Updating kokkos lib
git-svn-id: svn://svn.icms.temple.edu/lammps-ro/trunk@14918 f3b2605a-c512-4ea7-a41b-209d697bcdaa
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/*
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//@HEADER
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// ************************************************************************
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//
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// Kokkos v. 2.0
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// Copyright (2014) Sandia Corporation
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//
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// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
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// the U.S. Government retains certain rights in this software.
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are
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// met:
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//
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// 1. Redistributions of source code must retain the above copyright
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// notice, this list of conditions and the following disclaimer.
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//
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// 2. Redistributions in binary form must reproduce the above copyright
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// notice, this list of conditions and the following disclaimer in the
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// documentation and/or other materials provided with the distribution.
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//
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// 3. Neither the name of the Corporation nor the names of the
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// contributors may be used to endorse or promote products derived from
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// this software without specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
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// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
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// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
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// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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//
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// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
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//
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// ************************************************************************
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//@HEADER
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*/
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#ifndef KOKKOS_HEXELEMENT_HPP
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#define KOKKOS_HEXELEMENT_HPP
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namespace Kokkos {
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namespace Example {
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template< unsigned NodeCount >
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class HexElement_TensorData ;
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template< unsigned NodeCount , class Device >
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class HexElement_TensorEval ;
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//----------------------------------------------------------------------------
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/** \brief Evaluate Hex element on interval [-1,1]^3 */
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template<>
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class HexElement_TensorData< 8 > {
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public:
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static const unsigned element_node_count = 8 ;
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static const unsigned spatial_dimension = 3 ;
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static const unsigned integration_count_1d = 2 ;
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static const unsigned function_count_1d = 2 ;
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float values_1d [ function_count_1d ][ integration_count_1d ];
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float derivs_1d [ function_count_1d ][ integration_count_1d ];
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float weights_1d[ integration_count_1d ];
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unsigned char eval_map[ element_node_count ][4] ;
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static float eval_value_1d( const unsigned jf , const float x )
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{
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return 0 == jf ? 0.5 * ( 1.0 - x ) : (
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1 == jf ? 0.5 * ( 1.0 + x ) : 0 );
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}
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static float eval_deriv_1d( const unsigned jf , const float )
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{
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return 0 == jf ? -0.5 : (
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1 == jf ? 0.5 : 0 );
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}
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HexElement_TensorData()
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{
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const unsigned char tmp_map[ element_node_count ][ spatial_dimension ] =
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{ { 0 , 0 , 0 },
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{ 1 , 0 , 0 },
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{ 1 , 1 , 0 },
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{ 0 , 1 , 0 },
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{ 0 , 0 , 1 },
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{ 1 , 0 , 1 },
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{ 1 , 1 , 1 },
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{ 0 , 1 , 1 } };
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weights_1d[0] = 1 ;
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weights_1d[1] = 1 ;
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const float points_1d[ integration_count_1d ] =
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{ -0.577350269 , 0.577350269 };
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for ( unsigned i = 0 ; i < element_node_count ; ++i ) {
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eval_map[i][0] = tmp_map[i][0];
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eval_map[i][1] = tmp_map[i][1];
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eval_map[i][2] = tmp_map[i][2];
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}
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for ( unsigned xp = 0 ; xp < integration_count_1d ; ++xp ) {
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for ( unsigned xf = 0 ; xf < function_count_1d ; ++xf ) {
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values_1d[xp][xf] = eval_value_1d( xf , points_1d[xp] );
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derivs_1d[xp][xf] = eval_deriv_1d( xf , points_1d[xp] );
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}}
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}
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};
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//----------------------------------------------------------------------------
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template<>
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class HexElement_TensorData< 27 > {
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public:
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static const unsigned element_node_count = 27 ;
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static const unsigned spatial_dimension = 3 ;
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static const unsigned integration_count_1d = 3 ;
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static const unsigned function_count_1d = 3 ;
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float values_1d [ function_count_1d ][ integration_count_1d ];
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float derivs_1d [ function_count_1d ][ integration_count_1d ];
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float weights_1d[ integration_count_1d ];
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unsigned char eval_map[ element_node_count ][4] ;
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// sizeof(EvaluateElementHex) = 111 bytes =
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// sizeof(float) * 9 +
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// sizeof(float) * 9 +
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// sizeof(float) * 3 +
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// sizeof(char) * 27
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static float eval_value_1d( const unsigned jf , const float p )
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{
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return 0 == jf ? 0.5 * p * ( p - 1 ) : (
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1 == jf ? 1.0 - p * p : (
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2 == jf ? 0.5 * p * ( p + 1 ) : 0 ));
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}
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static float eval_deriv_1d( const unsigned jf , const float p )
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{
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return 0 == jf ? p - 0.5 : (
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1 == jf ? -2.0 * p : (
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2 == jf ? p + 0.5 : 0 ));
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}
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HexElement_TensorData()
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{
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const unsigned char tmp_map[ element_node_count ][ spatial_dimension ] =
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{ { 0 , 0 , 0 },
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{ 2 , 0 , 0 },
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{ 2 , 2 , 0 },
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{ 0 , 2 , 0 },
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{ 0 , 0 , 2 },
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{ 2 , 0 , 2 },
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{ 2 , 2 , 2 },
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{ 0 , 2 , 2 },
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{ 1 , 0 , 0 },
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{ 2 , 1 , 0 },
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{ 1 , 2 , 0 },
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{ 0 , 1 , 0 },
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{ 0 , 0 , 1 },
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{ 2 , 0 , 1 },
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{ 2 , 2 , 1 },
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{ 0 , 2 , 1 },
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{ 1 , 0 , 2 },
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{ 2 , 1 , 2 },
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{ 1 , 2 , 2 },
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{ 0 , 1 , 2 },
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{ 1 , 1 , 1 },
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{ 1 , 1 , 0 },
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{ 1 , 1 , 2 },
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{ 0 , 1 , 1 },
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{ 2 , 1 , 1 },
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{ 1 , 0 , 1 },
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{ 1 , 2 , 1 } };
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// Interval [-1,1]
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weights_1d[0] = 0.555555556 ;
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weights_1d[1] = 0.888888889 ;
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weights_1d[2] = 0.555555556 ;
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const float points_1d[3] = { -0.774596669 ,
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0.000000000 ,
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0.774596669 };
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for ( unsigned i = 0 ; i < element_node_count ; ++i ) {
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eval_map[i][0] = tmp_map[i][0];
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eval_map[i][1] = tmp_map[i][1];
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eval_map[i][2] = tmp_map[i][2];
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}
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for ( unsigned xp = 0 ; xp < integration_count_1d ; ++xp ) {
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for ( unsigned xf = 0 ; xf < function_count_1d ; ++xf ) {
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values_1d[xp][xf] = eval_value_1d( xf , points_1d[xp] );
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derivs_1d[xp][xf] = eval_deriv_1d( xf , points_1d[xp] );
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}}
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}
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};
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//----------------------------------------------------------------------------
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template< unsigned NodeCount >
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class HexElement_Data {
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public:
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static const unsigned spatial_dimension = 3 ;
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static const unsigned element_node_count = NodeCount ;
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static const unsigned integration_count = NodeCount ;
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static const unsigned function_count = NodeCount ;
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float weights[ integration_count ] ;
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float values[ integration_count ][ function_count ];
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float gradients[ integration_count ][ spatial_dimension ][ function_count ];
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HexElement_Data()
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{
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HexElement_TensorData< NodeCount > tensor_data ;
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for ( unsigned ip = 0 ; ip < integration_count ; ++ip ) {
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const unsigned ipx = tensor_data.eval_map[ip][0] ;
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const unsigned ipy = tensor_data.eval_map[ip][1] ;
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const unsigned ipz = tensor_data.eval_map[ip][2] ;
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weights[ip] = tensor_data.weights_1d[ ipx ] *
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tensor_data.weights_1d[ ipy ] *
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tensor_data.weights_1d[ ipz ] ;
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for ( unsigned jf = 0 ; jf < function_count ; ++jf ) {
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const unsigned jfx = tensor_data.eval_map[jf][0] ;
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const unsigned jfy = tensor_data.eval_map[jf][1] ;
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const unsigned jfz = tensor_data.eval_map[jf][2] ;
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values[ip][jf] = tensor_data.values_1d[ ipx ][ jfx ] *
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tensor_data.values_1d[ ipy ][ jfy ] *
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tensor_data.values_1d[ ipz ][ jfz ] ;
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gradients[ip][0][jf] = tensor_data.derivs_1d[ ipx ][ jfx ] *
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tensor_data.values_1d[ ipy ][ jfy ] *
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tensor_data.values_1d[ ipz ][ jfz ] ;
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gradients[ip][1][jf] = tensor_data.values_1d[ ipx ][ jfx ] *
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tensor_data.derivs_1d[ ipy ][ jfy ] *
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tensor_data.values_1d[ ipz ][ jfz ] ;
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gradients[ip][2][jf] = tensor_data.values_1d[ ipx ][ jfx ] *
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tensor_data.values_1d[ ipy ][ jfy ] *
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tensor_data.derivs_1d[ ipz ][ jfz ] ;
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}
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}
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}
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};
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//----------------------------------------------------------------------------
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} /* namespace Example */
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} /* namespace Kokkos */
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#endif /* #ifndef KOKKOS_HEXELEMENT_HPP */
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