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			<p><a class="reference internal" href="Section_accelerate.html"><em>Return to Section accelerate overview</em></a></p>
			<div class="section" id="user-intel-package">
			<h1>5.USER-INTEL package<a class="headerlink" href="#user-intel-package" title="Permalink to this headline">¶</a></h1>
			<p>The USER-INTEL package was developed by Mike Brown at Intel
			Corporation. It provides two methods for accelerating simulations,
			depending on the hardware you have. The first is acceleration on
			Intel(R) CPUs by running in single, mixed, or double precision with
			vectorization. The second is acceleration on Intel(R) Xeon Phi(TM)
			coprocessors via offloading neighbor list and non-bonded force
			calculations to the Phi. The same C++ code is used in both cases.
			When offloading to a coprocessor from a CPU, the same routine is run
			twice, once on the CPU and once with an offload flag.</p>
			<p>Note that the USER-INTEL package supports use of the Phi in “offload”
			mode, not “native” mode like the <a class="reference internal" href="accelerate_kokkos.html"><em>KOKKOS package</em></a>.</p>
			<p>Also note that the USER-INTEL package can be used in tandem with the
			<a class="reference internal" href="accelerate_omp.html"><em>USER-OMP package</em></a>. This is useful when
			offloading pair style computations to the Phi, so that other styles
			not supported by the USER-INTEL package, e.g. bond, angle, dihedral,
			improper, and long-range electrostatics, can run simultaneously in
			threaded mode on the CPU cores. Since less MPI tasks than CPU cores
			will typically be invoked when running with coprocessors, this enables
			the extra CPU cores to be used for useful computation.</p>
			<p>As illustrated below, if LAMMPS is built with both the USER-INTEL and
			USER-OMP packages, this dual mode of operation is made easier to use,
			via the “-suffix hybrid intel omp” <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> or the <a class="reference internal" href="suffix.html"><em>suffix hybrid intel omp</em></a> command. Both set a second-choice suffix to “omp” so
			that styles from the USER-INTEL package will be used if available,
			with styles from the USER-OMP package as a second choice.</p>
			<p>Here is a quick overview of how to use the USER-INTEL package for CPU
			acceleration, assuming one or more 16-core nodes. More details
			follow.</p>
			<div class="highlight-python"><div class="highlight"><pre>use an Intel compiler
			use these CCFLAGS settings in Makefile.machine: -fopenmp, -DLAMMPS_MEMALIGN=64, -restrict, -xHost, -fno-alias, -ansi-alias, -override-limits
			use these LINKFLAGS settings in Makefile.machine: -fopenmp, -xHost
			make yes-user-intel yes-user-omp # including user-omp is optional
			make mpi # build with the USER-INTEL package, if settings (including compiler) added to Makefile.mpi
			make intel_cpu # or Makefile.intel_cpu already has settings, uses Intel MPI wrapper
			Make.py -v -p intel omp -intel cpu -a file mpich_icc # or one-line build via Make.py for MPICH
			Make.py -v -p intel omp -intel cpu -a file ompi_icc # or for OpenMPI
			Make.py -v -p intel omp -intel cpu -a file intel_cpu # or for Intel MPI wrapper
			</pre></div>
			</div>
			<div class="highlight-python"><div class="highlight"><pre>lmp_machine -sf intel -pk intel 0 omp 16 -in in.script # 1 node, 1 MPI task/node, 16 threads/task, no USER-OMP
			mpirun -np 32 lmp_machine -sf intel -in in.script # 2 nodess, 16 MPI tasks/node, no threads, no USER-OMP
			lmp_machine -sf hybrid intel omp -pk intel 0 omp 16 -pk omp 16 -in in.script # 1 node, 1 MPI task/node, 16 threads/task, with USER-OMP
			mpirun -np 32 -ppn 4 lmp_machine -sf hybrid intel omp -pk omp 4 -pk omp 4 -in in.script # 8 nodes, 4 MPI tasks/node, 4 threads/task, with USER-OMP
			</pre></div>
			</div>
			<p>Here is a quick overview of how to use the USER-INTEL package for the
			same CPUs as above (16 cores/node), with an additional Xeon Phi(TM)
			coprocessor per node. More details follow.</p>
			<div class="highlight-python"><div class="highlight"><pre>Same as above for building, with these additions/changes:
			add the flag -DLMP_INTEL_OFFLOAD to CCFLAGS in Makefile.machine
			add the flag -offload to LINKFLAGS in Makefile.machine
			for Make.py change "-intel cpu" to "-intel phi", and "file intel_cpu" to "file intel_phi"
			</pre></div>
			</div>
			<div class="highlight-python"><div class="highlight"><pre>mpirun -np 32 lmp_machine -sf intel -pk intel 1 -in in.script # 2 nodes, 16 MPI tasks/node, 240 total threads on coprocessor, no USER-OMP
			mpirun -np 16 -ppn 8 lmp_machine -sf intel -pk intel 1 omp 2 -in in.script # 2 nodes, 8 MPI tasks/node, 2 threads/task, 240 total threads on coprocessor, no USER-OMP
			mpirun -np 32 -ppn 8 lmp_machine -sf hybrid intel omp -pk intel 1 omp 2 -pk omp 2 -in in.script # 4 nodes, 8 MPI tasks/node, 2 threads/task, 240 total threads on coprocessor, with USER-OMP
			</pre></div>
			</div>
			<p><strong>Required hardware/software:</strong></p>
			<p>Your compiler must support the OpenMP interface. Use of an Intel(R)
			C++ compiler is recommended, but not required. However, g++ will not
			recognize some of the settings listed above, so they cannot be used.
			Optimizations for vectorization have only been tested with the
			Intel(R) compiler. Use of other compilers may not result in
			vectorization, or give poor performance.</p>
			<p>The recommended version of the Intel(R) compiler is 14.0.1.106.
			Versions 15.0.1.133 and later are also supported. If using Intel(R)
			MPI, versions 15.0.2.044 and later are recommended.</p>
			<p>To use the offload option, you must have one or more Intel(R) Xeon
			Phi(TM) coprocessors and use an Intel(R) C++ compiler.</p>
			<p><strong>Building LAMMPS with the USER-INTEL package:</strong></p>
			<p>The lines above illustrate how to include/build with the USER-INTEL
			package, for either CPU or Phi support, in two steps, using the “make”
			command. Or how to do it with one command via the src/Make.py script,
			described in <a class="reference internal" href="Section_start.html#start-4"><span>Section 2.4</span></a> of the manual.
			Type “Make.py -h” for help. Because the mechanism for specifing what
			compiler to use (Intel in this case) is different for different MPI
			wrappers, 3 versions of the Make.py command are shown.</p>
			<p>Note that if you build with support for a Phi coprocessor, the same
			binary can be used on nodes with or without coprocessors installed.
			However, if you do not have coprocessors on your system, building
			without offload support will produce a smaller binary.</p>
			<p>If you also build with the USER-OMP package, you can use styles from
			both packages, as described below.</p>
			<p>Note that the CCFLAGS and LINKFLAGS settings in Makefile.machine must
			include “-fopenmp”. Likewise, if you use an Intel compiler, the
			CCFLAGS setting must include “-restrict”. For Phi support, the
			“-DLMP_INTEL_OFFLOAD” (CCFLAGS) and “-offload” (LINKFLAGS) settings
			are required. The other settings listed above are optional, but will
			typically improve performance. The Make.py command will add all of
			these automatically.</p>
			<p>If you are compiling on the same architecture that will be used for
			the runs, adding the flag <em>-xHost</em> to CCFLAGS enables vectorization
			with the Intel(R) compiler. Otherwise, you must provide the correct
			compute node architecture to the -x option (e.g. -xAVX).</p>
			<p>Example machines makefiles Makefile.intel_cpu and Makefile.intel_phi
			are included in the src/MAKE/OPTIONS directory with settings that
			perform well with the Intel(R) compiler. The latter has support for
			offload to Phi coprocessors; the former does not.</p>
			<p><strong>Run with the USER-INTEL package from the command line:</strong></p>
			<p>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.</p>
			<p>If you compute (any portion of) pairwise interactions using USER-INTEL
			pair styles on the CPU, or use USER-OMP styles on the CPU, you need to
			choose how many OpenMP threads per MPI task to use. If both packages
			are used, it must be done for both packages, and the same thread count
			value should be used for both. Note that the product of MPI tasks *
			threads/task should not exceed the physical number of cores (on a
			node), otherwise performance will suffer.</p>
			<p>When using the USER-INTEL package for the Phi, you also need to
			specify the number of coprocessor/node and optionally the number of
			coprocessor threads per MPI task to use. Note that coprocessor
			threads (which run on the coprocessor) are totally independent from
			OpenMP threads (which run on the CPU). The default values for the
			settings that affect coprocessor threads are typically fine, as
			discussed below.</p>
			<p>As in the lines above, use the “-sf intel” or “-sf hybrid intel omp”
			<a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>, which will
			automatically append “intel” to styles that support it. In the second
			case, “omp” will be appended if an “intel” style does not exist.</p>
			<p>Note that if either switch is used, it also invokes a default command:
			<a class="reference internal" href="package.html"><em>package intel 1</em></a>. If the “-sf hybrid intel omp” switch
			is used, the default USER-OMP command <a class="reference internal" href="package.html"><em>package omp 0</em></a> is
			also invoked (if LAMMPS was built with USER-OMP). Both set the number
			of OpenMP threads per MPI task via the OMP_NUM_THREADS environment
			variable. The first command sets the number of Xeon Phi(TM)
			coprocessors/node to 1 (ignored if USER-INTEL is built for CPU-only),
			and the precision mode to “mixed” (default value).</p>
			<p>You can also use the “-pk intel Nphi” <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to explicitly set Nphi = # of Xeon
			Phi(TM) coprocessors/node, as well as additional options. Nphi should
			be >= 1 if LAMMPS was built with coprocessor support, otherswise Nphi
			= 0 for a CPU-only build. All the available coprocessor threads on
			each Phi will be divided among MPI tasks, unless the <em>tptask</em> option
			of the “-pk intel” <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> is
			used to limit the coprocessor threads per MPI task. See the <a class="reference internal" href="package.html"><em>package intel</em></a> command for details, including the default values
			used for all its options if not specified, and how to set the number
			of OpenMP threads via the OMP_NUM_THREADS environment variable if
			desired.</p>
			<p>If LAMMPS was built with the USER-OMP package, you can also use the
			“-pk omp Nt” <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to
			explicitly set Nt = # of OpenMP threads per MPI task to use, as well
			as additional options. Nt should be the same threads per MPI task as
			set for the USER-INTEL package, e.g. via the “-pk intel Nphi omp Nt”
			command. Again, see the <a class="reference internal" href="package.html"><em>package omp</em></a> command for
			details, including the default values used for all its options if not
			specified, and how to set the number of OpenMP threads via the
			OMP_NUM_THREADS environment variable if desired.</p>
			<p><strong>Or run with the USER-INTEL package by editing an input script:</strong></p>
			<p>The discussion above for the mpirun/mpiexec command, MPI tasks/node,
			OpenMP threads per MPI task, and coprocessor threads per MPI task is
			the same.</p>
			<p>Use the <a class="reference internal" href="suffix.html"><em>suffix intel</em></a> or <a class="reference internal" href="suffix.html"><em>suffix hybrid intel omp</em></a> commands, or you can explicitly add an “intel” or
			“omp” suffix to individual styles in your input script, e.g.</p>
			<div class="highlight-python"><div class="highlight"><pre>pair_style lj/cut/intel 2.5
			</pre></div>
			</div>
			<p>You must also use the <a class="reference internal" href="package.html"><em>package intel</em></a> command, unless the
			“-sf intel” or “-pk intel” <a class="reference internal" href="Section_start.html#start-7"><span>command-line switches</span></a> were used. It specifies how many
			coprocessors/node to use, as well as other OpenMP threading and
			coprocessor options. The <a class="reference internal" href="package.html"><em>package</em></a> doc page explains how
			to set the number of OpenMP threads via an environment variable if
			desired.</p>
			<p>If LAMMPS was also built with the USER-OMP package, you must also use
			the <a class="reference internal" href="package.html"><em>package omp</em></a> command to enable that package, unless
			the “-sf hybrid intel omp” or “-pk omp” <a class="reference internal" href="Section_start.html#start-7"><span>command-line switches</span></a> were used. It specifies how many
			OpenMP threads per MPI task to use (should be same as the setting for
			the USER-INTEL package), as well as other options. Its doc page
			explains how to set the number of OpenMP threads via an environment
			variable if desired.</p>
			<p><strong>Speed-ups to expect:</strong></p>
			<p>If LAMMPS was not built with coprocessor support (CPU only) when
			including the USER-INTEL package, then acclerated styles will run on
			the CPU using vectorization optimizations and the specified precision.
			This may give a substantial speed-up for a pair style, particularly if
			mixed or single precision is used.</p>
			<p>If LAMMPS was built with coproccesor support, the pair styles will run
			on one or more Intel(R) Xeon Phi(TM) coprocessors (per node). The
			performance of a Xeon Phi versus a multi-core CPU is a function of
			your hardware, which pair style is used, the number of
			atoms/coprocessor, and the precision used on the coprocessor (double,
			single, mixed).</p>
			<p>See the <a class="reference external" href="http://lammps.sandia.gov/bench.html">Benchmark page</a> of the
			LAMMPS web site for performance of the USER-INTEL package on different
			hardware.</p>
			<div class="admonition note">
			<p class="first admonition-title">Note</p>
			<p class="last">Setting core affinity is often used to pin MPI tasks and OpenMP
			threads to a core or group of cores so that memory access can be
			uniform. Unless disabled at build time, affinity for MPI tasks and
			OpenMP threads on the host (CPU) will be set by default on the host
			when using offload to a coprocessor. In this case, it is unnecessary
			to use other methods to control affinity (e.g. taskset, numactl,
			I_MPI_PIN_DOMAIN, etc.). This can be disabled in an input script with
			the <em>no_affinity</em> option to the <a class="reference internal" href="package.html"><em>package intel</em></a> command
			or by disabling the option at build time (by adding
			-DINTEL_OFFLOAD_NOAFFINITY to the CCFLAGS line of your Makefile).
			Disabling this option is not recommended, especially when running on a
			machine with hyperthreading disabled.</p>
			</div>
			<p><strong>Guidelines for best performance on an Intel(R) Xeon Phi(TM)
			coprocessor:</strong></p>
			<ul class="simple">
			<li>The default for the <a class="reference internal" href="package.html"><em>package intel</em></a> command is to have
			all the MPI tasks on a given compute node use a single Xeon Phi(TM)
			coprocessor. In general, running with a large number of MPI tasks on
			each node will perform best with offload. Each MPI task will
			automatically get affinity to a subset of the hardware threads
			available on the coprocessor. For example, if your card has 61 cores,
			with 60 cores available for offload and 4 hardware threads per core
			(240 total threads), running with 24 MPI tasks per node will cause
			each MPI task to use a subset of 10 threads on the coprocessor. Fine
			tuning of the number of threads to use per MPI task or the number of
			threads to use per core can be accomplished with keyword settings of
			the <a class="reference internal" href="package.html"><em>package intel</em></a> command.</li>
			<li>If desired, only a fraction of the pair style computation can be
			offloaded to the coprocessors. This is accomplished by using the
			<em>balance</em> keyword in the <a class="reference internal" href="package.html"><em>package intel</em></a> command. A
			balance of 0 runs all calculations on the CPU. A balance of 1 runs
			all calculations on the coprocessor. A balance of 0.5 runs half of
			the calculations on the coprocessor. Setting the balance to -1 (the
			default) will enable dynamic load balancing that continously adjusts
			the fraction of offloaded work throughout the simulation. This option
			typically produces results within 5 to 10 percent of the optimal fixed
			balance.</li>
			<li>When using offload with CPU hyperthreading disabled, it may help
			performance to use fewer MPI tasks and OpenMP threads than available
			cores. This is due to the fact that additional threads are generated
			internally to handle the asynchronous offload tasks.</li>
			<li>If running short benchmark runs with dynamic load balancing, adding a
			short warm-up run (10-20 steps) will allow the load-balancer to find a
			near-optimal setting that will carry over to additional runs.</li>
			<li>If pair computations are being offloaded to an Intel(R) Xeon Phi(TM)
			coprocessor, a diagnostic line is printed to the screen (not to the
			log file), during the setup phase of a run, indicating that offload
			mode is being used and indicating the number of coprocessor threads
			per MPI task. Additionally, an offload timing summary is printed at
			the end of each run. When offloading, the frequency for <a class="reference internal" href="atom_modify.html"><em>atom sorting</em></a> is changed to 1 so that the per-atom data is
			effectively sorted at every rebuild of the neighbor lists.</li>
			<li>For simulations with long-range electrostatics or bond, angle,
			dihedral, improper calculations, computation and data transfer to the
			coprocessor will run concurrently with computations and MPI
			communications for these calculations on the host CPU. The USER-INTEL
			package has two modes for deciding which atoms will be handled by the
			coprocessor. This choice is controlled with the <em>ghost</em> keyword of
			the <a class="reference internal" href="package.html"><em>package intel</em></a> command. When set to 0, ghost atoms
			(atoms at the borders between MPI tasks) are not offloaded to the
			card. This allows for overlap of MPI communication of forces with
			computation on the coprocessor when the <a class="reference internal" href="newton.html"><em>newton</em></a> setting
			is “on”. The default is dependent on the style being used, however,
			better performance may be achieved by setting this option
			explictly.</li>
			</ul>
			<div class="section" id="restrictions">
			<h2>Restrictions<a class="headerlink" href="#restrictions" title="Permalink to this headline">¶</a></h2>
			<p>When offloading to a coprocessor, <a class="reference internal" href="pair_hybrid.html"><em>hybrid</em></a> styles
			that require skip lists for neighbor builds cannot be offloaded.
			Using <a class="reference internal" href="pair_hybrid.html"><em>hybrid/overlay</em></a> is allowed. Only one intel
			accelerated style may be used with hybrid styles.
			<a class="reference internal" href="special_bonds.html"><em>Special_bonds</em></a> exclusion lists are not currently
			supported with offload, however, the same effect can often be
			accomplished by setting cutoffs for excluded atom types to 0. None of
			the pair styles in the USER-INTEL package currently support the
			“inner”, “middle”, “outer” options for rRESPA integration via the
			<a class="reference internal" href="run_style.html"><em>run_style respa</em></a> command; only the “pair” option is
			supported.</p>
			</div>
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