Diffusion lammps (efficient_neuronet) Browse

accelerate_kokkos.txt
71f3c4556f54efficient_neuronet

accelerate_kokkos.txt
View Options

			"Previous Section"_Section_packages.html - "LAMMPS WWW Site"_lws -
			"LAMMPS Documentation"_ld - "LAMMPS Commands"_lc :c

			:link(lws,http://lammps.sandia.gov)
			:link(ld,Manual.html)
			:link(lc,Section_commands.html#comm)

			:line

			"Return to Section accelerate overview"_Section_accelerate.html

			5.3.3 KOKKOS package :h4

			The KOKKOS package was developed primarily by Christian Trott (Sandia)
			with contributions of various styles by others, including Sikandar
			Mashayak (UIUC), Stan Moore (Sandia), and Ray Shan (Sandia). The
			underlying Kokkos library was written primarily by Carter Edwards,
			Christian Trott, and Dan Sunderland (all Sandia).

			The KOKKOS package contains versions of pair, fix, and atom styles
			that use data structures and macros provided by the Kokkos library,
			which is included with LAMMPS in lib/kokkos.

			The Kokkos library is part of
			"Trilinos"_http://trilinos.sandia.gov/packages/kokkos and can also be
			downloaded from "Github"_https://github.com/kokkos/kokkos. Kokkos is a
			templated C++ library that provides two key abstractions for an
			application like LAMMPS. First, it allows a single implementation of
			an application kernel (e.g. a pair style) to run efficiently on
			different kinds of hardware, such as a GPU, Intel Phi, or many-core
			CPU.

			The Kokkos library also provides data abstractions to adjust (at
			compile time) the memory layout of basic data structures like 2d and
			3d arrays and allow the transparent utilization of special hardware
			load and store operations. Such data structures are used in LAMMPS to
			store atom coordinates or forces or neighbor lists. The layout is
			chosen to optimize performance on different platforms. Again this
			functionality is hidden from the developer, and does not affect how
			the kernel is coded.

			These abstractions are set at build time, when LAMMPS is compiled with
			the KOKKOS package installed. 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 LAMMPS (one or
			multiple per compute node) is set in the usual manner via the mpirun
			or mpiexec commands, and is independent of Kokkos.

			Kokkos currently provides support for 3 modes of execution (per MPI
			task). These are OpenMP (for many-core CPUs), Cuda (for NVIDIA GPUs),
			and OpenMP (for Intel Phi). Note that the KOKKOS package supports
			running on the Phi in native mode, not offload mode like the
			USER-INTEL package supports. You choose the mode at build time to
			produce an executable compatible with specific hardware.

			Here is a quick overview of how to use the KOKKOS package
			for CPU acceleration, assuming one or more 16-core nodes.
			More details follow.

			use a C++11 compatible compiler
			make yes-kokkos
			make mpi KOKKOS_DEVICES=OpenMP # build with the KOKKOS package
			make kokkos_omp # or Makefile.kokkos_omp already has variable set
			Make.py -v -p kokkos -kokkos omp -o mpi -a file mpi # or one-line build via Make.py :pre

			mpirun -np 16 lmp_mpi -k on -sf kk -in in.lj # 1 node, 16 MPI tasks/node, no threads
			mpirun -np 2 -ppn 1 lmp_mpi -k on t 16 -sf kk -in in.lj # 2 nodes, 1 MPI task/node, 16 threads/task
			mpirun -np 2 lmp_mpi -k on t 8 -sf kk -in in.lj # 1 node, 2 MPI tasks/node, 8 threads/task
			mpirun -np 32 -ppn 4 lmp_mpi -k on t 4 -sf kk -in in.lj # 8 nodes, 4 MPI tasks/node, 4 threads/task :pre

			specify variables and settings in your Makefile.machine that enable OpenMP, GPU, or Phi support
			include the KOKKOS package and build LAMMPS
			enable the KOKKOS package and its hardware options via the "-k on" command-line switch use KOKKOS styles in your input script :ul

			Here is a quick overview of how to use the KOKKOS package for GPUs,
			assuming one or more nodes, each with 16 cores and a GPU. More
			details follow.

			discuss use of NVCC, which Makefiles to examine

			use a C++11 compatible compiler
			KOKKOS_DEVICES = Cuda, OpenMP
			KOKKOS_ARCH = Kepler35
			make yes-kokkos
			make machine
			Make.py -p kokkos -kokkos cuda arch=31 -o kokkos_cuda -a file kokkos_cuda :pre

			mpirun -np 1 lmp_cuda -k on t 6 -sf kk -in in.lj # one MPI task, 6 threads on CPU
			mpirun -np 4 -ppn 1 lmp_cuda -k on t 6 -sf kk -in in.lj # ditto on 4 nodes :pre

			mpirun -np 2 lmp_cuda -k on t 8 g 2 -sf kk -in in.lj # two MPI tasks, 8 threads per CPU
			mpirun -np 32 -ppn 2 lmp_cuda -k on t 8 g 2 -sf kk -in in.lj # ditto on 16 nodes :pre

			Here is a quick overview of how to use the KOKKOS package
			for the Intel Phi:

			use a C++11 compatible compiler
			KOKKOS_DEVICES = OpenMP
			KOKKOS_ARCH = KNC
			make yes-kokkos
			make machine
			Make.py -p kokkos -kokkos phi -o kokkos_phi -a file mpi :pre

			host=MIC, Intel Phi with 61 cores (240 threads/phi via 4x hardware threading):
			mpirun -np 1 lmp_g++ -k on t 240 -sf kk -in in.lj # 1 MPI task on 1 Phi, 1*240 = 240
			mpirun -np 30 lmp_g++ -k on t 8 -sf kk -in in.lj # 30 MPI tasks on 1 Phi, 30*8 = 240
			mpirun -np 12 lmp_g++ -k on t 20 -sf kk -in in.lj # 12 MPI tasks on 1 Phi, 12*20 = 240
			mpirun -np 96 -ppn 12 lmp_g++ -k on t 20 -sf kk -in in.lj # ditto on 8 Phis :pre

			[Required hardware/software:]

			Kokkos support within LAMMPS must be built with a C++11 compatible
			compiler. If using gcc, version 4.8.1 or later is required.

			To build with Kokkos support for CPUs, 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.

			To build with Kokkos support for NVIDIA GPUs, NVIDIA Cuda software
			version 6.5 or later must be installed on your system. See the
			discussion for the "GPU"_accelerate_gpu.html package for details of
			how to check and do this.

			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).

			To build with Kokkos support for Intel Xeon Phi coprocessors, your
			sysmte must be configured to use them in "native" mode, not "offload"
			mode like the USER-INTEL package supports.

			[Building LAMMPS with the KOKKOS package:]

			You must choose at build time whether to build for CPUs (OpenMP),
			GPUs, or Phi.

			You can do any of these in one line, using the src/Make.py script,
			described in "Section 2.4"_Section_start.html#start_4 of the manual.
			Type "Make.py -h" for help. If run from the src directory, these
			commands will create src/lmp_kokkos_omp, lmp_kokkos_cuda, and
			lmp_kokkos_phi. Note that the OMP and PHI options use
			src/MAKE/Makefile.mpi as the starting Makefile.machine. The CUDA
			option uses src/MAKE/OPTIONS/Makefile.kokkos_cuda.

			The latter two steps can be done using the "-k on", "-pk kokkos" and
			"-sf kk" "command-line switches"_Section_start.html#start_7
			respectively. Or the effect of the "-pk" or "-sf" switches can be
			duplicated by adding the "package kokkos"_package.html or "suffix
			kk"_suffix.html commands respectively to your input script.


			Or you can follow these steps:

			CPU-only (run all-MPI or with OpenMP threading):

			cd lammps/src
			make yes-kokkos
			make g++ KOKKOS_DEVICES=OpenMP :pre

			Intel Xeon Phi:

			cd lammps/src
			make yes-kokkos
			make g++ KOKKOS_DEVICES=OpenMP KOKKOS_ARCH=KNC :pre

			CPUs and GPUs:

			cd lammps/src
			make yes-kokkos
			make cuda KOKKOS_DEVICES=Cuda :pre

			These examples set the KOKKOS-specific OMP, MIC, CUDA variables on the
			make command line which requires a GNU-compatible make command. Try
			"gmake" if your system's standard make complains.

			NOTE: If you build using make line variables and re-build LAMMPS twice
			with different KOKKOS options and the same target, e.g. g++ in the
			first two examples above, then you must perform a "make clean-all"
			or "make clean-machine" before each build. This is to force all the
			KOKKOS-dependent files to be re-compiled with the new options.

			You can also hardwire these make variables in the specified machine
			makefile, e.g. src/MAKE/Makefile.g++ in the first two examples above,
			with a line like:

			KOKKOS_ARCH = KNC :pre

			Note that if you build LAMMPS multiple times in this manner, using
			different KOKKOS options (defined in different machine makefiles), you
			do not have to worry about doing a "clean" in between. This is
			because the targets will be different.

			NOTE: The 3rd example above for a GPU, uses a different machine
			makefile, in this case src/MAKE/Makefile.cuda, which is included in
			the LAMMPS distribution. To build the KOKKOS package for a GPU, this
			makefile must use the NVIDA "nvcc" compiler. And it must have a
			KOKKOS_ARCH setting that is appropriate for your NVIDIA hardware and
			installed software. Typical values for KOKKOS_ARCH are given below,
			as well as other settings that must be included in the machine
			makefile, if you create your own.

			NOTE: Currently, there are no precision options with the KOKKOS
			package. All compilation and computation is performed in double
			precision.

			There are other allowed options when building with the KOKKOS package.
			As above, they can be set either as variables on the make command line
			or in Makefile.machine. This is the full list of options, including
			those discussed above, Each takes a value shown below. The
			default value is listed, which is set in the
			lib/kokkos/Makefile.kokkos file.

			#Default settings specific options
			#Options: force_uvm,use_ldg,rdc

			KOKKOS_DEVICES, values = {OpenMP}, {Serial}, {Pthreads}, {Cuda}, default = {OpenMP}
			KOKKOS_ARCH, values = {KNC}, {SNB}, {HSW}, {Kepler}, {Kepler30}, {Kepler32}, {Kepler35}, {Kepler37}, {Maxwell}, {Maxwell50}, {Maxwell52}, {Maxwell53}, {ARMv8}, {BGQ}, {Power7}, {Power8}, default = {none}
			KOKKOS_DEBUG, values = {yes}, {no}, default = {no}
			KOKKOS_USE_TPLS, values = {hwloc}, {librt}, default = {none}
			KOKKOS_CUDA_OPTIONS, values = {force_uvm}, {use_ldg}, {rdc} :ul

			KOKKOS_DEVICE sets the parallelization method used for Kokkos code
			(within LAMMPS). KOKKOS_DEVICES=OpenMP means that OpenMP will be
			used. KOKKOS_DEVICES=Pthreads means that pthreads will be used.
			KOKKOS_DEVICES=Cuda means an NVIDIA GPU running CUDA will be used.

			If KOKKOS_DEVICES=Cuda, then the lo-level Makefile in the src/MAKE
			directory must use "nvcc" as its compiler, via its CC setting. For
			best performance its CCFLAGS setting should use -O3 and have a
			KOKKOS_ARCH setting that matches the compute capability of your NVIDIA
			hardware and software installation, e.g. KOKKOS_ARCH=Kepler30. Note
			the minimal required compute capability is 2.0, but this will give
			signicantly reduced performance compared to Kepler generation GPUs
			with compute capability 3.x. For the LINK setting, "nvcc" should not
			be used; instead use g++ or another compiler suitable for linking C++
			applications. Often you will want to use your MPI compiler wrapper
			for this setting (i.e. mpicxx). Finally, the lo-level Makefile must
			also have a "Compilation rule" for creating .o files from .cu files.
			See src/Makefile.cuda for an example of a lo-level Makefile with all
			of these settings.

			KOKKOS_USE_TPLS=hwloc binds threads to hardware cores, so they do not
			migrate during a simulation. KOKKOS_USE_TPLS=hwloc should always be
			used if running with KOKKOS_DEVICES=Pthreads for pthreads. It is not
			necessary for KOKKOS_DEVICES=OpenMP for OpenMP, because OpenMP
			provides alternative methods via environment variables for binding
			threads to hardware cores. More info on binding threads to cores is
			given in "this section"_Section_accelerate.html#acc_8.

			KOKKOS_ARCH=KNC enables compiler switches needed when compling for an
			Intel Phi processor.

			KOKKOS_USE_TPLS=librt enables use of a more accurate timer mechanism
			on most Unix platforms. This library is not available on all
			platforms.

			KOKKOS_DEBUG is only useful when developing a Kokkos-enabled style
			within LAMMPS. KOKKOS_DEBUG=yes enables printing of run-time
			debugging information that can be useful. It also enables runtime
			bounds checking on Kokkos data structures.

			KOKKOS_CUDA_OPTIONS are additional options for CUDA.

			For more information on Kokkos see the Kokkos programmers' guide here:
			/lib/kokkos/doc/Kokkos_PG.pdf.

			[Run with the KOKKOS package from the command line:]

			The mpirun or mpiexec command sets the total number of MPI tasks used
			by LAMMPS (one or multiple per compute node) and the number of MPI
			tasks used per node. E.g. the mpirun command in MPICH does this via
			its -np and -ppn switches. Ditto for OpenMPI via -np and -npernode.

			When using KOKKOS built with host=OMP, you need to choose how many
			OpenMP threads per MPI task will be used (via the "-k" command-line
			switch discussed below). 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.

			When using the KOKKOS package built with device=CUDA, you must use
			exactly one MPI task per physical GPU.

			When using the KOKKOS package built with host=MIC for Intel Xeon Phi
			coprocessor support you need to insure there are one or more MPI tasks
			per coprocessor, and choose the number of coprocessor threads to use
			per MPI task (via the "-k" command-line switch discussed below). The
			product of MPI tasks * coprocessor threads/task should not exceed the
			maximum number of threads the coproprocessor is designed to run,
			otherwise performance will suffer. This value is 240 for current
			generation Xeon Phi(TM) chips, which is 60 physical cores * 4
			threads/core. Note that with the KOKKOS package you do not need to
			specify how many Phi coprocessors there are per node; each
			coprocessors is simply treated as running some number of MPI tasks.

			You must use the "-k on" "command-line
			switch"_Section_start.html#start_7 to enable the KOKKOS package. It
			takes additional arguments for hardware settings appropriate to your
			system. Those arguments are "documented
			here"_Section_start.html#start_7. The two most commonly used
			options are:

			-k on t Nt g Ng :pre

			The "t Nt" option applies to host=OMP (even if device=CUDA) and
			host=MIC. For host=OMP, it specifies how many OpenMP threads per MPI
			task to use with a node. For host=MIC, it specifies how many Xeon Phi
			threads per MPI task to use within a node. The default is Nt = 1.
			Note that for host=OMP this is effectively MPI-only mode which may be
			fine. But for host=MIC you will typically end up using far less than
			all the 240 available threads, which could give very poor performance.

			The "g Ng" option applies to device=CUDA. It specifies how many GPUs
			per compute node to use. The default is 1, so this only needs to be
			specified is you have 2 or more GPUs per compute node.

			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"_package.html command doc page.

			Use the "-sf kk" "command-line switch"_Section_start.html#start_7,
			which will automatically append "kk" to styles that support it. Use
			the "-pk kokkos" "command-line switch"_Section_start.html#start_7 if
			you wish to change any of the default "package kokkos"_package.html
			optionns set by the "-k on" "command-line
			switch"_Section_start.html#start_7.



			Note that the default for the "package kokkos"_package.html command is
			to use "full" neighbor lists and set the Newton flag to "off" for both
			pairwise and bonded interactions. This typically gives fastest
			performance. If the "newton"_newton.html command is used in the input
			script, it can override the Newton flag defaults.

			However, when running in MPI-only mode with 1 thread per MPI task, it
			will typically be faster to use "half" neighbor lists and set the
			Newton flag to "on", just as is the case for non-accelerated pair
			styles. You can do this with the "-pk" "command-line
			switch"_Section_start.html#start_7.

			[Or run with the KOKKOS package by editing an input script:]

			The discussion above for the mpirun/mpiexec command and setting
			appropriate thread and GPU values for host=OMP or host=MIC or
			device=CUDA are the same.

			You must still use the "-k on" "command-line
			switch"_Section_start.html#start_7 to enable the KOKKOS package, and
			specify its additional arguments for hardware options appopriate to
			your system, as documented above.

			Use the "suffix kk"_suffix.html command, or you can explicitly add a
			"kk" suffix to individual styles in your input script, e.g.

			pair_style lj/cut/kk 2.5 :pre

			You only need to use the "package kokkos"_package.html command if you
			wish to change any of its option defaults, as set by the "-k on"
			"command-line switch"_Section_start.html#start_7.

			[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, the following rules of thumb apply:

			When running on CPUs only, with a single thread per MPI task,
			performance of a KOKKOS style is somewhere between the standard
			(un-accelerated) styles (MPI-only mode), and those provided by the
			USER-OMP package. However the difference between all 3 is small (less
			than 20%). :ulb,l

			When running on CPUs only, with multiple threads per MPI task,
			performance of a KOKKOS style is a bit slower than the USER-OMP
			package. :l

			When running large number of atoms per GPU, KOKKOS is typically faster
			than the GPU package. :l

			When running on Intel Xeon Phi, KOKKOS is not as fast as
			the USER-INTEL package, which is optimized for that hardware. :l,ule

			See the "Benchmark page"_http://lammps.sandia.gov/bench.html of the
			LAMMPS web site for performance of the KOKKOS package on different
			hardware.

			[Guidelines for best performance:]

			Here are guidline for using the KOKKOS package on the different
			hardware configurations listed above.

			Many of the guidelines use the "package kokkos"_package.html command
			See its doc page for details and default settings. Experimenting with
			its options can provide a speed-up for specific calculations.

			[Running on a multi-core CPU:]

			If N is the number of physical cores/node, then the number of MPI
			tasks/node * number of threads/task should not exceed N, and should
			typically equal N. Note that the default threads/task is 1, as set by
			the "t" keyword of the "-k" "command-line
			switch"_Section_start.html#start_7. If you do not change this, no
			additional parallelism (beyond MPI) will be invoked on the host
			CPU(s).

			You can compare the performance running in different modes:

			run with 1 MPI task/node and N threads/task
			run with N MPI tasks/node and 1 thread/task
			run with settings in between these extremes :ul

			Examples of mpirun commands in these modes are shown above.

			When using KOKKOS to perform 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 ./lmp_openmpi ...
			Mvapich2 2.0: mpiexec -np 2 -bind-to socket -map-by socket ./lmp_mvapich ... :pre

			For binding threads with the KOKKOS OMP option, 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. For binding threads with the
			KOKKOS pthreads option, compile LAMMPS the KOKKOS HWLOC=yes option, as
			discussed in "Section 2.3.4"_Sections_start.html#start_3_4 of the
			manual.

			[Running on GPUs:]

			Insure the -arch setting in the machine makefile you are using,
			e.g. src/MAKE/Makefile.cuda, is correct for your GPU hardware/software
			(see "this section"_Section_start.html#start_3_4 of the manual for
			details).

			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.

			Use the "-k" "command-line switch"_Section_commands.html#start_7 to
			specify the number of GPUs per node, and the number of threads per MPI
			task. 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 * number of
			threads/task should not exceed N. With one GPU (and one MPI task) it
			may be faster to use less than all the available cores, by setting
			threads/task to a smaller value. This is because using all the cores
			on a dual-socket node will incur extra cost to copy memory from the
			2nd socket to the GPU.

			Examples of mpirun commands that follow these rules are shown above.

			NOTE: When using a GPU, you will achieve the best performance if your
			input script does not use any 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
			"thermo"_thermo_style.html or "dump"_dump.html output will cause data
			to be copied back to the CPU.

			You cannot yet assign multiple MPI tasks to the same GPU with the
			KOKKOS package. We plan to support this in the future, similar to the
			GPU package in LAMMPS.

			You cannot yet use both the host (multi-threaded) and device (GPU)
			together to compute pairwise interactions with the KOKKOS package. We
			hope to support this in the future, similar to the GPU package in
			LAMMPS.

			[Running on an Intel Phi:]

			Kokkos only uses Intel Phi processors in their "native" mode, i.e.
			not hosted by a CPU.

			As illustrated above, build LAMMPS with OMP=yes (the default) and
			MIC=yes. The latter insures code is correctly compiled for the Intel
			Phi. The OMP setting means OpenMP will be used for parallelization on
			the Phi, which is currently the best option within Kokkos. In the
			future, other options may be added.

			Current-generation Intel Phi chips have either 61 or 57 cores. One
			core should be excluded for running the OS, leaving 60 or 56 cores.
			Each core is hyperthreaded, so there are effectively N = 240 (4*60) or
			N = 224 (4*56) cores to run on.

			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 2 values should be N, i.e.
			240 or 224. Also, the number of threads/task should be a multiple of
			4 so that logical threads from more than one MPI task do not run on
			the same physical core.

			Examples of mpirun commands that follow these rules are shown above.

			[Restrictions:]

			As noted above, if using GPUs, the number of MPI tasks per compute
			node should equal to the number of GPUs per compute node. In the
			future Kokkos will support assigning multiple MPI tasks to a single
			GPU.

			Currently Kokkos does not support AMD GPUs due to limits in the
			available backend programming models. Specifically, Kokkos requires
			extensive C++ support from the Kernel language. This is expected to
			change in the future.

lammps/doc/src/accelerate_kokkos.txt71f3c4556f54efficient_neuronet

accelerate_kokkos.txtView Options

lammps/doc/src/accelerate_kokkos.txt
71f3c4556f54efficient_neuronet

accelerate_kokkos.txt
View Options