Scientific computing and parallel computing C++23/C++26
iamthewilsonator at hotmail.com
Fri Jan 21 03:23:59 UTC 2022
On Thursday, 20 January 2022 at 08:36:32 UTC, Ola Fosheim Grøstad
> Yes, so why do you need compile time features?
> My understanding is that the goal of nvc++ is to compile to CPU
> or GPU based on what pays of more for the actual code. So it
> will not need any annotations (it is up to the compiler to
> choose between CPU/GPU?). Bryce suggested that it currently
> only targets one specific GPU, but that it will target multiple
> GPUs for the same executable in the future.
There are two major advantages for compile time features, for the
host and for the device (e.g. GPU).
On the host side, D meta programming allows DCompute to do what
CUDA does with its <<<>>> kernel launch syntax, in terms of type
safety and convenience, with regular D code. This is the feature
that makes CUDA nice to use and OpenCL's lack of such a feature
quite horrible to use, and change of kernel signature a
refactoring unto itself.
On the device side, I'm sure Bruce can give you some concrete
> The goal for C++ parallelism is to make it fairly transparent
> to the programmer. Or did I misunderstand what he said?
You want it to be transparent, not invisible.
>> Same caveats apply for metal (should be pretty easy to do:
>> need Objective-C support in LDC, need Metal bindings).
> Use clang to compile the objective-c code to object files and
> link with it?
Wont work, D needs to be able to call the objective-c.
I mean you could use a C or C++ shim, but that would be pretty
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