forked from lijiext/lammps
85 lines
3.8 KiB
Plaintext
85 lines
3.8 KiB
Plaintext
/***************************************************************************
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README
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-------------------
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W. Michael Brown
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README for building LAMMPS GPU Library
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__________________________________________________________________________
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This file is part of the LAMMPS GPU Library
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__________________________________________________________________________
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begin : Thu Jun 25 2009
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copyright : (C) 2009 by W. Michael Brown
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email : wmbrown@sandia.gov
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***************************************************************************/
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/* -----------------------------------------------------------------------
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Copyright (2009) Sandia Corporation. Under the terms of Contract
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DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
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certain rights in this software. This software is distributed under
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the GNU General Public License.
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----------------------------------------------------------------------- */
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GENERAL NOTES
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This library, pair_gpu_lib.a, provides routines for GPGPU acceleration
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of LAMMPS pair styles. Currently, only CUDA enabled GPUs are
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supported. Compilation of this library requires installing the CUDA
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GPU driver and CUDA toolkit for your operating system. In addition to
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the LAMMPS library, the binary nvc_get_devices will also be
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built. This can be used to query the names and properties of GPU
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devices on your system.
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NOTE: Installation of the CUDA SDK is not required.
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Current pair styles supporting GPU Accelartion:
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1. lj/cut/gpu
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2. gayberne/gpu
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MULTIPLE LAMMPS PROCESSES
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When using GPGPU acceleration, you are restricted to one physical GPU
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per LAMMPS process. This can be multiple GPUs on a single node or
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across multiple nodes. Intructions on GPU assignment can be found in
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the LAMMPS documentation.
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SPEEDUPS
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The speedups that can be obtained using this library are highly
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dependent on the GPU architecture and the computational expense of the
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pair potential. When comparing a single precision Tesla C1060 run to a
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serial Intel Xeon 5140 2.33 GHz serial run, the speedup is ~4.42x for
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lj/cut with a cutoff of 2.5. For gayberne with a cutoff of 7, the
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speedup is >103x for 8000 particles. The speedup will improve with an
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increase in the number of particles or an increase in the cutoff.
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BUILDING AND PRECISION MODES
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To build, edit the CUDA_CPP, CUDA_ARCH, CUDA_PREC, and CUDA_LINK files for
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your machine. Type make. Additionally, the GPU package must be installed and
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compiled for LAMMPS. The library supports 3 precision modes as determined by
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the CUDA_PREC variable:
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CUDA_PREC = -D_SINGLE_SINGLE # Single precision for all calculations
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CUDA_PREC = -D_DOUBLE_DOUBLE # Double precision for all calculations
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CUDA_PREC = -D_SINGLE_DOUBLE # Accumulation of forces, etc. in double
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NOTE: Double precision is only supported on certain GPUS (with
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compute capability>=1.3).
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NOTE: The gayberne/gpu pair style will only be installed if the ASPHERE
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package has been installed before installing the GPU package in LAMMPS.
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GPU MEMORY
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Upon initialization of the pair style, the library will reserve memory
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for 64K atoms per GPU or 70% of each cards GPU memory, whichever value
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is limiting. The value of 70% can be changed by editing the
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PERCENT_GPU_MEMORY definition in the source file. The value of 64K
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cannot be increased and is the maximum number of atoms allowed per
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GPU. Using the 'neigh_modify one' modifier in your LAMMPS input script
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can help to increase maximum number of atoms per GPU for cards with
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limited memory.
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