kokkos-proj-tmpl

A minimal cmake based project skeleton for developping a kokkos application

Download this skeleton

git clone --recursive git@github.com:pkestene/kokkos-proj-tmpl.git

How to build ?

Requirement

• cmake version 3.16

• note: if you are on a fairly recent OS (ex: Ubuntu 21.10, or any OS using glibc >= 2.34), you may need to turn off linking with libdl when using kokkos/cuda backend. See this issue, as nvcc (even version 11.6) apparently doesn't seem to handle empty file /usr/lib/x86_64-linux-gnu/libdl.a (stub, libdl is integrated into glibc). Hopefully this will be solved in an upcoming cuda release.

# run this to know your glibc version
ldd --version

Build with target device OpenMP

Default behavior is to download and build kokkos from source; thus you need to specifiy for which hardware target (aka Kokkos backend) you want

mkdir -p build/openmp
cd build/openmp
CXX=YOUR_COMPILER_HERE cmake -DKOKKOS_PROJ_TMPL_BACKEND=OpenMP ../..
make
# then you can run the application
./src/saxpy_kokkos_lambda.openmp

Note that option -DKokkos_ENABLE_HWLOC=ON is enabled by default.

If you already have build and installed kokkos for some target backend (OpenMP, Cuda, HIP, etc...), you don't need to specify cmake option KOKKOS_PROJ_TMPL_BACKEND, it will determine by the build system but of course you need to set env variable CMAKE_PREFIX_PATH to the directory containing file KokkosConfig.cmake inside your kokkos installation.

Build with target device CUDA

You need to have Nvidia compiler nvcc in your PATH.

CMake and Kokkos will set the compiler to nvcc_wrapper (located in kokkos sources, cloned as git submodule).

mkdir -p build/cuda
cd build/cuda
cmake -DKOKKOS_PROJ_TMPL_BACKEND=Cuda -DKokkos_ARCH_AMPERE86=ON ../..
make
# then you can run the application as before
./src/saxpy_kokkos_lambda.cuda

Of course, you will need to adapt variable Kokkos_ARCH to your actual GPU architecture (use cuda sample device_query to probe the architecture).

Depending on your OS, you may need to set variable Kokkos_CUDA_DIR to point to your CUDA SDK (if cmake is not able to figure out by itself); e.g. /usr/local/cuda-9.0

Build with target device HIP (AMD GPU)

CMake and Kokkos will set the compiler to hipcc (located in kokkos sources, cloned as git submodule).

Example:

mkdir build_hip
cd build_hip
cmake -DKOKKOS_PROJ_TMPL_BACKEND=HIP -DKokkos_ARCH_VEGA908=ON ..
make
# then you can run the application as before
./src/saxpy_kokkos_lambda.hip

Additional notes

Stream benchmark

The stream benchmark source code is slightly adapted from BabelStream.

Stencil benchmark

Here are the results obtained on different computing platforms:

Intel Skylake (2x20 cores, Intel Xeon Gold 5115, icpc 2018.0.128)

Intel KNL (icpc 2017.0.6.256, OMP_NUM_THREADS=64)

Nvidia K80, cuda 9.2

Nvidia P100, cuda 9.2

glibc 2.34 and nvlink error

If using glibc version >= 2.34 you get the following link error when building with Cuda backend:

[ 65%] Linking CXX executable saxpy_kokkos_lambda.cuda
nvlink fatal   : Could not open input file '/usr/lib/x86_64-linux-gnu/libdl.a'
make[2]: *** [src/CMakeFiles/saxpy_kokkos_lambda.cuda.dir/build.make:118: src/saxpy_kokkos_lambda.cuda] Error 1
make[1]: *** [CMakeFiles/Makefile2:1047: src/CMakeFiles/saxpy_kokkos_lambda.cuda.dir/all] Error 2
make: *** [Makefile:136: all] Error 2

One temporary solution (until fixed in a future nvcc release ?) is mentionned here: https://matsci.org/t/lammps-users-kokkos-linker-error-nvidia-libdl-a/41050

for simplicity, you just need to create a fake libdl.a, e.g. in current build dirrector

touch empty.c
gcc -fpic -c empty.c
ar rcsv libdl.a empty.o

and then reconfigure cmake with additionnal flag -DLIBDL_LIBRARY=$PWD/libdl.a and the build will work as expected.