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/// \file cuda/Backend.h
/// \author Johannes de Fine Licht (johannes.definelicht@cern.ch)
#ifndef VECGEOM_BACKEND_CUDA_INTERFACE_H_
#define VECGEOM_BACKEND_CUDA_INTERFACE_H_
#include "VecGeom/base/Config.h"
#include "VecGeom/base/Global.h"
#ifdef VECGEOM_ENABLE_CUDA
#include "driver_types.h" // Required for cudaError_t type
#include "cuda_runtime.h"
#include <vector>
#include <unordered_map>
#include <type_traits>
namespace vecgeom {
#ifdef VECCORE_CUDA
inline namespace cuda {
template <typename DataClass, typename... ArgsTypes>
__global__ void ConstructOnGpu(DataClass *gpu_ptr, ArgsTypes... params)
{
new (gpu_ptr) DataClass(params...);
}
template <typename DataClass, typename... ArgsTypes>
__global__ void ConstructArrayOnGpu(DataClass *gpu_ptr, size_t nElements, ArgsTypes... params)
{
unsigned int tid = threadIdx.x + blockIdx.x * blockDim.x;
unsigned int idx = tid;
while (idx < nElements) {
new (gpu_ptr + idx) DataClass(params...);
idx += blockDim.x * gridDim.x;
}
}
/*!
* Construct many objects on the GPU, whose addresses and parameters are passed as arrays.
* \tparam DataClass Type of the objects to construct.
* \param nElements Number of elements to construct. It is assumed that all argument arrays have this size.
* \param gpu_ptrs Array of pointers to place the new objects at.
* \param params Array(s) of constructor parameters for each object.
*/
template <typename DataClass, typename... ArgsTypes>
__global__ void ConstructManyOnGpu_kernel(size_t nElements, DataClass **gpu_ptrs, const ArgsTypes *... params)
{
const size_t tid = threadIdx.x + blockIdx.x * blockDim.x;
for (size_t idx = tid; idx < nElements; idx += blockDim.x * gridDim.x) {
new (gpu_ptrs[idx]) DataClass(params[idx]...);
}
}
template <typename DataClass>
__global__ void CopyBBoxesToGpu(size_t nElements, DataClass **raw_ptrs, Precision *boxes)
{
const size_t tid = threadIdx.x + blockIdx.x * blockDim.x;
for (size_t idx = tid; idx < nElements; idx += blockDim.x * gridDim.x) {
raw_ptrs[idx]->SetBBox({boxes[6 * idx], boxes[6 * idx + 1], boxes[6 * idx + 2]},
{boxes[6 * idx + 3], boxes[6 * idx + 4], boxes[6 * idx + 5]});
}
}
template <typename DataClass, typename... ArgsTypes>
void Generic_CopyToGpu(DataClass *const gpu_ptr, ArgsTypes... params)
{
ConstructOnGpu<<<1, 1>>>(gpu_ptr, params...);
}
} // namespace cuda
#else
namespace cuda {
template <typename Type>
Type *AllocateOnDevice();
template <typename DataClass, typename... ArgsTypes>
void Generic_CopyToGpu(DataClass *const gpu_ptr, ArgsTypes... params);
} // namespace cuda
#endif
#ifdef VECCORE_CUDA
namespace cxx {
#else
inline namespace cxx {
#endif
cudaError_t CudaCheckError(const cudaError_t err);
cudaError_t CudaCheckError();
void CudaAssertError(const cudaError_t err);
void CudaAssertError();
cudaError_t CudaMalloc(void **ptr, unsigned size);
cudaError_t CudaCopyToDevice(void *tgt, void const *src, unsigned size);
cudaError_t CudaCopyFromDevice(void *tgt, void const *src, unsigned size);
cudaError_t CudaCopyFromDeviceAsync(void *tgt, void const * src, unsigned size, cudaStream_t stream);
cudaError_t CudaFree(void *ptr);
cudaError_t CudaDeviceSetStackLimit(unsigned size);
cudaError_t CudaDeviceSetHeapLimit(unsigned size);
template <typename Type>
Type *AllocateOnDevice()
{
Type *ptr;
vecgeom::cxx::CudaAssertError(vecgeom::cxx::CudaMalloc((void **)&ptr, sizeof(Type)));
return ptr;
}
template <typename Type>
Type *AllocateOnGpu(const unsigned int size)
{
Type *ptr;
vecgeom::cxx::CudaAssertError(CudaMalloc((void **)&ptr, size));
return ptr;
}
template <typename Type>
Type *AllocateOnGpu()
{
return AllocateOnGpu<Type>(sizeof(Type));
}
template <typename Type>
void FreeFromGpu(Type *const ptr)
{
vecgeom::cxx::CudaAssertError(CudaFree(ptr));
}
template <typename Type>
void CopyToGpu(Type const *const src, Type *const tgt, const unsigned size)
{
vecgeom::cxx::CudaAssertError(CudaCopyToDevice(tgt, src, size));
}
template <typename Type>
void CopyToGpu(Type const *const src, Type *const tgt)
{
CopyToGpu<Type>(src, tgt, sizeof(Type));
}
template <typename Type>
void CopyFromGpu(Type const *const src, Type *const tgt, const unsigned size)
{
vecgeom::cxx::CudaAssertError(CudaCopyFromDevice(tgt, src, size));
}
class DevicePtrBase {
void *fPtr;
#ifdef DEBUG_DEVICEPTR
size_t fAllocatedSize;
bool fIncremented;
#endif
protected:
DevicePtrBase(const DevicePtrBase &orig)
: fPtr(orig.fPtr)
#ifdef DEBUG_DEVICEPTR
,
fAllocatedSize(0), fIncremented(false)
#endif
{
}
DevicePtrBase &operator=(const DevicePtrBase &orig)
{
fPtr = orig.fPtr;
#ifdef DEBUG_DEVICEPTR
fAllocatedSize = orig.fAllocatedSize;
fIncremented = orig.fIncremented;
#endif
return *this;
}
void MemcpyToDevice(const void *what, unsigned long nbytes)
{
if (nbytes) vecgeom::cxx::CudaAssertError(vecgeom::cxx::CudaCopyToDevice(fPtr, what, nbytes));
}
void MemcpyToHostAsync(void *where, unsigned long nbytes, cudaStream_t stream)
{
vecgeom::cxx::CudaAssertError(vecgeom::cxx::CudaCopyFromDeviceAsync(where, fPtr, nbytes, stream));
}
VECCORE_ATT_HOST_DEVICE
void *GetPtr() const { return fPtr; }
void Free()
{
vecgeom::cxx::CudaAssertError(vecgeom::cxx::CudaFree((void *)fPtr));
#ifdef DEBUG_DEVICEPTR
fAllocatedSize = 0;
#endif
}
void Increment(long add)
{
fPtr = (char *)fPtr + add;
#ifdef DEBUG_DEVICEPTR
if (add) fIncremented = true;
#endif
}
public:
DevicePtrBase()
: fPtr(0)
#ifdef DEBUG_DEVICEPTR
,
fAllocatedSize(0), fIncremented(0)
#endif
{
}
explicit DevicePtrBase(void *input)
: fPtr(input)
#ifdef DEBUG_DEVICEPTR
,
fAllocatedSize(0), fIncremented(0)
#endif
{
}
~DevicePtrBase()
{ /* does not own content per se */
}
void Malloc(unsigned long size)
{
vecgeom::cxx::CudaAssertError(vecgeom::cxx::CudaMalloc((void **)&fPtr, size));
#ifdef DEBUG_DEVICEPTR
fAllocatedSize = size;
#endif
}
};
template <typename T>
class DevicePtr;
template <typename Type, typename Derived = DevicePtr<Type>>
class DevicePtrImpl : public DevicePtrBase {
protected:
DevicePtrImpl(const DevicePtrImpl & /* orig */) = default;
DevicePtrImpl &operator=(const DevicePtrImpl & /*orig*/) = default;
DevicePtrImpl() = default;
explicit DevicePtrImpl(void *input) : DevicePtrBase(input) {}
~DevicePtrImpl() = default;
public:
void Allocate(unsigned long nelems = 1) { Malloc(nelems * Derived::SizeOf()); }
void Deallocate() { Free(); }
void ToDevice(const Type *what, unsigned long nelems = 1) { MemcpyToDevice(what, nelems * Derived::SizeOf()); }
void FromDevice(Type *where, cudaStream_t stream)
{
// Async since we pass a stream.
MemcpyToHostAsync(where, Derived::SizeOf(), stream);
}
void FromDevice(Type *where, unsigned long nelems, cudaStream_t stream)
{
// Async since we pass a stream.
MemcpyToHostAsync(where, nelems * Derived::SizeOf(), stream);
}
VECCORE_ATT_HOST_DEVICE
Type *GetPtr() const { return reinterpret_cast<Type *>(DevicePtrBase::GetPtr()); }
VECCORE_ATT_HOST_DEVICE
operator Type *() const { return GetPtr(); }
Derived &operator++() // prefix ++
{
Increment(Derived::SizeOf());
return *(Derived *)this;
}
Derived operator++(int) // postfix ++
{
Derived tmp(*(Derived *)this);
Increment(Derived::SizeOf());
return tmp;
}
Derived &operator+=(long len) // prefix ++
{
Increment(len * Derived::SizeOf());
return *(Derived *)this;
}
};
template <typename Type>
class DevicePtr : public DevicePtrImpl<Type> {
public:
DevicePtr() = default;
DevicePtr(const DevicePtr &) = default;
DevicePtr &operator=(const DevicePtr &orig) = default;
// should be taking a DevicePtr<void*>
explicit DevicePtr(void *input) : DevicePtrImpl<Type>(input) {}
// Need to go via the explicit route accepting all conversion
// because the regular c++ compilation
// does not actually see the declaration for the cuda version
// (and thus can not determine the inheritance).
template <typename inputType>
explicit DevicePtr(DevicePtr<inputType> const &input) : DevicePtrImpl<Type>((void *)input)
{
}
// Disallow conversion from const to non-const.
DevicePtr(DevicePtr<const Type> const &input,
typename std::enable_if<!std::is_const<Type>::value, Type>::type * = nullptr) = delete;
#ifdef VECCORE_CUDA
// Allows implicit conversion from DevicePtr<Derived> to DevicePtr<Base>
template <typename inputType, typename std::enable_if<std::is_base_of<Type, inputType>::value>::type * = nullptr>
DevicePtr(DevicePtr<inputType> const &input) : DevicePtrImpl<Type>(input.GetPtr())
{
}
// Disallow conversion from const to non-const.
template <typename inputType, typename std::enable_if<std::is_base_of<Type, inputType>::value>::type * = nullptr>
DevicePtr(DevicePtr<const inputType> const &input) = delete;
#endif
#ifdef VECCORE_CUDA
template <typename... ArgsTypes>
void Construct(ArgsTypes... params) const
{
ConstructOnGpu<<<1, 1>>>(this->GetPtr(), params...);
}
template <typename... ArgsTypes>
void ConstructArray(size_t nElements, ArgsTypes... params) const
{
ConstructArrayOnGpu<<<nElements, 1>>>(this->GetPtr(), nElements, params...);
}
static size_t SizeOf() { return sizeof(Type); }
#else
template <typename... ArgsTypes>
void Construct(ArgsTypes... params) const;
template <typename... ArgsTypes>
void ConstructArray(size_t nElements, ArgsTypes... params) const;
static size_t SizeOf();
#endif
};
template <typename Type>
class DevicePtr<const Type> : private DevicePtrImpl<const Type> {
public:
DevicePtr() = default;
DevicePtr(const DevicePtr &) = default;
DevicePtr &operator=(const DevicePtr &orig) = default;
// should be taking a DevicePtr<void*>
explicit DevicePtr(void *input) : DevicePtrBase(input) {}
// Need to go via the explicit route accepting all conversion
// because the regular c++ compilation
// does not actually see the declaration for the cuda version
// (and thus can not determine the inheritance).
template <typename inputType>
explicit DevicePtr(DevicePtr<inputType> const &input) : DevicePtrImpl<const Type>((void *)input)
{
}
// Implicit conversion from non-const to const.
DevicePtr(DevicePtr<typename std::remove_const<Type>::type> const &input) : DevicePtrImpl<const Type>((void *)input)
{
}
#ifdef VECCORE_CUDA
// Allows implicit conversion from DevicePtr<Derived> to DevicePtr<Base>
template <typename inputType, typename std::enable_if<std::is_base_of<Type, inputType>::value>::type * = nullptr>
DevicePtr(DevicePtr<inputType> const &input) : DevicePtrImpl<const Type>(input.GetPtr())
{
}
#endif
VECCORE_ATT_HOST_DEVICE
const Type *GetPtr() const { return reinterpret_cast<const Type *>(DevicePtrBase::GetPtr()); }
VECCORE_ATT_HOST_DEVICE
operator const Type *() const { return GetPtr(); }
#ifdef VECCORE_CUDA
template <typename DataClass, typename... ArgsTypes>
void Construct(ArgsTypes... params) const
{
ConstructOnGpu<<<1, 1>>>(*(*this), params...);
}
template <typename... ArgsTypes>
void ConstructArray(size_t nElements, ArgsTypes... params) const
{
ConstructArrayOnGpu<<<nElements, 1>>>(this->GetPtr(), nElements, params...);
}
static size_t SizeOf() { return sizeof(Type); }
#else
template <typename... ArgsTypes>
void Construct(ArgsTypes... params) const;
template <typename... ArgsTypes>
void ConstructArray(size_t nElements, ArgsTypes... params) const;
static size_t SizeOf();
#endif
};
namespace CudaInterfaceHelpers {
/*!
* Copy multiple arrays of values to the GPU.
* For each array, allocate memory on the device, and copy it to the GPU.
* The cpuToGpuMapping finally maps the CPU array pointers to the GPU arrays.
* \param[out] cpuToGpuMapping Mapping of CPU array to GPU array. It gets filled during the function execution.
* \param[in] nElement Number of elements in all collections.
* \param[in] toCopy First array to copy.
* \param[in] restToCopy Parameter pack with more arrays to copy (can be empty).
*/
template <typename Arg_t, typename... Args_t>
void allocateAndCopyToGpu(std::unordered_map<const void *, void *> &cpuToGpuMapping, std::size_t nElement,
const Arg_t *toCopy, const Args_t *... restToCopy)
{
const auto nByte = sizeof(toCopy[0]) * nElement;
const void *hostMem = toCopy;
void *deviceMem = AllocateOnGpu<void *>(nByte);
cpuToGpuMapping[hostMem] = deviceMem;
CopyToGpu(hostMem, deviceMem, nByte);
#if __cplusplus >= 201703L
if constexpr (sizeof...(Args_t) > 0) {
allocateAndCopyToGpu(cpuToGpuMapping, nElement, restToCopy...);
}
#else
// C++11 "fold expression" hack. Please remove once VecGeom moves to c++17.
int expandParameterPack[] = {0, ((void)allocateAndCopyToGpu(cpuToGpuMapping, nElement, restToCopy), 0)...};
(void)expandParameterPack[0]; // Make nvcc happy
#endif
}
} // namespace CudaInterfaceHelpers
/*!
* Construct many objects on the GPU, whose addresses and constructor parameters are passed as arrays.
* \tparam DataClass The type to construct on the GPU.
* \tparam DevPtr_t Device pointer type to specify the location of the GPU objects.
* \param nElement Number of elements to construct. It is assumed that all argument arrays have this length.
* \param gpu_ptrs Array of addresses to place the new objects at.
* \param params Array(s) of constructor parameters with one entry for each object.
*/
template <class DataClass, class DevPtr_t, typename... Args_t>
void ConstructManyOnGpu(std::size_t nElement, const DevPtr_t *gpu_ptrs, const Args_t *... params)
#ifdef VECCORE_CUDA
{
using namespace CudaInterfaceHelpers;
std::unordered_map<const void *, void *> cpuToGpuMem;
std::vector<DataClass *> raw_gpu_ptrs;
std::transform(gpu_ptrs, gpu_ptrs + nElement, std::back_inserter(raw_gpu_ptrs),
[](const DevPtr_t &ptr) { return static_cast<DataClass *>(ptr.GetPtr()); });
allocateAndCopyToGpu(cpuToGpuMem, nElement, raw_gpu_ptrs.data(), params...);
ConstructManyOnGpu_kernel<<<128, 32>>>(raw_gpu_ptrs.size(),
static_cast<decltype(raw_gpu_ptrs.data())>(cpuToGpuMem[raw_gpu_ptrs.data()]),
static_cast<decltype(params)>(cpuToGpuMem[params])...);
for (const auto &memCpu_memGpu : cpuToGpuMem) {
FreeFromGpu(memCpu_memGpu.second);
}
CudaCheckError();
}
#else
;
#endif
template <class DataClass, class DevPtr_t>
void CopyBBoxesToGpuImpl(std::size_t nElement, const DevPtr_t *gpu_ptrs, Precision *boxes_data)
#ifdef VECCORE_CUDA
{
std::unordered_map<const void *, void *> cpuToGpuMem;
std::vector<DataClass *> raw_gpu_ptrs;
std::transform(gpu_ptrs, gpu_ptrs + nElement, std::back_inserter(raw_gpu_ptrs),
[](const DevPtr_t &ptr) { return static_cast<DataClass *>(ptr.GetPtr()); });
const auto nByteBoxes = 6 * nElement * sizeof(Precision);
const auto nByteVolumes = nElement * sizeof(DataClass *);
Precision *boxes_data_gpu = AllocateOnGpu<Precision>(nByteBoxes);
DataClass **raw_gpu_ptrs_gpu = AllocateOnGpu<DataClass *>(nByteVolumes);
CopyToGpu(boxes_data, boxes_data_gpu, nByteBoxes);
CopyToGpu(raw_gpu_ptrs.data(), raw_gpu_ptrs_gpu, nByteVolumes);
cudaDeviceSynchronize();
CopyBBoxesToGpu<DataClass><<<128, 32>>>(raw_gpu_ptrs.size(), raw_gpu_ptrs_gpu, boxes_data_gpu);
FreeFromGpu(boxes_data_gpu);
FreeFromGpu(raw_gpu_ptrs_gpu);
}
#else
;
#endif
} // End cxx namespace
} // namespace vecgeom
#endif // VECGEOM_ENABLE_CUDA
#endif // VECGEOM_BACKEND_CUDA_INTERFACE_H_
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