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Kokkos is a templated C++ library that provides abstractions to allow a single implementation of an application kernel (e.g. a collision style) to run efficiently on different kinds of hardware, such as GPUs, Intel Xeon Phis, or many-core CPUs. Kokkos maps the C++ kernel onto different backend languages such as CUDA, OpenMP, or Pthreads. The Kokkos library also provides data abstractions to adjust (at compile time) the memory layout of data structures like 2d and 3d arrays to optimize performance on different hardware. For more information on Kokkos, see Github. Kokkos is part of Trilinos. The Kokkos library was written primarily by Carter Edwards, Christian Trott, and Dan Sunderland (all Sandia).
The SPARTA KOKKOS package contains versions of collide, fix, and compute styles that use data structures and macros provided by the Kokkos library, which is included with SPARTA in /lib/kokkos. The KOKKOS package was developed primarily by Stan Moore (Sandia) with contributions of various styles by others, including Dan Ibanez (Sandia), Tim Fuller (Sandia), and Sam Mish (Sandia). For more information on developing using Kokkos abstractions see the Kokkos programmers' guide at /lib/kokkos/doc/Kokkos_PG.pdf.
The KOKKOS package currently provides support for 3 modes of execution (per MPI task). These are Serial (MPI-only for CPUs and Intel Phi), OpenMP (threading for many-core CPUs and Intel Phi), and CUDA (for NVIDIA GPUs). You choose the mode at build time to produce an executable compatible with specific hardware.
NOTE: Kokkos support within SPARTA must be built with a C++14 compatible compiler. For a list of compilers that have been tested with the Kokkos library, see the Kokkos README.
Building SPARTA with the KOKKOS package with Makefiles:
To build with the KOKKOS package, start with the provided Kokkos Makefiles in /src/MAKE/. You may need to modify the KOKKOS_ARCH variable in the Makefile to match your specific hardware. For example:
Building SPARTA with the KOKKOS package with CMake:
To build with the KOKKOS package, start with the provided preset files in /cmake/presets/. You may need to set -D Kokkos_ARCH_TYPE=ON to match your specific hardware. For example:
See the Advanced Kokkos Options section below for a listing of all Kokkos architecture options.
Compile for CPU-only (MPI only, no threading):
Use a C++14 compatible compiler and set Kokkos architicture variable in as described above. Then do the following:
cd sparta/src make yes-kokkos make kokkos_mpi_only
cd build cmake -C /path/to/sparta/cmake/presets/kokkos_mpi_only.cmake make
Compile for CPU-only (MPI plus OpenMP threading):
NOTE: To build with Kokkos support for OpenMP threading, your compiler must support the OpenMP interface. You should have one or more multi-core CPUs so that multiple threads can be launched by each MPI task running on a CPU.
Use a C++14 compatible compiler and set Kokkos architecture variable in as described above. Then do the following:
cd sparta/src make yes-kokkos make kokkos_omp
cd build cmake -C /path/to/sparta/cmake/presets/kokkos_omp.cmake make
Compile for Intel KNL Xeon Phi (Intel Compiler, OpenMPI):
Use a C++14 compatible compiler and do the following:
cd sparta/src make yes-kokkos make kokkos_phi
cd build cmake -C /path/to/sparta/cmake/presets/kokkos_phi.cmake make
Compile for CPUs and GPUs (with OpenMPI or MPICH):
NOTE: To build with Kokkos support for NVIDIA GPUs, NVIDIA CUDA software version 7.5 or later must be installed on your system.
Use a C++14 compatible compiler and set Kokkos architecture variable in for both GPU and CPU as described above. Then do the following:
cd sparta/src make yes-kokkos make kokkos_cuda
cd build cmake -C /path/to/sparta/cmake/presets/kokkos_cuda.cmake make
Running SPARTA with the KOKKOS package:
All Kokkos operations occur within the context of an individual MPI task running on a single node of the machine. The total number of MPI tasks used by SPARTA (one or multiple per compute node) is set in the usual manner via the mpirun or mpiexec commands, and is independent of Kokkos. The mpirun or mpiexec command sets the total number of MPI tasks used by SPARTA (one or multiple per compute node) and the number of MPI tasks used per node. E.g. the mpirun command in OpenMPI does this via its -np and -npernode switches. Ditto for MPICH via -np and -ppn.
Running on a multi-core CPU:
Here is a quick overview of how to use the KOKKOS package for CPU acceleration, assuming one or more 16-core nodes.
mpirun -np 16 spa_kokkos_mpi_only -k on -sf kk -in in.collide # 1 node, 16 MPI tasks/node, no multi-threading mpirun -np 2 -ppn 1 spa_kokkos_omp -k on t 16 -sf kk -in in.collide # 2 nodes, 1 MPI task/node, 16 threads/task mpirun -np 2 spa_kokkos_omp -k on t 8 -sf kk -in in.collide # 1 node, 2 MPI tasks/node, 8 threads/task mpirun -np 32 -ppn 4 spa_kokkos_omp -k on t 4 -sf kk -in in.collide # 8 nodes, 4 MPI tasks/node, 4 threads/task
To run using the KOKKOS package, use the "-k on", "-sf kk" and "-pk kokkos" command-line switches in your mpirun command. You must use the "-k on" command-line switch to enable the KOKKOS package. It takes additional arguments for hardware settings appropriate to your system. Those arguments are documented here. For OpenMP use:
-k on t Nt
The "t Nt" option specifies how many OpenMP threads per MPI task to use with a node. The default is Nt = 1, which is MPI-only mode. Note that the product of MPI tasks * OpenMP threads/task should not exceed the physical number of cores (on a node), otherwise performance will suffer. If hyperthreading is enabled, then the product of MPI tasks * OpenMP threads/task should not exceed the physical number of cores * hardware threads. The "-k on" switch also issues a "package kokkos" command (with no additional arguments) which sets various KOKKOS options to default values, as discussed on the package command doc page.
The "-sf kk" command-line switch will automatically append the "/kk" suffix to styles that support it. In this manner no modification to the input script is needed. Alternatively, one can run with the KOKKOS package by editing the input script as described below.
NOTE: When using a single OpenMP thread, the Kokkos Serial backend (i.e. Makefile.kokkos_mpi_only) will give better performance than the OpenMP backend (i.e. Makefile.kokkos_omp) because some of the overhead to make the code thread-safe is removed.
NOTE: The default for the package kokkos command is to use "threaded" communication. However, when running on CPUs, it will typically be faster to use "classic" non-threaded communication. Use the "-pk kokkos" command-line switch to change the default package kokkos options. See its doc page for details and default settings. Experimenting with its options can provide a speed-up for specific calculations. For example:
mpirun -np 16 spa_kokkos_mpi_only -k on -sf kk -pk kokkos comm classic -in in.collide # non-threaded comm
For OpenMP, the KOKKOS package uses data duplication (i.e. thread-private arrays) by default to avoid thread-level write conflicts in some compute styles. Data duplication is typically fastest for small numbers of threads (i.e. 8 or less) but does increase memory footprint and is not scalable to large numbers of threads. An alternative to data duplication is to use thread-level atomics, which don't require duplication. When using the Kokkos Serial backend or the OpenMP backend with a single thread, no duplication or atomics are used. For CUDA, the KOKKOS package always uses atomics in these computes when necessary. The use of atomics instead of duplication can be forced by compiling with the "-DSPARTA_KOKKOS_USE_ATOMICS" compile switch.
Core and Thread Affinity:
When using multi-threading, it is important for performance to bind both MPI tasks to physical cores, and threads to physical cores, so they do not migrate during a simulation.
If you are not certain MPI tasks are being bound (check the defaults for your MPI installation), binding can be forced with these flags:
OpenMPI 1.8: mpirun -np 2 -bind-to socket -map-by socket ./spa_openmpi ... Mvapich2 2.0: mpiexec -np 2 -bind-to socket -map-by socket ./spa_mvapich ...
For binding threads with KOKKOS OpenMP, use thread affinity environment variables to force binding. With OpenMP 3.1 (gcc 4.7 or later, intel 12 or later) setting the environment variable OMP_PROC_BIND=true should be sufficient. In general, for best performance with OpenMP 4.0 or better set OMP_PROC_BIND=spread and OMP_PLACES=threads. For binding threads with the KOKKOS pthreads option, compile SPARTA the KOKKOS HWLOC=yes option as described below.
Running on Knight's Landing (KNL) Intel Xeon Phi:
Here is a quick overview of how to use the KOKKOS package for the Intel Knight's Landing (KNL) Xeon Phi:
KNL Intel Phi chips have 68 physical cores. Typically 1 to 4 cores are reserved for the OS, and only 64 or 66 cores are used. Each core has 4 hyperthreads, so there are effectively N = 256 (4*64) or N = 264 (4*66) cores to run on. The product of MPI tasks * OpenMP threads/task should not exceed this limit, otherwise performance will suffer. Note that with the KOKKOS package you do not need to specify how many KNLs there are per node; each KNL is simply treated as running some number of MPI tasks.
Examples of mpirun commands that follow these rules are shown below.
Intel KNL node with 64 cores (256 threads/node via 4x hardware threading): mpirun -np 64 spa_kokkos_phi -k on t 4 -sf kk -in in.collide # 1 node, 64 MPI tasks/node, 4 threads/task mpirun -np 66 spa_kokkos_phi -k on t 4 -sf kk -in in.collide # 1 node, 66 MPI tasks/node, 4 threads/task mpirun -np 32 spa_kokkos_phi -k on t 8 -sf kk -in in.collide # 1 node, 32 MPI tasks/node, 8 threads/task mpirun -np 512 -ppn 64 spa_kokkos_phi -k on t 4 -sf kk -in in.collide # 8 nodes, 64 MPI tasks/node, 4 threads/task
The -np setting of the mpirun command sets the number of MPI tasks/node. The "-k on t Nt" command-line switch sets the number of threads/task as Nt. The product of these two values should be N, i.e. 256 or 264.
NOTE: The default for the package kokkos command is to use "threaded" communication. However, when running on KNL, it will typically be faster to use "classic" non-threaded communication. Use the "-pk kokkos" command-line switch to change the default package kokkos options. See its doc page for details and default settings. Experimenting with its options can provide a speed-up for specific calculations. For example:
mpirun -np 64 spa_kokkos_phi -k on t 4 -sf kk -pk kokkos comm classic -in in.collide # non-threaded comm
NOTE: MPI tasks and threads should be bound to cores as described above for CPUs.
NOTE: To build with Kokkos support for Intel Xeon Phi coprocessors such as Knight's Corner (KNC), your system must be configured to use them in "native" mode, not "offload" mode.
Running on GPUs:
Use the "-k" command-line switch to specify the number of GPUs per node, and the number of threads per MPI task. Typically the -np setting of the mpirun command should set the number of MPI tasks/node to be equal to the # of physical GPUs on the node. You can assign multiple MPI tasks to the same GPU with the KOKKOS package, but this is usually only faster if significant portions of the input script have not been ported to use Kokkos. Using CUDA MPS is recommended in this scenario. As above for multi-core CPUs (and no GPU), if N is the number of physical cores/node, then the number of MPI tasks/node should not exceed N.
-k on g Ng
Here are examples of how to use the KOKKOS package for GPUs, assuming one or more nodes, each with two GPUs.
mpirun -np 2 spa_kokkos_cuda -k on g 2 -sf kk -in in.collide # 1 node, 2 MPI tasks/node, 2 GPUs/node mpirun -np 32 -ppn 2 spa_kokkos_cuda -k on g 2 -sf kk -in in.collide # 16 nodes, 2 MPI tasks/node, 2 GPUs/node (32 GPUs total)
NOTE: The default for the package kokkos command is to use "parallel" reduction of statistics along with threaded communication. However, using "atomic" reduction is typically faster for GPUs. Use the "-pk kokkos" command-line switch to change the default package kokkos options. See its doc page for details and default settings. Experimenting with its options can provide a speed-up for specific calculations. For example:
mpirun -np 2 spa_kokkos_cuda -k on g 2 -sf kk -pk kokkos reduction atomic -in in.collide # set reduction = atomic
NOTE: Using OpenMP threading and CUDA together is currently not possible with the SPARTA KOKKOS package.
NOTE: For good performance of the KOKKOS package on GPUs, you must have Kepler generation GPUs (or later). The Kokkos library exploits texture cache options not supported by Telsa generation GPUs (or older).
NOTE: When using a GPU, you will achieve the best performance if your input script does not use fix or compute styles which are not yet Kokkos-enabled. This allows data to stay on the GPU for multiple timesteps, without being copied back to the host CPU. Invoking a non-Kokkos fix or compute, or performing I/O for stat or dump output will cause data to be copied back to the CPU incurring a performance penalty.
Run with the KOKKOS package by editing an input script:
Alternatively the effect of the "-sf" or "-pk" switches can be duplicated by adding the package kokkos or suffix kk commands to your input script.
The discussion above for building SPARTA with the KOKKOS package, the mpirun/mpiexec command, and setting appropriate thread are the same.
You must still use the "-k on" command-line switch to enable the KOKKOS package, and specify its additional arguments for hardware options appropriate to your system, as documented above.
You can use the suffix kk command, or you can explicitly add a "kk" suffix to individual styles in your input script, e.g.
collide vss/kk air ar.vss
You only need to use the package kokkos command if you wish to change any of its option defaults, as set by the "-k on" command-line switch.
Speed-ups to expect:
The performance of KOKKOS running in different modes is a function of your hardware, which KOKKOS-enable styles are used, and the problem size.
Generally speaking, when running on CPUs only, with a single thread per MPI task, the performance difference of a KOKKOS style and (un-accelerated) styles (MPI-only mode) is typically small (less than 20%).
See the Benchmark page of the SPARTA web site for performance of the KOKKOS package on different hardware.
Advanced Kokkos options:
There are other allowed options when building with the KOKKOS package. A few options are listed here; for a full list of all options, please refer to the Kokkos documentation. As above, these options can be set as variables on the command line, in a Makefile, or in a CMake presets file. For default CMake values, see cmake -LH | grep -i kokkos.
The CMake option Kokkos_ENABLE_OPTION or the makefile setting KOKKOS_DEVICE=OPTION sets the parallelization method used for Kokkos code (within SPARTA). For example, the CMake option Kokkos_ENABLE_SERIAL=ON or the makefile setting KOKKOS_DEVICES=SERIAL means that no threading will be used. The CMake option Kokkos_ENABLE_OPENMP=ON or the makefile setting KOKKOS_DEVICES=OPENMP means that OpenMP threading will be used. The CMake option Kokkos_ENABLE_CUDA=ON or the makefile setting KOKKOS_DEVICES=CUDA means an NVIDIA GPU running CUDA will be used.
As described above, the CMake option Kokkos_ARCH_TYPE=ON or the makefile setting KOKKOS_ARCH=TYPE enables compiler switches needed when compiling for a specific hardware:
|Arch-ID||HOST or GPU||Description|
|AMDAVX||HOST||AMD 64-bit x86 CPU (AVX 1)|
|EPYC||HOST||AMD EPYC Zen class CPU (AVX 2)|
|ARMV80||HOST||ARMv8.0 Compatible CPU|
|ARMV81||HOST||ARMv8.1 Compatible CPU|
|ARMV8_THUNDERX||HOST||ARMv8 Cavium ThunderX CPU|
|ARMV8_THUNDERX2||HOST||ARMv8 Cavium ThunderX2 CPU|
|WSM||HOST||Intel Westmere CPU (SSE 4.2)|
|SNB||HOST||Intel Sandy/Ivy Bridge CPU (AVX 1)|
|HSW||HOST||Intel Haswell CPU (AVX 2)|
|BDW||HOST||Intel Broadwell Xeon E-class CPU (AVX 2 + transactional mem)|
|SKX||HOST||Intel Sky Lake Xeon E-class HPC CPU (AVX512 + transactional mem)|
|KNC||HOST||Intel Knights Corner Xeon Phi|
|KNL||HOST||Intel Knights Landing Xeon Phi|
|BGQ||HOST||IBM Blue Gene/Q CPU|
|POWER7||HOST||IBM POWER7 CPU|
|POWER8||HOST||IBM POWER8 CPU|
|POWER9||HOST||IBM POWER9 CPU|
|KEPLER30||GPU||NVIDIA Kepler generation CC 3.0 GPU|
|KEPLER32||GPU||NVIDIA Kepler generation CC 3.2 GPU|
|KEPLER35||GPU||NVIDIA Kepler generation CC 3.5 GPU|
|KEPLER37||GPU||NVIDIA Kepler generation CC 3.7 GPU|
|MAXWELL50||GPU||NVIDIA Maxwell generation CC 5.0 GPU|
|MAXWELL52||GPU||NVIDIA Maxwell generation CC 5.2 GPU|
|MAXWELL53||GPU||NVIDIA Maxwell generation CC 5.3 GPU|
|PASCAL60||GPU||NVIDIA Pascal generation CC 6.0 GPU|
|PASCAL61||GPU||NVIDIA Pascal generation CC 6.1 GPU|
|VOLTA70||GPU||NVIDIA Volta generation CC 7.0 GPU|
|VOLTA72||GPU||NVIDIA Volta generation CC 7.2 GPU|
|TURING75||GPU||NVIDIA Turing generation CC 7.5 GPU|
|AMPERE80||GPU||NVIDIA Ampere generation CC 8.0 GPU|
|VEGA900||GPU||AMD GPU MI25 GFX900|
|VEGA906||GPU||AMD GPU MI50/MI60 GFX906|
|INTEL_GEN||GPU||Intel GPUs Gen9+|
The CMake option Kokkos_ENABLE_CUDA_OPTION or the makefile setting KOKKOS_CUDA_OPTIONS=OPTION are additional options for CUDA. For example, the CMake option Kokkos_ENABLE_CUDA_UVM=ON or the makefile setting KOKKOS_CUDA_OPTIONS="enable_lambda,force_uvm" enables the use of CUDA "Unified Virtual Memory" (UVM) in Kokkos. UVM allows to one to use the host CPU memory to supplement the memory used on the GPU (with some performance penalty) and thus enables running larger problems that would otherwise not fit into the RAM on the GPU. Please note, that the SPARTA KOKKOS package must always be compiled with the CMake option Kokkos_ENABLE_CUDA_LAMBDA=ON or the makefile setting KOKKOS_CUDA_OPTIONS=enable_lambda when using GPUs. The CMake configuration will thus always enable it.
The CMake option Kokkos_ENABLE_DEBUG=ON or the makefile setting KOKKOS_DEBUG=yes is useful when developing a Kokkos-enabled style within SPARTA. This option enables printing of run-time debugging information that can be useful and also enables runtime bounds checking on Kokkos data structures, but may slow down performance.
Currently, there are no precision options with the KOKKOS package. All compilation and computation is performed in double precision.