Guidelines for using raw pointers in modern C++ and GPUs

• CppCoreGuidelines

  306 41,497 7.6 Python

  The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++

  

Here ist the explanation: https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines#r3-a-raw-pointer-a-t-is-non-owning

• CHAI

  1 103 6.8 C++

  Copy-hiding array abstraction to automatically migrate data between memory spaces (by LLNL)

  

I believe most of these performance portability libraries have associated memory manager projects. For example, RAJA has CHAI. I would use those managed array classes.

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• gtensor

  1 33 8.9 C++

  GTensor is a multi-dimensional array C++14 header-only library for hybrid GPU development.

  

If you want something like thrust:: device_vector, that also supports intel GPUs via SYCL (AMD has rocThrust but no intel equivalent AFAIK), checkout our project https://github.com/wdmapp/gtensor/. It also has multi-d arrays and lazy evaluation of complex array expressions. and experimental cross vendor gpu BLAS and FFT with a nicer interface.

• stlbm

  1 - -

Have you seen this? https://gitlab.com/unigehpfs/stlbm

• CuTeLib

  1 0 7.8 C++

  Discontinued CUDA Template Library provides simple, typesafe, performant constructs for C++ CUDA projects

I am building a similarly library, including copy and streams and so on. Check it out https://github.com/anders-wind/CuTeLib

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