@schwarzmaler20@aiHax_on_X@HannesPreishub Dem stimme ich zu. AI kann derzeit auch nicht den Überblick über den ganzen Code behalten. Punktuel ist sie sehr gut aber nur wenn mam sie anleitet. AI kann auch nicht extrapolieren und Visionen entwickeln.
@ChShersh I like it ❤️, using a zip iterator is possible too but looks sometimes odd.
What I like here is that `i` could also be an iterator, it can be taversed e.g. until the range iterator returns a specific value and only than you access `i`.
It also shows that both are strongly coupled
@svadrb@SebAaltonen It depends strongly on how you use the tools. If the ai has full access to your code base and can run tests by its own the code becomes much better.
@OjasSharma276 My suggestion is adding the new compiler directly to the CI after a new version is released.
In our projects (OpenSource) we support 4 or more releases per compiler gcc/clang/nvcc/msvc(depending on the project because main OS is linux), icpx.
@zuhaitz_dev Beside that fact that this benchmark is useless CPU, compiler and flags are missing, for C/C++ this is on of the most important information.
@jithu83@_streetdogg They are equal. We added in our projects the rule that you should write the constbalways on the right side so beginners know that the left hand of the const is constant.
I dislike this rule but for someone who is seldom writing C++ it is easier.
@madhav1 If you do not want to run your code only on NVidia GPUs have a look into alpaka https://t.co/CU9RYKLe7l
Here is an example for vector multiply, change std::multiply with std::plus and you have a vectorAdd running on GPUs and CPUs.
Run it in godbolt https://t.co/ZbeFUmdfUZ
@blueberry_55555@basit_ayantunde Write code which is running in GPUs. If the stl function is jot constexpr you can not use it on GPU. The you start to write your own linkedblist implementation, chunked allocators, ...
@SebAaltonen Data access is not required to return the identity of data. An access can be a transformation e.g. compression, a derivation from other data fields of the object, ...
@SebAaltonen The problem is that many develops think that the oop objects are layout in memory must be equal to the object hierarchy.
That's wrong, you should seperate the user domain oop layout from the memory layout.
C++ ca do this with zero overhead: https://t.co/KAs0ttCQfD
🚀 alpaka 1.2.0 is here! 🎉 Now you can easily target the wide variety of GPU accelerators and CPU hardware with our latest release. 🦙
https://t.co/0TAEr35gyy