Questions Regarding GPU Acceleration

[dmicje12]

Hello everyone, I would like to use my RTX 5080 for GPU acceleration.
However, after running I get the following message:

**Back Engine Exception : PETSc error 76 of type 0 in MatSeqAIJCUSPARSECopyToGPU:2488: This program was not compiled for SM 120
: cudaErrorInvalidDevice: invalid device ordinal
** Location of Exception : petsc_impl.h:90
May I ask if the RTX 5080 is currently not supported? Or is there any other way to enable GPU acceleration with the RTX 5080?

Thank you, everyone!

[filipr]

QuantumATK relies on the PETSc library for some sparse matrix operations. It appears that PETSC uses one of a few specialized CUDA functions that are not compatible with newer compute capabilities (your RTX 5080 has compute capability 12.0 = SM120 as per this chart). Basically your GPU is too new to be used for the PETSc library shipped with QuantumATK. The compatible compute capabilities has to be chosen when compiling the PETSc source code, so it is baked in. So for now you can't use your RTX gpu for doing calculations that involve PETSc operations.

However, even if it did work it likely wouldn't be faster than running on CPU. RTX 5080 is a GPU primarily designed for graphics processing and it only has 384 FP64 floating point units - 2 per streaming multiprocessor, so reportedly you only get 1/64 of the FLOP throughput. Scientific calculations mostly rely on 64 bit floating point numbers for accuracy in the algorithms. For scientific computations one should use specific GPUs with many FP64 units as is the case for the A, H and B series data center GPUs.

The RTX 5080 sounds like a blast for gaming, though 

[dmicje12]

Thank you for your response!
I would like to know how your team evaluated the acceleration performance of the V100. Was the improvement significant?
I understand that the V100 is certainly not as powerful as the A100 or H100, but how does the V100 compare to a server-grade CPU (such as the EPYC 7F72 shown in the manual)?
Thanks!