OpenACC GPU port of VASP: Difference between revisions
Vaspmaster (talk | contribs) No edit summary |
Vaspmaster (talk | contribs) |
||
| Line 17: | Line 17: | ||
* An installation of [https://developer.nvidia.com/cuda-toolkit NVIDIA's CUDA Toolkit] (>= 10.0): the necessary parts are already bundled into the [https://developer.nvidia.com/hpc-sdk NVIDIA HPC-SDK] and PGI's Compilers & Tools, so there is no need to separately install the CUDA Toolkit if you use either of the latter compiler suites. | * An installation of [https://developer.nvidia.com/cuda-toolkit NVIDIA's CUDA Toolkit] (>= 10.0): the necessary parts are already bundled into the [https://developer.nvidia.com/hpc-sdk NVIDIA HPC-SDK] and PGI's Compilers & Tools, so there is no need to separately install the CUDA Toolkit if you use either of the latter compiler suites. | ||
* A CUDA-aware version of MPI. | |||
<u>''Drivers''</u> | <u>''Drivers''</u> | ||
Revision as of 19:34, 26 January 2021
With VASP.6.2.0 we officially released the OpenACC GPU-port of VASP: Official in the sense that we now strongly recommend to use this OpenACC version to run VASP on GPU accelerated systems.
The previous CUDA-C GPU-port of VASP is considered to be deprecated and is no longer actively developed, maintained, or supported. In the near future, the CUDA-C GPU-port of VASP will be dropped completely.
Requirements
Software stack
Compiler
- To compile the OpenACC version of VASP you need either the NVIDIA HPC-SDK or a recent version (>=19.10) of PGI's Compilers & Tools.
- In principle any compiler that supports at least OpenACC standard 2.6 should do the trick, but we have tried and tested the aforementioned ones.
Libraries
- When compiling with PGI Compilers & Tools: the QD (software emulated quadruple precision arithmetic) and NCCL (>=2.7.8) libraries. (Conveniently, these libraries are part of the NVIDIA HPC-SDK.)
- An installation of NVIDIA's CUDA Toolkit (>= 10.0): the necessary parts are already bundled into the NVIDIA HPC-SDK and PGI's Compilers & Tools, so there is no need to separately install the CUDA Toolkit if you use either of the latter compiler suites.
- A CUDA-aware version of MPI.
Drivers
- You need a CUDA driver that supports at least CUDA-10.0 (see above).
Hardware
We have only tested the OpenACC GPU-port of VASP with the following NVIDIA GPUs:
- NVIDIA datacenter GPUs: P100 (Pascal), V100 (Volta), and A100 (Ampere).
- NVIDIA Quadro GPUs: GP100 (Pascal), and GV100 (Volta).
N.B.: Running VASP on other NVIDIA GPUs (e.g. "gaming" hardware) is technically possible but not advisable: these GPUs are not well suited since they do not offer fast double precision floating point arithmetic (FP64) performance and in general have smaller memories without error correction code (ECC) capabilities.