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

[max haughton]

On Saturday, 15 January 2022 at 17:29:35 UTC, Guillaume Piolat 
wrote:
> On Saturday, 15 January 2022 at 12:21:37 UTC, Ola Fosheim 
> Grøstad wrote:
>>
>>> Definitely. Homogenous memory is interesting for the ability 
>>> to make GPUs do the things GPUs are good at and leave the 
>>> rest to the CPU without worrying about memory transfer across 
>>> the PCI-e. Something which CUDA can't take advantage of on 
>>> account of nvidia GPUs being only discrete.
>>
>> Steam Deck, which appears to come out next month, seems to run 
>> under Linux and has an "AMD APU" with a modern GPU and CPU 
>> integrated on the same chip
>
> Related: has anyone here seen an actual measured performance 
> gain from co-located CPU and GPU on the same chip? I used to 
> test with OpenCL + Intel SoC and again, it was underwhelming 
> and not faster. I'd be happy to know about other experiences.

Well console memory systems are basically built around this idea. 
On the assumption that you mean a consumer chip with integrated 
graphics, any gain you see from sharing memory is going to be 
contrasted against the chip being intended for people who were 
going to actually use integrated graphics. For compute especially 
it seems like this is very dependant on what patterns you 
actually want to do with the memory.

The new Apple chips have a unified memory architecture, and a 
really fast one too. I don't know what GPGPU is like on it but 
it's one of the reason why it absolutely flies on normal code.