paper is from 2008, meanwhile in 2021,
>
> https://www.hpcwire.com/off-the-wire/julia-joins-petaflop-club//
>
> 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.