This page gives hints on how to set parameters for a parallel calculation with the ABINIT package.
Running ABINIT in parallel (MPI 10 processors) can be as simple as:
mpirun -n 10 abinit run.abi > log 2> err
or (MPI 10 processors + OpenMP 4 threads):
export OMP_NUM_THREADS=4 mpirun -n 10 abinit run.abi > log 2> err
In the latter, the standard output of the application is redirected to
err collects the standard error.
The command mpirun might possibly be replaced by mpiexec depending on your system.
For ground-state calculations, the code has been parallelized (MPI-based parallelism) on the k-points, the spins, the spinor components, the bands, and the FFT grid and plane wave coefficients. For the k-point and spin parallelisations (using MPI), the communication load is generally very small. and the parallel efficiency very good provided the number of MPI procs divide the number of k-points in the IBZ. However, the number of nodes that can be used with this kind of k-point/spin distribution might be small, and depends strongly on the physics of the problem. A combined FFT / band parallelisation (LOBPCG with paral_kgb 1) is available [Bottin2008], and has shown very large speed up (>1000) on powerful computers with a large number of processors and high-speed interconnect. The combination of FFT / band / k point and spin parallelism is also available, and quite efficient for such computers. Available for norm-conserving as well as PAW cases. Automatic determination of the best combination of parallelism levels is available. Use of MPI-IO is mandatory for the largest speed ups to be observed.
Chebyshev filtering (Chebfi) is a method to solve the linear eigenvalue problem, and can be used as a SCF solver in Abinit. It is implemented in Abinit [Levitt2015]. The design goal is for Chebfi to replace LOBPCG as the solver of choice for large-scale computations in Abinit. By performing less orthogonalizations and diagonalizations than LOBPCG, scaling to higher processor counts is possible. A manual to use Chebfi is available here
For ground-state calculations, with a set of images (e.g. nudged elastic band method, the string method, the path-integral molecular dynamics, the genetic algorithm), MPI-based parallelism is used. The workload for the different images has been distributed. This parallelization level can be combined with the parallelism described above, leading to speed-up beyond 5000.
For ground-state calculations, GPUs can be used. The implementation is based on CUDA+MAGMA.
For ground-state calculations, the wavelet part of ABINIT (BigDFT) is also very well parallelized: MPI band parallelism, combined with GPUs.
For response calculations, the code has been MPI-parallelized on k-points, spins, bands, as well as on perturbations. For the k-points, spins and bands parallelisation, the communication load is rather small also, and, unlike for the GS calculations, the number of nodes that can be used in parallel will be large, nearly independently of the physics of the problem. Parallelism on perturbations is very similar to the parallelism on images in the ground state case (so, very efficient), although the load balancing problem for perturbations with different number of k points is not adressed at present. Use of MPI-IO is mandatory for the largest speed ups to be observed.
GW calculations are MPI-parallelized over k-points. They are also parallelized over transitions (valence to conduction band pairs), but the two parallelisation cannot be used currently at present. The transition parallelism has been show to allow speed ups as large as 300.
Ground state, response function, and GW parallel calculations can be done also by using OpenMP parallelism, even combined with MPI parallelism.
Related Input Variables¶
- autoparal AUTOmatisation of the PARALlelism
- paral_atom activate PARALelization over (paw) ATOMic sites
- paral_kgb activate PARALelization over K-point, G-vectors and Bands
- paral_rf Activate PARALlelization over Response Function perturbations
- bandpp BAND Per Processor
- gwpara GW PARAllelization level
- max_ncpus MAXimum Number of CPUS
- npband Number of Processors at the BAND level
- npfft Number of Processors at the FFT level
- nphf Number of Processors for (Hartree)-Fock exact exchange
- npimage Number of Processors at the IMAGE level
- npkpt Number of Processors at the K-Point Level
- nppert Number of Processors at the PERTurbation level
- npspinor Number of Processors at the SPINOR level
- gpu_devices GPU: choice of DEVICES on one node
- gpu_linalg_limit GPU (Cuda): LINear ALGebra LIMIT
- iomode Input-Output MODE
- localrdwf LOCAL ReaD WaveFunctions
- np_slk Number of mpi Processors used for ScaLapacK calls
- pw_unbal_thresh Plane Wave UNBALancing: THRESHold for balancing procedure
- slk_rankpp ScaLapacK matrix RANK Per Process
- use_gemm_nonlop USE the GEMM routine for the application of the NON-Local OPerator
- use_gpu_cuda activate USE of GPU accelerators with CUDA (nvidia)
- use_slk USE ScaLapacK
Selected Input Files¶
- An introduction on ABINIT in Parallel should be read before going to the next tutorials about parallelism. One simple example of parallelism in ABINIT will be shown.
- Parallelism for ground-state calculations, with plane waves presents the combined k-point (K), plane-wave (G), band (B), spin/spinor parallelism of ABINIT (so, the “KGB” parallelism), for the computation of total energy, density, and ground state properties
- Parallelism for molecular dynamics calculations
- Parallelism based on “images”, e.g. for the determination of transitions paths (NEB, string method) or PIMD, that can be activated on top of the “KGB” parallelism for force calculations.
- Parallelism for ground-state calculations, with wavelets presents the parallelism of ABINIT, when wavelets are used as a basis function instead of planewaves, for the computation of total energy, density, and ground state properties
- Parallelism of response-function calculations - you need to be familiarized with the calculation of linear-response properties within ABINIT, see the tutorial Response-Function 1 (RF1)
- Parallelism of Many-Body Perturbation calculations (GW) allows to speed up the calculation of accurate electronic structures (quasi-particle band structure, including many-body effects).