dbcsr_example_1: how to create a dbcsr matrix (fortran)dbcsr_example_2: how to set a dbcsr matrix (fortran)dbcsr_example_3: how to multiply two dbcsr matrices (fortran and cpp)dbcsr_tensor_example_1: how to create a dbcsr matrix (fortran)- the example can be run with different parameters, controlling block size, sparsity, verbosity and more
dbcsr_tensor_example_2: tensor contraction example (cpp)- tensor1 x tensor2 = tensor3, (13|2)x(54|21)=(3|45)
See the examples' documentation.
Compile the DBCSR library, using -DUSE_MPI=ON -DWITH_EXAMPLES=ON.
The examples require MPI. Furthermore, if you are using threading, MPI_THREAD_FUNNELED mode is required.
You can run the examples, for instance from the build directory, as follows:
srun -N 1 --ntasks-per-core 2 --ntasks-per-node 12 --cpus-per-task 2 ./examples/dbcsr_example_1How to run (this example and DBCSR for tensors in general):
- best performance is obtained by running with mpi and one openmp thread per rank.
- ideally number of mpi ranks should be composed of small prime factors (e.g. powers of 2).
- for sparse data & heterogeneous block sizes, DBCSR should be run on CPUs with libxsmm backend.
- for dense data best performance is obtained by choosing homogeneous block sizes of 64 and by compiling with GPU support.