libhoomd/computes_gpu/TableDihedralForceComputeGPU.cc

   1 /*
   2 Highly Optimized Object-oriented Many-particle Dynamics -- Blue Edition
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  41 IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
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  49
  50 // Maintainer: joaander
  51
  52 #include <boost/python.hpp>
  53 using namespace boost::python;
  54 #include <boost/bind.hpp>
  55 using namespace boost;
  56
  57 #include "TableDihedralForceComputeGPU.h"
  58 #include <stdexcept>
  59
  60 /*! \file TableDihedralForceComputeGPU.cc
  61     \brief Defines the TableDihedralForceComputeGPU class
  62 */
  63
  64 using namespace std;
  65
  66 /*! \param sysdef System to compute forces on
  67     \param table_width Width the tables will be in memory
  68     \param log_suffix Name given to this instance of the table potential
  69 */
  70 TableDihedralForceComputeGPU::TableDihedralForceComputeGPU(boost::shared_ptr<SystemDefinition> sysdef,
  71                                      unsigned int table_width,
  72                                      const std::string& log_suffix)
  73     : TableDihedralForceCompute(sysdef, table_width, log_suffix)
  74     {
  75     // can't run on the GPU if there aren't any GPUs in the execution configuration
  76     if (!exec_conf->isCUDAEnabled())
  77         {
  78         m_exec_conf->msg->error() << "Creating a BondTableForceComputeGPU with no GPU in the execution configuration" << endl;
  79         throw std::runtime_error("Error initializing BondTableForceComputeGPU");
  80         }
  81
  82      // allocate flags storage on the GPU
  83     GPUArray<unsigned int> flags(1, this->exec_conf);
  84     m_flags.swap(flags);
  85
  86     m_tuner.reset(new Autotuner(32, 1024, 32, 5, 100000, "table_dihedral", this->m_exec_conf));
  87     }
  88
  89 /*! \post The table based forces are computed for the given timestep.
  90
  91 \param timestep specifies the current time step of the simulation
  92
  93 Calls gpu_compute_bondtable_forces to do the leg work
  94 */
  95 void TableDihedralForceComputeGPU::computeForces(unsigned int timestep)
  96     {
  97
  98     // start the profile
  99     if (m_prof) m_prof->push(exec_conf, "Dihedral Table");
 100
 101     // access the particle data
 102     ArrayHandle<Scalar4> d_pos(m_pdata->getPositions(), access_location::device, access_mode::read);
 103     BoxDim box = m_pdata->getBox();
 104
 105     // access the table data
 106     ArrayHandle<Scalar2> d_tables(m_tables, access_location::device, access_mode::read);
 107
 108     ArrayHandle<Scalar4> d_force(m_force,access_location::device,access_mode::overwrite);
 109     ArrayHandle<Scalar> d_virial(m_virial,access_location::device,access_mode::overwrite);
 110
 111         {
 112         // Access the dihedral data for reading
 113         ArrayHandle<group_storage<4> > d_gpu_dihedrallist(m_dihedral_data->getGPUTable(), access_location::device,access_mode::read);
 114         ArrayHandle<unsigned int> d_gpu_n_dihedrals(m_dihedral_data->getNGroupsArray(), access_location::device, access_mode::read);
 115         ArrayHandle<unsigned int> d_dihedrals_ABCD(m_dihedral_data->getGPUPosTable(), access_location::device, access_mode::read);
 116
 117
 118         // run the kernel on all GPUs in parallel
 119         m_tuner->begin();
 120         gpu_compute_table_dihedral_forces(d_force.data,
 121                              d_virial.data,
 122                              m_virial.getPitch(),
 123                              m_pdata->getN(),
 124                              d_pos.data,
 125                              box,
 126                              d_gpu_dihedrallist.data,
 127                              d_dihedrals_ABCD.data,
 128                              m_dihedral_data->getGPUTableIndexer().getW(),
 129                              d_gpu_n_dihedrals.data,
 130                              d_tables.data,
 131                              m_table_width,
 132                              m_table_value,
 133                              m_tuner->getParam(),
 134                              m_exec_conf->getComputeCapability());
 135         }
 136
 137
 138     if (exec_conf->isCUDAErrorCheckingEnabled())
 139         {
 140         CHECK_CUDA_ERROR();
 141         }
 142
 143     m_tuner->end();
 144
 145     if (m_prof) m_prof->pop(exec_conf);
 146     }
 147
 148 void export_TableDihedralForceComputeGPU()
 149     {
 150     class_<TableDihedralForceComputeGPU, boost::shared_ptr<TableDihedralForceComputeGPU>, bases<TableDihedralForceCompute>, boost::noncopyable >
 151     ("TableDihedralForceComputeGPU",
 152      init< boost::shared_ptr<SystemDefinition>,
 153      unsigned int,
 154      const std::string& >())
 155     ;
 156     }