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DOI

benchParanumal

benchParanumal contains several benchmark problems set out, or inspired by, the Center for Efficient Exascale Discretizations (CEED) Bake-off Problems.

How to compile benchParanumal

There are a couple of prerequisites for building benchParanumal;

  • MPI
  • OpenBlas

Installing MPI and OpenBlas can be done using whatever package manager your operating system provides.

OCCA is packaged with benchParanumal in a git submodule. Either clone with --recursive or run

git submodule init
git submoduel update

To build benchParanumal:

$ git clone --recursive https://github.com/paranumal/benchparanumal
$ cd benchparanumal
$ export LIBP_BLAS_DIR=</path/to/openblas>
$ make -j `nproc`

If your MPI supports GPU-aware RDMA functionality, you can optionally build benchParanumal with this support via:

$ make -j `nproc` --gpu-aware-mpi=true

How to run benchParanumal

benchParanumal contains two distinct types of tests:

  1. BK - Benchmark Kernels
  2. BP - Benchmark Problems

The usage of each benchmark, outside of the provide run scripts, can be found with the -h option. For example:

$ mpirun -np 1 ./BK/BK1/BK1 -h

Name:     [THREAD MODEL]
CL keys:  [-m, --mode]
Description: OCCA's Parallel execution platform
Possible values: { Serial, OpenMP, CUDA, HIP, OpenCL }

Name:     [PLATFORM NUMBER]
CL keys:  [-pl, --platform]
Description: Parallel platform number (used in OpenCL mode)

Name:     [DEVICE NUMBER]
CL keys:  [-d, --device]
Description: Parallel device number

Name:     [ELEMENT TYPE]
CL keys:  [-e, --elements]
Description: Type of mesh elements
Possible values: { Tri, Quad, Tet, Hex }

Name:     [BOX NX]
CL keys:  [-nx, --dimx]
Description: Number of elements in X-dimension per rank

Name:     [BOX NY]
CL keys:  [-ny, --dimy]
Description: Number of elements in Y-dimension per rank

Name:     [BOX NZ]
CL keys:  [-nz, --dimz]
Description: Number of elements in Z-dimension per rank

Name:     [POLYNOMIAL DEGREE]
CL keys:  [-p, --degree]
Description: Degree of polynomial finite element space
Possible values: { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 }

Name:     [VERBOSE]
CL keys:  [-v, --verbose]
Description: Enable verbose output
Possible values: { TRUE, FALSE }

Name:     [HELP]
CL keys:  [-h, --help]
Description: Print this help message

Here is an example large problem size that you can run on one GPU:

$ mpirun -np 1 ./BP/BP5/BP5 -m HIP -nx 24 -ny 24 -nz 24 -p 15 -v

Running on multiple GPUs can by done by passing a larger argument to np:

$ mpirun -np 4 ./BP/BP5/BP5 -m HIP -nx 24 -ny 24 -nz 24 -p 15 -v

Verifying correctness

To verify that the computation is correct, add the -v option to the command line. Example output towards the end of the run may look like this:

CG: it 96, r norm 1.405229334496e-04, alpha = 2.686587e+00
CG: it 97, r norm 1.375460859099e-04, alpha = 2.540830e+00
CG: it 98, r norm 1.198097786957e-04, alpha = 2.780510e+00
CG: it 99, r norm 1.108821042895e-04, alpha = 2.907639e+00
CG: it 100, r norm 9.086922290200e-05, alpha = 2.946219e+00
BP5: N, DOFs, elapsed, iterations, time per DOF, avg BW (GB/s), avg GFLOPs, DOFs*iterations/ranks*time
4, 68921, 0.0216, 100, 3.13e-07, 81.5, 49.8, 3.20e+08

The printed value of r norm at the end of 100 CG iterations should be small.

How to clean build objects

To clean the benchParanumal build objects:

$ make realclean

Please invoke make help for more supported options.