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Kokkos_CudaExec.hpp
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Kokkos_CudaExec.hpp
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/*
//@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_CUDAEXEC_HPP
#define KOKKOS_CUDAEXEC_HPP
#include <Kokkos_Macros.hpp>
#ifdef KOKKOS_ENABLE_CUDA
#include <string>
#include <cstdint>
#include <Kokkos_Parallel.hpp>
#include <impl/Kokkos_Error.hpp>
#include <Cuda/Kokkos_Cuda_abort.hpp>
#include <Cuda/Kokkos_Cuda_Error.hpp>
#include <Cuda/Kokkos_Cuda_Locks.hpp>
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Impl {
struct CudaTraits {
enum { WarpSize = 32 /* 0x0020 */ };
enum { WarpIndexMask = 0x001f /* Mask for warpindex */ };
enum { WarpIndexShift = 5 /* WarpSize == 1 << WarpShift */ };
enum { SharedMemoryBanks = 32 /* Compute device 2.0 */ };
enum { SharedMemoryCapacity = 0x0C000 /* 48k shared / 16k L1 Cache */ };
enum { SharedMemoryUsage = 0x04000 /* 16k shared / 48k L1 Cache */ };
enum { UpperBoundGridCount = 65535 /* Hard upper bound */ };
enum { ConstantMemoryCapacity = 0x010000 /* 64k bytes */ };
enum { ConstantMemoryUsage = 0x008000 /* 32k bytes */ };
enum { ConstantMemoryCache = 0x002000 /* 8k bytes */ };
typedef unsigned long
ConstantGlobalBufferType[ ConstantMemoryUsage / sizeof(unsigned long) ];
enum { ConstantMemoryUseThreshold = 0x000200 /* 512 bytes */ };
KOKKOS_INLINE_FUNCTION static
CudaSpace::size_type warp_count( CudaSpace::size_type i )
{ return ( i + WarpIndexMask ) >> WarpIndexShift ; }
KOKKOS_INLINE_FUNCTION static
CudaSpace::size_type warp_align( CudaSpace::size_type i )
{
enum { Mask = ~CudaSpace::size_type( WarpIndexMask ) };
return ( i + WarpIndexMask ) & Mask ;
}
};
//----------------------------------------------------------------------------
CudaSpace::size_type cuda_internal_multiprocessor_count();
CudaSpace::size_type cuda_internal_maximum_warp_count();
CudaSpace::size_type cuda_internal_maximum_grid_count();
CudaSpace::size_type cuda_internal_maximum_shared_words();
CudaSpace::size_type cuda_internal_maximum_concurrent_block_count();
CudaSpace::size_type * cuda_internal_scratch_flags( const CudaSpace::size_type size );
CudaSpace::size_type * cuda_internal_scratch_space( const CudaSpace::size_type size );
CudaSpace::size_type * cuda_internal_scratch_unified( const CudaSpace::size_type size );
} // namespace Impl
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
#if defined( __CUDACC__ )
/** \brief Access to constant memory on the device */
#ifdef KOKKOS_ENABLE_CUDA_RELOCATABLE_DEVICE_CODE
__device__ __constant__
extern unsigned long kokkos_impl_cuda_constant_memory_buffer[] ;
#else
__device__ __constant__
unsigned long kokkos_impl_cuda_constant_memory_buffer[ Kokkos::Impl::CudaTraits::ConstantMemoryUsage / sizeof(unsigned long) ] ;
#endif
namespace Kokkos {
namespace Impl {
void* cuda_resize_scratch_space(std::int64_t bytes, bool force_shrink = false);
}
}
template< typename T >
inline
__device__
T * kokkos_impl_cuda_shared_memory()
{ extern __shared__ Kokkos::CudaSpace::size_type sh[]; return (T*) sh ; }
namespace Kokkos {
namespace Impl {
//----------------------------------------------------------------------------
// See section B.17 of Cuda C Programming Guide Version 3.2
// for discussion of
// __launch_bounds__(maxThreadsPerBlock,minBlocksPerMultiprocessor)
// function qualifier which could be used to improve performance.
//----------------------------------------------------------------------------
// Maximize L1 cache and minimize shared memory:
// cudaFuncSetCacheConfig(MyKernel, cudaFuncCachePreferL1 );
// For 2.0 capability: 48 KB L1 and 16 KB shared
//----------------------------------------------------------------------------
template< class DriverType>
__global__
static void cuda_parallel_launch_constant_memory()
{
const DriverType & driver =
*((const DriverType *) kokkos_impl_cuda_constant_memory_buffer );
driver();
}
template< class DriverType, unsigned int maxTperB, unsigned int minBperSM >
__global__
__launch_bounds__(maxTperB, minBperSM)
static void cuda_parallel_launch_constant_memory()
{
const DriverType & driver =
*((const DriverType *) kokkos_impl_cuda_constant_memory_buffer );
driver();
}
template< class DriverType>
__global__
static void cuda_parallel_launch_local_memory( const DriverType driver )
{
driver();
}
template< class DriverType, unsigned int maxTperB, unsigned int minBperSM >
__global__
__launch_bounds__(maxTperB, minBperSM)
static void cuda_parallel_launch_local_memory( const DriverType driver )
{
driver();
}
template < class DriverType
, class LaunchBounds = Kokkos::LaunchBounds<>
, bool Large = ( CudaTraits::ConstantMemoryUseThreshold < sizeof(DriverType) ) >
struct CudaParallelLaunch ;
template < class DriverType, class LaunchBounds >
struct CudaParallelLaunch< DriverType, LaunchBounds, true > {
inline
CudaParallelLaunch( const DriverType & driver
, const dim3 & grid
, const dim3 & block
, const int shmem
, const cudaStream_t stream = 0 )
{
if ( grid.x && ( block.x * block.y * block.z ) ) {
if ( sizeof( Kokkos::Impl::CudaTraits::ConstantGlobalBufferType ) <
sizeof( DriverType ) ) {
Kokkos::Impl::throw_runtime_exception( std::string("CudaParallelLaunch FAILED: Functor is too large") );
}
// Fence before changing settings and copying closure
Kokkos::Cuda::fence();
if ( CudaTraits::SharedMemoryCapacity < shmem ) {
Kokkos::Impl::throw_runtime_exception( std::string("CudaParallelLaunch FAILED: shared memory request is too large") );
}
#ifndef KOKKOS_ARCH_KEPLER //On Kepler the L1 has no benefit since it doesn't cache reads
else if ( shmem ) {
CUDA_SAFE_CALL( cudaFuncSetCacheConfig( cuda_parallel_launch_constant_memory< DriverType, LaunchBounds::maxTperB, LaunchBounds::minBperSM > , cudaFuncCachePreferShared ) );
} else {
CUDA_SAFE_CALL( cudaFuncSetCacheConfig( cuda_parallel_launch_constant_memory< DriverType, LaunchBounds::maxTperB, LaunchBounds::minBperSM > , cudaFuncCachePreferL1 ) );
}
#endif
// Copy functor to constant memory on the device
cudaMemcpyToSymbol( kokkos_impl_cuda_constant_memory_buffer , & driver , sizeof(DriverType) );
KOKKOS_ENSURE_CUDA_LOCK_ARRAYS_ON_DEVICE();
// Invoke the driver function on the device
cuda_parallel_launch_constant_memory< DriverType, LaunchBounds::maxTperB, LaunchBounds::minBperSM ><<< grid , block , shmem , stream >>>();
#if defined( KOKKOS_ENABLE_DEBUG_BOUNDS_CHECK )
CUDA_SAFE_CALL( cudaGetLastError() );
Kokkos::Cuda::fence();
#endif
}
}
};
template < class DriverType, class LaunchBounds >
struct CudaParallelLaunch< DriverType, LaunchBounds, false > {
inline
CudaParallelLaunch( const DriverType & driver
, const dim3 & grid
, const dim3 & block
, const int shmem
, const cudaStream_t stream = 0 )
{
if ( grid.x && ( block.x * block.y * block.z ) ) {
if ( CudaTraits::SharedMemoryCapacity < shmem ) {
Kokkos::Impl::throw_runtime_exception( std::string("CudaParallelLaunch FAILED: shared memory request is too large") );
}
#ifndef KOKKOS_ARCH_KEPLER //On Kepler the L1 has no benefit since it doesn't cache reads
else if ( shmem ) {
CUDA_SAFE_CALL( cudaFuncSetCacheConfig( cuda_parallel_launch_local_memory< DriverType, LaunchBounds::maxTperB, LaunchBounds::minBperSM > , cudaFuncCachePreferShared ) );
} else {
CUDA_SAFE_CALL( cudaFuncSetCacheConfig( cuda_parallel_launch_local_memory< DriverType, LaunchBounds::maxTperB, LaunchBounds::minBperSM > , cudaFuncCachePreferL1 ) );
}
#endif
KOKKOS_ENSURE_CUDA_LOCK_ARRAYS_ON_DEVICE();
cuda_parallel_launch_local_memory< DriverType, LaunchBounds::maxTperB, LaunchBounds::minBperSM ><<< grid , block , shmem , stream >>>( driver );
#if defined( KOKKOS_ENABLE_DEBUG_BOUNDS_CHECK )
CUDA_SAFE_CALL( cudaGetLastError() );
Kokkos::Cuda::fence();
#endif
}
}
};
//----------------------------------------------------------------------------
} // namespace Impl
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
#endif /* defined( __CUDACC__ ) */
#endif /* defined( KOKKOS_ENABLE_CUDA ) */
#endif /* #ifndef KOKKOS_CUDAEXEC_HPP */

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