Homec4science
Diffusion lammps (runner) Browse

lammps/lib/kokkos/core/src/Cuda/KokkosExp_Cuda_View.hpp
13bbbd83a65crunner

Last Change
Raw File

KokkosExp_Cuda_View.hpp
View Options

/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#ifndef KOKKOS_EXPERIMENTAL_CUDA_VIEW_HPP
#define KOKKOS_EXPERIMENTAL_CUDA_VIEW_HPP
/* only compile this file if CUDA is enabled for Kokkos */
#if defined( KOKKOS_HAVE_CUDA )
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Experimental {
namespace Impl {
template<>
struct ViewOperatorBoundsErrorAbort< Kokkos::CudaSpace > {
KOKKOS_INLINE_FUNCTION
static void apply( const size_t rank
, const size_t n0 , const size_t n1
, const size_t n2 , const size_t n3
, const size_t n4 , const size_t n5
, const size_t n6 , const size_t n7
, const size_t i0 , const size_t i1
, const size_t i2 , const size_t i3
, const size_t i4 , const size_t i5
, const size_t i6 , const size_t i7 )
{
const int r =
( n0 <= i0 ? 0 :
( n1 <= i1 ? 1 :
( n2 <= i2 ? 2 :
( n3 <= i3 ? 3 :
( n4 <= i4 ? 4 :
( n5 <= i5 ? 5 :
( n6 <= i6 ? 6 : 7 )))))));
const size_t n =
( n0 <= i0 ? n0 :
( n1 <= i1 ? n1 :
( n2 <= i2 ? n2 :
( n3 <= i3 ? n3 :
( n4 <= i4 ? n4 :
( n5 <= i5 ? n5 :
( n6 <= i6 ? n6 : n7 )))))));
const size_t i =
( n0 <= i0 ? i0 :
( n1 <= i1 ? i1 :
( n2 <= i2 ? i2 :
( n3 <= i3 ? i3 :
( n4 <= i4 ? i4 :
( n5 <= i5 ? i5 :
( n6 <= i6 ? i6 : i7 )))))));
printf("Cuda view array bounds error index %d : FAILED %lu < %lu\n" , r , i , n );
Kokkos::Impl::cuda_abort("Cuda view array bounds error");
}
};
} // namespace Impl
} // namespace Experimental
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Experimental {
namespace Impl {
// Cuda Texture fetches can be performed for 4, 8 and 16 byte objects (int,int2,int4)
// Via reinterpret_case this can be used to support all scalar types of those sizes.
// Any other scalar type falls back to either normal reads out of global memory,
// or using the __ldg intrinsic on Kepler GPUs or newer (Compute Capability >= 3.0)
template< typename ValueType , typename AliasType >
struct CudaTextureFetch {
::cudaTextureObject_t m_obj ;
const ValueType * m_ptr ;
int m_offset ;
// Deference operator pulls through texture object and returns by value
template< typename iType >
KOKKOS_INLINE_FUNCTION
ValueType operator[]( const iType & i ) const
{
#if defined( __CUDA_ARCH__ ) && ( 300 <= __CUDA_ARCH__ )
AliasType v = tex1Dfetch<AliasType>( m_obj , i + m_offset );
return *(reinterpret_cast<ValueType*> (&v));
#else
return m_ptr[ i ];
#endif
}
// Pointer to referenced memory
KOKKOS_INLINE_FUNCTION
operator const ValueType * () const { return m_ptr ; }
KOKKOS_INLINE_FUNCTION
CudaTextureFetch() : m_obj() , m_ptr() , m_offset() {}
KOKKOS_INLINE_FUNCTION
~CudaTextureFetch() {}
KOKKOS_INLINE_FUNCTION
CudaTextureFetch( const CudaTextureFetch & rhs )
: m_obj( rhs.m_obj )
, m_ptr( rhs.m_ptr )
, m_offset( rhs.m_offset )
{}
KOKKOS_INLINE_FUNCTION
CudaTextureFetch( CudaTextureFetch && rhs )
: m_obj( rhs.m_obj )
, m_ptr( rhs.m_ptr )
, m_offset( rhs.m_offset )
{}
KOKKOS_INLINE_FUNCTION
CudaTextureFetch & operator = ( const CudaTextureFetch & rhs )
{
m_obj = rhs.m_obj ;
m_ptr = rhs.m_ptr ;
m_offset = rhs.m_offset ;
return *this ;
}
KOKKOS_INLINE_FUNCTION
CudaTextureFetch & operator = ( CudaTextureFetch && rhs )
{
m_obj = rhs.m_obj ;
m_ptr = rhs.m_ptr ;
m_offset = rhs.m_offset ;
return *this ;
}
// Texture object spans the entire allocation.
// This handle may view a subset of the allocation, so an offset is required.
template< class CudaMemorySpace >
inline explicit
CudaTextureFetch( const ValueType * const arg_ptr
, Kokkos::Experimental::Impl::SharedAllocationRecord< CudaMemorySpace , void > & record
)
: m_obj( record.template attach_texture_object< AliasType >() )
, m_ptr( arg_ptr )
, m_offset( record.attach_texture_object_offset( reinterpret_cast<const AliasType*>( arg_ptr ) ) )
{}
};
#if defined( KOKKOS_CUDA_USE_LDG_INTRINSIC )
template< typename ValueType , typename AliasType >
struct CudaLDGFetch {
const ValueType * m_ptr ;
template< typename iType >
KOKKOS_INLINE_FUNCTION
ValueType operator[]( const iType & i ) const
{
AliasType v = __ldg(reinterpret_cast<AliasType*>(&m_ptr[i]));
return *(reinterpret_cast<ValueType*> (&v));
}
KOKKOS_INLINE_FUNCTION
operator const ValueType * () const { return m_ptr ; }
KOKKOS_INLINE_FUNCTION
CudaLDGFetch() : m_ptr() {}
KOKKOS_INLINE_FUNCTION
~CudaLDGFetch() {}
KOKKOS_INLINE_FUNCTION
CudaLDGFetch( const CudaLDGFetch & rhs )
: m_ptr( rhs.m_ptr )
{}
KOKKOS_INLINE_FUNCTION
CudaLDGFetch( CudaLDGFetch && rhs )
: m_ptr( rhs.m_ptr )
{}
KOKKOS_INLINE_FUNCTION
CudaLDGFetch & operator = ( const CudaLDGFetch & rhs )
{
m_ptr = rhs.m_ptr ;
return *this ;
}
KOKKOS_INLINE_FUNCTION
CudaLDGFetch & operator = ( CudaLDGFetch && rhs )
{
m_ptr = rhs.m_ptr ;
return *this ;
}
template< class CudaMemorySpace >
inline explicit
CudaTextureFetch( const ValueType * const arg_ptr
, Kokkos::Experimental::Impl::SharedAllocationRecord< CudaMemorySpace , void > const &
)
: m_ptr( arg_data_ptr )
{}
};
#endif
} // namespace Impl
} // namespace Experimental
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Experimental {
namespace Impl {
/** \brief Replace Default ViewDataHandle with Cuda texture fetch specialization
* if 'const' value type, CudaSpace and random access.
*/
template< class Traits >
class ViewDataHandle< Traits ,
typename std::enable_if<(
// Is Cuda memory space
( std::is_same< typename Traits::memory_space,Kokkos::CudaSpace>::value ||
std::is_same< typename Traits::memory_space,Kokkos::CudaUVMSpace>::value )
&&
// Is a trivial const value of 4, 8, or 16 bytes
std::is_trivial<typename Traits::const_value_type>::value
&&
std::is_same<typename Traits::const_value_type,typename Traits::value_type>::value
&&
( sizeof(typename Traits::const_value_type) == 4 ||
sizeof(typename Traits::const_value_type) == 8 ||
sizeof(typename Traits::const_value_type) == 16 )
&&
// Random access trait
( Traits::memory_traits::RandomAccess != 0 )
)>::type >
{
public:
using track_type = Kokkos::Experimental::Impl::SharedAllocationTracker ;
using value_type = typename Traits::const_value_type ;
using return_type = typename Traits::const_value_type ; // NOT a reference
using alias_type = typename std::conditional< ( sizeof(value_type) == 4 ) , int ,
typename std::conditional< ( sizeof(value_type) == 8 ) , ::int2 ,
typename std::conditional< ( sizeof(value_type) == 16 ) , ::int4 , void
>::type
>::type
>::type ;
#if defined( KOKKOS_CUDA_USE_LDG_INTRINSIC )
using handle_type = Kokkos::Experimental::Impl::CudaLDGFetch< value_type , alias_type > ;
#else
using handle_type = Kokkos::Experimental::Impl::CudaTextureFetch< value_type , alias_type > ;
#endif
KOKKOS_INLINE_FUNCTION
static handle_type const & assign( handle_type const & arg_handle , track_type const & /* arg_tracker */ )
{
return arg_handle ;
}
KOKKOS_INLINE_FUNCTION
static handle_type assign( value_type * arg_data_ptr, track_type const & arg_tracker )
{
#if defined( KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_HOST )
// Assignment of texture = non-texture requires creation of a texture object
// which can only occur on the host. In addition, 'get_record' is only valid
// if called in a host execution space
return handle_type( arg_data_ptr , arg_tracker.template get_record< typename Traits::memory_space >() );
#else
Kokkos::Impl::cuda_abort("Cannot create Cuda texture object from within a Cuda kernel");
return handle_type();
#endif
}
};
}
}
}
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
#endif /* #if defined( KOKKOS_HAVE_CUDA ) */
#endif /* #ifndef KOKKOS_CUDA_VIEW_HPP */
c4science · Help