[CP2K-user] [CP2K:22090] GPU vs CPU performance on consumer workstation

[rafa...@gmail.com]

Hello, I'm testing CP2K performance on an older workstation PC and I'm 
finding that a the CPU version of CP2k 2025.2 is faster than the GPU 
version. My understanding is that many consumer GPUs do not have great 
double precision performance, but I can't tell if the slower GPU timing is 
normal for my system or if there is anything I can improve? For example, a 
CPU-only H2O-32.inp benchmark is twice as fast as a GPU run. The timings 
show that "grid_collocate_task_list" and "grid_integrate_task_list" are the 
most time consuming steps.

I came across a similar thread from 2018 issue73 
<https://github.com/cp2k/cp2k/issues/73>, but I wonder how those comments 
hold up for the 2025.2 CP2K version? Should I expect any performance gains 
from a GPU on small systems (<250 atoms)? I attached the ARCH files I used 
to build the CPU and GPU versions of CP2K along with the output files from 
the H2O-32.inp benchmarks.

My system has: hyperthreaded 4-core AMD Ryzen 5 2400G CPU, NVIDIA RTX 3050 
6gb GPU, and 16gb RAM.

For CPU runs I use 4 MPI ranks with 2 OMP threads to get full CPU 
utilization. For GPU runs I use 1 MPI rank with 2 OMP threads, increasing 
OMP_NUM_THREADS to 4, 6, 8 does not show increased CPU utilization during a 
GPU run.

(I am unable to run H20-64.inp on GPU because of a CUDA OOM error: ERROR: 
"cudaErrorLaunchOutOfResources" at 
/home/raf/cp2k-home/cp2k-colordiffusion/cp2k-2025.2/src/grid/gpu/grid_gpu_collocate.cu:387 
)

Thanks,
Rafal

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