Cross-platform programming model for many-core lattice Boltzmann simulations · HackerPapers discussions

Cross-platform programming model for many-core lattice Boltzmann simulations — mentioned by maxwell86

Mon, 16 May 2022 07:27:31 GMT

> I severely doubt that std::for_each_n exists on GPU code. https://docs.nvidia.com/hpc-sdk/compilers/c++-parallel-algor... This is 4 years old. Been using it in production for the last 2 years. Works fine. Pretty much everyone I've talked to using this in production from other research groups was able to remove all their CUDA code and replace it with this without any performance hit. There are some recent publications about this, but most of them are quite old right now cause this is not new anymore: https://arxiv.org/abs/2010.11751

Paper and discussion history. A mention is not an endorsement.

Cross-platform programming model for many-core lattice Boltzmann simulations — mentioned by volta83

Tue, 16 Nov 2021 18:33:52 GMT

This paper ported a CFD application, which had a tuned CUDA implementation, to std::par: https://arxiv.org/pdf/2010.11751.pdf . In Table 3, first and last columns shows the performance of CUDA and std::par in % of theoretical peak. The rows show results for different GPU architectures. On V100, CUDA achieves 62% theoretical peak and std::par 58%. The amount of developer effort required to achieve over 50% theoretical peak with std::par makes it a no brainer IMO. If there is one kernel where you need more performance, you can always implement that kernel in CUDA, but for 99% of the kernels in…

Paper and discussion history. A mention is not an endorsement.