182 lines
		
	
	
		
			6.8 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
		
		
			
		
	
	
			182 lines
		
	
	
		
			6.8 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
|   | /* | ||
|  |  [auto_generated] | ||
|  |  boost/numeric/odeint/external/mkl/mkl_operations.hpp | ||
|  | 
 | ||
|  |  [begin_description] | ||
|  |  Wrapper classes for intel math kernel library types. | ||
|  |  Get a free, non-commercial download of MKL at | ||
|  |  http://software.intel.com/en-us/articles/non-commercial-software-download/ | ||
|  |  [end_description] | ||
|  | 
 | ||
|  |  Copyright 2010-2011 Mario Mulansky | ||
|  |  Copyright 2011-2013 Karsten Ahnert | ||
|  | 
 | ||
|  |  Distributed under the Boost Software License, Version 1.0. | ||
|  |  (See accompanying file LICENSE_1_0.txt or | ||
|  |  copy at http://www.boost.org/LICENSE_1_0.txt) | ||
|  |  */ | ||
|  | 
 | ||
|  | 
 | ||
|  | #ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_MKL_MKL_OPERATIONS_HPP_INCLUDED | ||
|  | #define BOOST_NUMERIC_ODEINT_EXTERNAL_MKL_MKL_OPERATIONS_HPP_INCLUDED | ||
|  | 
 | ||
|  | #include <iostream> | ||
|  | 
 | ||
|  | #include <mkl_cblas.h> | ||
|  | #include <boost/numeric/odeint/algebra/default_operations.hpp> | ||
|  | 
 | ||
|  | /* exemplary example for writing bindings to the Intel MKL library | ||
|  |  * see test/mkl for how to use mkl with odeint | ||
|  |  * this is a quick and dirty implementation showing the general possibility. | ||
|  |  * It works only with containers based on double and sequential memory allocation. | ||
|  |  */ | ||
|  | 
 | ||
|  | namespace boost { | ||
|  | namespace numeric { | ||
|  | namespace odeint { | ||
|  | 
 | ||
|  | /* only defined for doubles */ | ||
|  | struct mkl_operations | ||
|  | { | ||
|  |     //template< class Fac1 , class Fac2 > struct scale_sum2; | ||
|  | 
 | ||
|  |     template< class F1 = double , class F2 = F1 > | ||
|  |     struct scale_sum2 | ||
|  |     { | ||
|  |         typedef double Fac1; | ||
|  |         typedef double Fac2; | ||
|  |         const Fac1 m_alpha1; | ||
|  |         const Fac2 m_alpha2; | ||
|  | 
 | ||
|  |         scale_sum2( const Fac1 alpha1 , const Fac2 alpha2 ) : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) { } | ||
|  | 
 | ||
|  |         template< class T1 , class T2 , class T3 > | ||
|  |         void operator()( T1 &t1 , const T2 &t2 , const T3 &t3) const | ||
|  |         {   // t1 = m_alpha1 * t2 + m_alpha2 * t3; | ||
|  |             // we get Containers that have size() and [i]-access | ||
|  | 
 | ||
|  |             const int n = t1.size(); | ||
|  |             //boost::numeric::odeint::copy( t1 , t3 ); | ||
|  |             if( &(t2[0]) != &(t1[0]) ) | ||
|  |             { | ||
|  |                 cblas_dcopy( n , &(t2[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             } | ||
|  |             cblas_dscal( n , m_alpha1 , &(t1[0]) , 1 ); | ||
|  |             cblas_daxpy( n , m_alpha2 , &(t3[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             //daxpby( &n , &m_alpha2 , &(t3[0]) , &one , &m_alpha1 , &(t1[0]) , &one ); | ||
|  |         } | ||
|  |     }; | ||
|  | 
 | ||
|  |     template< class F1 = double , class F2 = F1 , class F3 = F2 > | ||
|  |     struct scale_sum3 | ||
|  |     { | ||
|  |         typedef double Fac1; | ||
|  |         typedef double Fac2; | ||
|  |         typedef double Fac3; | ||
|  |         const Fac1 m_alpha1; | ||
|  |         const Fac2 m_alpha2; | ||
|  |         const Fac3 m_alpha3; | ||
|  | 
 | ||
|  |         scale_sum3( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 ) | ||
|  |             : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) { } | ||
|  | 
 | ||
|  |         template< class T1 , class T2 , class T3 , class T4 > | ||
|  |         void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 ) const | ||
|  |         {   // t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4; | ||
|  |             // we get Containers that have size() and [i]-access | ||
|  | 
 | ||
|  |             const int n = t1.size(); | ||
|  |             //boost::numeric::odeint::copy( t1 , t3 ); | ||
|  |             if( &(t2[0]) != &(t1[0]) ) | ||
|  |             { | ||
|  |                 cblas_dcopy( n , &(t2[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             } | ||
|  |             cblas_dscal( n , m_alpha1 , &(t1[0]) , 1 ); | ||
|  |             cblas_daxpy( n , m_alpha2 , &(t3[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             //daxpby( &n , &m_alpha2 , &(t3[0]) , &one , &m_alpha1 , &(t1[0]) , &one ); | ||
|  |             cblas_daxpy( n , m_alpha3 , &(t4[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |         } | ||
|  |     }; | ||
|  | 
 | ||
|  |     template< class F1 = double , class F2 = F1 , class F3 = F2 , class F4 = F3 > | ||
|  |     struct scale_sum4 | ||
|  |     { | ||
|  |         typedef double Fac1; | ||
|  |         typedef double Fac2; | ||
|  |         typedef double Fac3; | ||
|  |         typedef double Fac4; | ||
|  |         const Fac1 m_alpha1; | ||
|  |         const Fac2 m_alpha2; | ||
|  |         const Fac3 m_alpha3; | ||
|  |         const Fac4 m_alpha4; | ||
|  | 
 | ||
|  |         scale_sum4( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 , const Fac4 alpha4 ) | ||
|  |             : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) { } | ||
|  | 
 | ||
|  |         template< class T1 , class T2 , class T3 , class T4 , class T5 > | ||
|  |         void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 ) const | ||
|  |         {   // t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5; | ||
|  |             // we get Containers that have size() and [i]-access | ||
|  | 
 | ||
|  |             const int n = t1.size(); | ||
|  |             //boost::numeric::odeint::copy( t1 , t3 ); | ||
|  |             if( &(t2[0]) != &(t1[0]) ) | ||
|  |             { | ||
|  |                 cblas_dcopy( n , &(t2[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             } | ||
|  | 
 | ||
|  |             cblas_dscal( n , m_alpha1 , &(t1[0]) , 1 ); | ||
|  |             cblas_daxpy( n , m_alpha2 , &(t3[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             //daxpby( &n , &m_alpha2 , &(t3[0]) , &one , &m_alpha1 , &(t1[0]) , &one ); | ||
|  |             cblas_daxpy( n , m_alpha3 , &(t4[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             cblas_daxpy( n , m_alpha4 , &(t5[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |         } | ||
|  |     }; | ||
|  | 
 | ||
|  | 
 | ||
|  |     template< class F1 = double , class F2 = F1 , class F3 = F2 , class F4 = F3 , class F5 = F4 > | ||
|  |     struct scale_sum5 | ||
|  |     { | ||
|  |         typedef double Fac1; | ||
|  |         typedef double Fac2; | ||
|  |         typedef double Fac3; | ||
|  |         typedef double Fac4; | ||
|  |         typedef double Fac5; | ||
|  |         const Fac1 m_alpha1; | ||
|  |         const Fac2 m_alpha2; | ||
|  |         const Fac3 m_alpha3; | ||
|  |         const Fac4 m_alpha4; | ||
|  |         const Fac5 m_alpha5; | ||
|  | 
 | ||
|  |         scale_sum5( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 , const Fac4 alpha4 , const Fac5 alpha5 ) | ||
|  |             : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) { } | ||
|  | 
 | ||
|  |         template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6   > | ||
|  |         void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 ) const | ||
|  |         {   // t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6; | ||
|  |             // we get Containers that have size() and [i]-access | ||
|  | 
 | ||
|  |             const int n = t1.size(); | ||
|  |             //boost::numeric::odeint::copy( t1 , t3 ); | ||
|  |             if( &(t2[0]) != &(t1[0]) ) | ||
|  |             { | ||
|  |                 cblas_dcopy( n , &(t2[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             } | ||
|  | 
 | ||
|  |             cblas_dscal( n , m_alpha1 , &(t1[0]) , 1 ); | ||
|  |             cblas_daxpy( n , m_alpha2 , &(t3[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             //daxpby( &n , &m_alpha2 , &(t3[0]) , &one , &m_alpha1 , &(t1[0]) , &one ); | ||
|  |             cblas_daxpy( n , m_alpha3 , &(t4[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             cblas_daxpy( n , m_alpha4 , &(t5[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |             cblas_daxpy( n , m_alpha5 , &(t6[0]) , 1 , &(t1[0]) , 1 ); | ||
|  |         } | ||
|  |     }; | ||
|  | 
 | ||
|  | }; | ||
|  | 
 | ||
|  | } // odeint | ||
|  | } // numeric | ||
|  | } // boost | ||
|  | 
 | ||
|  | #endif // BOOST_NUMERIC_ODEINT_EXTERNAL_MKL_MKL_OPERATIONS_HPP_INCLUDED |