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

[Bruce Carneal]

On Tuesday, 18 January 2022 at 17:03:33 UTC, sfp wrote:
> On Monday, 17 January 2022 at 21:31:25 UTC, H. S. Teoh wrote:
>> On Mon, Jan 17, 2022 at 09:12:52PM +0000, bioinfornatics via 
>> Digitalmars-d wrote: [...]
>>> And recently I put my feedback where D could provide some 
>>> killer feature in this area: 
>>> https://forum.dlang.org/thread/fuzvsdlqtklhmxsnzgye@forum.dlang.org
>>> 
>>> Unfortunately, this will not be possible in the near future, 
>>> so others language will keep the market
>>
>> Why would it not be possible in the near future?
>>
>> None of the items you listed seem to be specific to the 
>> language itself, it seems to be more of an ecosystem issue.
>>
>>
>> T
>
> Take one item on the list: developing an equivalent of numpy 
> and scipy. What do you take to be the "near future"? One year 
> away? Two years?
>
> There is no language feature holding these items back. 
> Addressing ecosystem issues is a massive undertaking.
>
> In order for a D clone of even just numpy to be successful, it 
> needs to have a significant user base feeding input back into 
> the development cycle so that it can go beyond simply being 
> churned out by a few overeager developers and actually 
> stabilized so that it becomes useful and robust.
>
> You must also consider that the items that bioinfornatics 
> listed are all somewhat contingent on each other. In isolation 
> they aren't nearly as useful. You might have a numpy/scipy 
> clone, but if you don't also have a matplotlib clone (or some 
> other means of doing data visualization from D) their utility 
> is a bit limited.
>
> His wishlist is a tall order.

Yes.  Better to concentrate on things D *can* enable, like a 
great performance programming experience.

D appeals to me primarily because it lets me write simpler 
performant code.  It regularly opens the door to better 
perf/complexity ratios than C++ for example.  This is 
particularly important in markets where even small performance 
gains bring large economic benefits, where novel code is 
indicated.

OTOH, if your value add is more about quickly 
assembling/rearranging existing components that are sufficiently 
peformant in themselves and in combination, well, by all means, 
carry on!