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// A C++ wrapper for CUDA (not quite yet)
#ifndef _AFJDFJSDFSD_PYCUDA_HEADER_SEEN_CUDA_HPP
#define _AFJDFJSDFSD_PYCUDA_HEADER_SEEN_CUDA_HPP
#include <cuda.h>
#include <stdexcept>
#include <boost/shared_ptr.hpp>
#include <boost/foreach.hpp>
#include <boost/weak_ptr.hpp>
#include <utility>
#include <stack>
#include <iostream>
#include <vector>
#include <boost/python.hpp>
// #define CUDAPP_TRACE_CUDA
#ifdef CUDAPP_TRACE_CUDA
#define CUDAPP_PRINT_CALL_TRACE(NAME) std::cerr << NAME << std::endl;
#else
#define CUDAPP_PRINT_CALL_TRACE(NAME) /*nothing*/
#endif
#define CUDAPP_CALL_GUARDED_THREADED(NAME, ARGLIST) \
CUDAPP_PRINT_CALL_TRACE(#NAME); \
CUresult cu_status_code; \
Py_BEGIN_ALLOW_THREADS \
cu_status_code = NAME ARGLIST; \
Py_END_ALLOW_THREADS \
if (cu_status_code != CUDA_SUCCESS) \
throw cuda::error(#NAME, cu_status_code);\
}
#define CUDAPP_CALL_GUARDED(NAME, ARGLIST) \
{ \
CUDAPP_PRINT_CALL_TRACE(#NAME); \
CUresult cu_status_code; \
cu_status_code = NAME ARGLIST; \
if (cu_status_code != CUDA_SUCCESS) \
throw cuda::error(#NAME, cu_status_code);\
}
namespace cuda
{
namespace py = boost::python;
class error : public std::runtime_error
{
private:
const char *m_routine;
CUresult m_code;
private:
static std::string make_message(const char *rout, CUresult c, const char *msg)
{
std::string result = rout;
result += " failed: ";
result += curesult_to_str(c);
if (msg)
{
result += " - ";
result += msg;
}
return result;
}
error(const char *rout, CUresult c, const char *msg=0)
: std::runtime_error(make_message(rout, c, msg)),
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m_routine(rout), m_code(c)
{ }
const char *routine() const
{
return m_routine;
}
CUresult code() const
{
return m_code;
}
static const char *curesult_to_str(CUresult e)
{
switch (e)
{
case CUDA_SUCCESS: return "success";
case CUDA_ERROR_INVALID_VALUE: return "invalid value";
case CUDA_ERROR_OUT_OF_MEMORY: return "out of memory";
case CUDA_ERROR_NOT_INITIALIZED: return "not initialized";
#if CUDA_VERSION >= 2000
case CUDA_ERROR_DEINITIALIZED: return "deinitialized";
#endif
case CUDA_ERROR_NO_DEVICE: return "no device";
case CUDA_ERROR_INVALID_DEVICE: return "invalid device";
case CUDA_ERROR_INVALID_IMAGE: return "invalid image";
case CUDA_ERROR_INVALID_CONTEXT: return "invalid context";
case CUDA_ERROR_CONTEXT_ALREADY_CURRENT: return "context already current";
case CUDA_ERROR_MAP_FAILED: return "map failed";
case CUDA_ERROR_UNMAP_FAILED: return "unmap failed";
case CUDA_ERROR_ARRAY_IS_MAPPED: return "array is mapped";
case CUDA_ERROR_ALREADY_MAPPED: return "already mapped";
case CUDA_ERROR_NO_BINARY_FOR_GPU: return "no binary for gpu";
case CUDA_ERROR_ALREADY_ACQUIRED: return "already acquired";
case CUDA_ERROR_NOT_MAPPED: return "not mapped";
case CUDA_ERROR_INVALID_SOURCE: return "invalid source";
case CUDA_ERROR_FILE_NOT_FOUND: return "file not found";
case CUDA_ERROR_INVALID_HANDLE: return "invalid handle";
case CUDA_ERROR_NOT_FOUND: return "not found";
case CUDA_ERROR_NOT_READY: return "not ready";
case CUDA_ERROR_LAUNCH_FAILED: return "launch failed";
case CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES: return "launch out of resources";
case CUDA_ERROR_LAUNCH_TIMEOUT: return "launch timeout";
case CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING: return "launch incompatible texturing";
case CUDA_ERROR_UNKNOWN: return "unknown";
default: return "invalid error code";
}
}
};
// device -------------------------------------------------------------------
class context;
class device
{
private:
CUdevice m_device;
public:
device(CUdevice dev)
: m_device(dev)
{ }
static int count()
{
int result;
CUDAPP_CALL_GUARDED(cuDeviceGetCount, (&result));
return result;
}
std::string name()
{
char buffer[1024];
CUDAPP_CALL_GUARDED(cuDeviceGetName, (buffer, sizeof(buffer), m_device));
return buffer;
}
py::tuple compute_capability()
{
int major, minor;
CUDAPP_CALL_GUARDED(cuDeviceComputeCapability, (&major, &minor, m_device));
return py::make_tuple(major, minor);
}
unsigned int total_memory()
{
unsigned int bytes;
CUDAPP_CALL_GUARDED(cuDeviceTotalMem, (&bytes, m_device));
return bytes;
}
int get_attribute(CUdevice_attribute attr)
{
int result;
CUDAPP_CALL_GUARDED(cuDeviceGetAttribute, (&result, attr, m_device));
return result;
}
bool operator==(const device &other) const
{
return m_device == other.m_device;
}
bool operator!=(const device &other) const
{
return m_device != other.m_device;
}
long hash() const
{
return m_device;
}
boost::shared_ptr<context> make_context(unsigned int flags);
};
inline
void init(unsigned int flags)
{
CUDAPP_CALL_GUARDED(cuInit, (flags));
}
device *make_device(int ordinal)
{
CUdevice result;
CUDAPP_CALL_GUARDED(cuDeviceGet, (&result, ordinal));
return new device(result);
}
// context ------------------------------------------------------------------
/* A word on context management: We don't let CUDA's context stack get more
* than one deep. CUDA only supports pushing floating contexts. We may wish
* to push contexts that are already active at a deeper stack level, so we
* maintain all contexts floating other than the top one.
*/
class context : boost::noncopyable
{
private:
CUcontext m_context;
bool m_valid;
unsigned m_use_count;
typedef std::stack<boost::weak_ptr<context>,
std::vector<boost::weak_ptr<context> > > context_stack_t;
static context_stack_t m_context_stack;
public:
context(CUcontext ctx)
: m_context(ctx), m_valid(true), m_use_count(1)
{ }
~context()
if (m_use_count)
std::cerr
<< "-----------------------------------------------------------" << std::endl
<< "PyCuda WARNING: I'm being asked to destroy a " << std::endl
<< "context that's part of the current context stack." << std::endl
<< "-----------------------------------------------------------" << std::endl
<< "I will pick the next lower active context from the" << std::endl
<< "context stack. Since this choice is happening" << std::endl
<< "at an unspecified point in time, your code" << std::endl
<< "may be making false assumptions about which" << std::endl
<< "context is active at what point." << std::endl
<< "Call detach() explicitly to avoid this warning." << std::endl
<< "-----------------------------------------------------------" << std::endl
<< "If Python is terminating abnormally (eg. exiting upon an" << std::endl
<< "unhandled exception), you may ignore this." << std::endl
<< "-----------------------------------------------------------" << std::endl;
CUcontext data() const
{ return m_context; }
void detach()
{
if (m_valid)
{
if (current_context().get() == this)
{
CUDAPP_CALL_GUARDED(cuCtxDetach, (m_context));
}
else
CUDAPP_CALL_GUARDED(cuCtxDestroy, (m_context));
m_valid = false;
boost::shared_ptr<context> new_active = current_context(this);
if (new_active.get())
CUDAPP_CALL_GUARDED(cuCtxPushCurrent, (new_active->m_context));
}
else
throw error("context::detach", CUDA_ERROR_INVALID_CONTEXT,
"cannot detach from invalid context");
}
static device get_device()
{
CUdevice dev;
CUDAPP_CALL_GUARDED(cuCtxGetDevice, (&dev));
return device(dev);
}
#if CUDA_VERSION >= 2000
static void prepare_context_switch()
{
if (context::m_context_stack.size())
{
CUcontext popped;
CUDAPP_CALL_GUARDED(cuCtxPopCurrent, (&popped));
}
}
void pop()
{
prepare_context_switch();
m_context_stack.pop();
--m_use_count;
boost::shared_ptr<context> current = current_context();
if (current)
CUDAPP_CALL_GUARDED(cuCtxPushCurrent, (current_context()->m_context));
}
#else
static void prepare_context_switch() { }
#endif
static void synchronize()
{ CUDAPP_CALL_GUARDED_THREADED(cuCtxSynchronize, ()); }
static boost::shared_ptr<context> current_context(context *except=0)
while (true)
{
if (m_context_stack.size() == 0)
return boost::shared_ptr<context>();
boost::weak_ptr<context> result(m_context_stack.top());
if (!result.expired() && result.lock().get() != except)
// good, weak pointer didn't expire
// (treating except as expired weak pointer)
return result.lock();
}
else
{
// weak pointer invalidated, pop it and try again.
m_context_stack.pop();
}
friend class device;
friend void context_push(boost::shared_ptr<context> ctx);
};
boost::shared_ptr<context> device::make_context(unsigned int flags)
{
context::prepare_context_switch();
CUcontext ctx;
CUDAPP_CALL_GUARDED(cuCtxCreate, (&ctx, flags, m_device));
boost::shared_ptr<context> result(new context(ctx));
context::m_context_stack.push(result);
return result;
}
#if CUDA_VERSION >= 2000
void context_push(boost::shared_ptr<context> ctx)
{
context::prepare_context_switch();
CUDAPP_CALL_GUARDED(cuCtxPushCurrent, (ctx->m_context));
context::m_context_stack.push(ctx);
++ctx->m_use_count;
}
#endif
class explicit_context_dependent
{
private:
boost::shared_ptr<context> m_ward_context;
public:
void acquire_context()
{
m_ward_context = context::current_context();
if (m_ward_context.get() == 0)
throw error("explicit_context_dependent",
CUDA_ERROR_INVALID_CONTEXT,
"no currently active context?");
}
void release_context()
{
m_ward_context.reset();
}
boost::shared_ptr<context> get_context()
{
return m_ward_context;
}
class context_dependent : public explicit_context_dependent
{
private:
boost::shared_ptr<context> m_ward_context;
public:
context_dependent()
{ acquire_context(); }
};
class scoped_context_activation
{
private:
boost::shared_ptr<context> m_context;
bool m_did_switch;
public:
scoped_context_activation(boost::shared_ptr<context> ctx)
: m_context(ctx)
{
m_did_switch = context::current_context() != m_context;
if (m_did_switch)
{
#if CUDA_VERSION >= 2000
context_push(m_context);
#else
throw cuda::error("scoped_context_activation", CUDA_ERROR_INVALID_CONTEXT,
"not available in CUDA < 2.0");
#endif
}
~scoped_context_activation()
#if CUDA_VERSION >= 2000
if (m_did_switch)
m_context->pop();
#endif
// streams ------------------------------------------------------------------
class stream : public boost::noncopyable, public context_dependent
{
private:
CUstream m_stream;
public:
stream(unsigned int flags=0)
{ CUDAPP_CALL_GUARDED(cuStreamCreate, (&m_stream, flags)); }
~stream()
{
scoped_context_activation ca(get_context());
CUDAPP_CALL_GUARDED(cuStreamDestroy, (m_stream));
}
void synchronize()
{ CUDAPP_CALL_GUARDED_THREADED(cuStreamSynchronize, (m_stream)); }
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CUstream data() const
{ return m_stream; }
bool is_done() const
{
#ifdef TRACE_CUDA
std::cerr << "cuStreamQuery" << std::endl;
#endif
CUresult result = cuStreamQuery(m_stream);
switch (result)
{
case CUDA_SUCCESS:
return true;
case CUDA_ERROR_NOT_READY:
return false;
default:
throw error("cuStreamQuery", result);
}
}
};
// arrays -------------------------------------------------------------------
class array : public boost::noncopyable, public context_dependent
{
private:
CUarray m_array;
bool m_managed;
public:
array(const CUDA_ARRAY_DESCRIPTOR &descr)
{ CUDAPP_CALL_GUARDED(cuArrayCreate, (&m_array, &descr)); }
#if CUDA_VERSION >= 2000
array(const CUDA_ARRAY3D_DESCRIPTOR &descr)
{ CUDAPP_CALL_GUARDED(cuArray3DCreate, (&m_array, &descr)); }
#endif
array(CUarray ary, bool managed)
{ }
~array()
{
if (m_managed)
{
scoped_context_activation ca(get_context());
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CUDAPP_CALL_GUARDED(cuArrayDestroy, (m_array));
}
}
CUDA_ARRAY_DESCRIPTOR get_descriptor()
{
CUDA_ARRAY_DESCRIPTOR result;
CUDAPP_CALL_GUARDED(cuArrayGetDescriptor, (&result, m_array));
return result;
}
#if CUDA_VERSION >= 2000
CUDA_ARRAY3D_DESCRIPTOR get_descriptor_3d()
{
CUDA_ARRAY3D_DESCRIPTOR result;
CUDAPP_CALL_GUARDED(cuArray3DGetDescriptor, (&result, m_array));
return result;
}
#endif
CUarray data() const
{ return m_array; }
};
// texture reference --------------------------------------------------------
class module;
class texture_reference : public boost::noncopyable
{
private:
CUtexref m_texref;
bool m_managed;
// life support for array and module
boost::shared_ptr<array> m_array;
boost::shared_ptr<module> m_module;
public:
texture_reference()
: m_managed(true)
{ CUDAPP_CALL_GUARDED(cuTexRefCreate, (&m_texref)); }
texture_reference(CUtexref tr, bool managed)
: m_texref(tr), m_managed(managed)
{ }
~texture_reference()
{
if (m_managed)
{
CUDAPP_CALL_GUARDED(cuTexRefDestroy, (m_texref));
}
}
void set_module(boost::shared_ptr<module> mod)
{ m_module = mod; }
CUtexref data() const
{ return m_texref; }
void set_array(boost::shared_ptr<array> ary)
{
CUDAPP_CALL_GUARDED(cuTexRefSetArray, (m_texref,
ary->data(), CU_TRSA_OVERRIDE_FORMAT));
m_array = ary;
}
unsigned int set_address(CUdeviceptr dptr, unsigned int bytes)
{
unsigned int byte_offset;
CUDAPP_CALL_GUARDED(cuTexRefSetAddress, (&byte_offset,
m_texref, dptr, bytes));
m_array.reset();
return byte_offset;
}
void set_format(CUarray_format fmt, int num_packed_components)
{ CUDAPP_CALL_GUARDED(cuTexRefSetFormat, (m_texref, fmt, num_packed_components)); }
void set_address_mode(int dim, CUaddress_mode am)
{ CUDAPP_CALL_GUARDED(cuTexRefSetAddressMode, (m_texref, dim, am)); }
void set_filter_mode(CUfilter_mode fm)
{ CUDAPP_CALL_GUARDED(cuTexRefSetFilterMode, (m_texref, fm)); }
void set_flags(unsigned int flags)
{ CUDAPP_CALL_GUARDED(cuTexRefSetFlags, (m_texref, flags)); }
CUdeviceptr get_address()
{
CUdeviceptr result;
CUDAPP_CALL_GUARDED(cuTexRefGetAddress, (&result, m_texref));
return result;
}
array *get_array()
{
CUarray result;
CUDAPP_CALL_GUARDED(cuTexRefGetArray, (&result, m_texref));
return new array(result, false);
}
CUaddress_mode get_address_mode(int dim)
{
CUaddress_mode result;
CUDAPP_CALL_GUARDED(cuTexRefGetAddressMode, (&result, m_texref, dim));
return result;
}
CUfilter_mode get_filter_mode()
{
CUfilter_mode result;
CUDAPP_CALL_GUARDED(cuTexRefGetFilterMode, (&result, m_texref));
return result;
}
#if CUDA_VERSION >= 2000
py::tuple get_format()
{
CUarray_format fmt;
int num_channels;
CUDAPP_CALL_GUARDED(cuTexRefGetFormat, (&fmt, &num_channels, m_texref));
return py::make_tuple(fmt, num_channels);
}
#endif
unsigned int get_flags()
{
unsigned int result;
CUDAPP_CALL_GUARDED(cuTexRefGetFlags, (&result, m_texref));
return result;
}
};
// module -------------------------------------------------------------------
class function;
class module : public boost::noncopyable, public context_dependent
{
private:
CUmodule m_module;
public:
module(CUmodule mod)
{ }
~module()
{
scoped_context_activation ca(get_context());
CUDAPP_CALL_GUARDED(cuModuleUnload, (m_module));
}
CUmodule data() const
{ return m_module; }
function get_function(const char *name);
py::tuple get_global(const char *name)
{
CUdeviceptr devptr;
unsigned int bytes;
CUDAPP_CALL_GUARDED(cuModuleGetGlobal, (&devptr, &bytes, m_module, name));
return py::make_tuple(devptr, bytes);
}
};
module *module_from_file(const char *filename)
{
CUmodule mod;
CUDAPP_CALL_GUARDED(cuModuleLoad, (&mod, filename));
return new module(mod);
}
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texture_reference *module_get_texref(boost::shared_ptr<module> mod, const char *name)
{
CUtexref tr;
CUDAPP_CALL_GUARDED(cuModuleGetTexRef, (&tr, mod->data(), name));
std::auto_ptr<texture_reference> result(
new texture_reference(tr, false));
result->set_module(mod);
return result.release();
}
// function -----------------------------------------------------------------
class function
{
private:
CUfunction m_function;
public:
function(CUfunction func)
: m_function(func)
{ }
void set_block_shape(int x, int y, int z)
{ CUDAPP_CALL_GUARDED(cuFuncSetBlockShape, (m_function, x, y, z)); }
void set_shared_size(unsigned int bytes)
{ CUDAPP_CALL_GUARDED(cuFuncSetSharedSize, (m_function, bytes)); }
void param_set_size(unsigned int bytes)
{ CUDAPP_CALL_GUARDED(cuParamSetSize, (m_function, bytes)); }
void param_set(int offset, unsigned int value)
{ CUDAPP_CALL_GUARDED(cuParamSeti, (m_function, offset, value)); }
void param_set(int offset, float value)
{ CUDAPP_CALL_GUARDED(cuParamSetf, (m_function, offset, value)); }
void param_setv(int offset, void *buf, unsigned long len)
{
CUDAPP_CALL_GUARDED(cuParamSetv, (m_function, offset, buf, len));
}
void param_set_texref(const texture_reference &tr)
{
CUDAPP_CALL_GUARDED(cuParamSetTexRef, (m_function,
CU_PARAM_TR_DEFAULT, tr.data()));
}
void launch()
{ CUDAPP_CALL_GUARDED_THREADED(cuLaunch, (m_function)); }
void launch_grid(int grid_width, int grid_height)
{ CUDAPP_CALL_GUARDED_THREADED(cuLaunchGrid, (m_function, grid_width, grid_height)); }
void launch_grid_async(int grid_width, int grid_height, const stream &s)
{ CUDAPP_CALL_GUARDED_THREADED(cuLaunchGridAsync, (m_function, grid_width, grid_height, s.data())); }
function module::get_function(const char *name)
{
CUfunction func;
CUDAPP_CALL_GUARDED(cuModuleGetFunction, (&func, m_module, name));
return function(func);
}
// device memory ------------------------------------------------------------
inline
py::tuple mem_get_info()
{
unsigned int free, total;
CUDAPP_CALL_GUARDED(cuMemGetInfo, (&free, &total));
return py::make_tuple(free, total);
}
inline
CUdeviceptr mem_alloc(unsigned long bytes)
{
CUdeviceptr devptr;
CUDAPP_CALL_GUARDED(cuMemAlloc, (&devptr, bytes));
return devptr;
}
inline
void mem_free(CUdeviceptr devptr)
{
CUDAPP_CALL_GUARDED(cuMemFree, (devptr));
}
class device_allocation : public boost::noncopyable, public context_dependent
CUdeviceptr m_devptr;
public:
device_allocation(CUdeviceptr devptr)
scoped_context_activation ca(get_context());
release_context();
m_valid = false;
}
else
throw cuda::error("device_allocation::free", CUDA_ERROR_INVALID_HANDLE);
}
~device_allocation()
{
{ return m_devptr; }
};
inline
device_allocation *make_device_allocation(unsigned long bytes)
inline unsigned int mem_alloc_pitch(
std::auto_ptr<device_allocation> &da,
unsigned int width, unsigned int height, unsigned int access_size)
{
CUdeviceptr devptr;
unsigned int pitch;
CUDAPP_CALL_GUARDED(cuMemAllocPitch, (&devptr, &pitch, width, height, access_size));
da = std::auto_ptr<device_allocation>(new device_allocation(devptr));
return pitch;
py::tuple mem_get_address_range(CUdeviceptr ptr)
{
CUdeviceptr base;
unsigned int size;
CUDAPP_CALL_GUARDED(cuMemGetAddressRange, (&base, &size, ptr));
return py::make_tuple(base, size);
}
void memcpy_dtoa(array const &ary, unsigned int index, CUdeviceptr src, unsigned int len)
{ CUDAPP_CALL_GUARDED_THREADED(cuMemcpyDtoA, (ary.data(), index, src, len)); }
void memcpy_atod(CUdeviceptr dst, array const &ary, unsigned int index, unsigned int len)
{ CUDAPP_CALL_GUARDED_THREADED(cuMemcpyAtoD, (dst, ary.data(), index, len)); }
void memcpy_atoa(
array const &dst, unsigned int dst_index,
array const &src, unsigned int src_index,
unsigned int len)
{ CUDAPP_CALL_GUARDED_THREADED(cuMemcpyAtoA, (dst.data(), dst_index, src.data(), src_index, len)); }
// structured memcpy --------------------------------------------------------
#if PY_VERSION_HEX >= 0x02050000
typedef Py_ssize_t PYCUDA_BUFFER_SIZE_T;
#else
typedef int PYCUDA_BUFFER_SIZE_T;
#endif
#define MEMCPY_SETTERS \
void set_src_host(py::object buf_py) \
{ \
srcMemoryType = CU_MEMORYTYPE_HOST; \
PYCUDA_BUFFER_SIZE_T len; \
if (PyObject_AsReadBuffer(buf_py.ptr(), &srcHost, &len)) \
throw py::error_already_set(); \
} \
\
void set_src_array(array const &ary) \
{ \
srcMemoryType = CU_MEMORYTYPE_ARRAY; \
srcArray = ary.data(); \
} \
\
void set_src_device(CUdeviceptr devptr) \
{ \
srcMemoryType = CU_MEMORYTYPE_DEVICE; \
srcDevice = devptr; \
} \
\
void set_dst_host(py::object buf_py) \
{ \
dstMemoryType = CU_MEMORYTYPE_HOST; \
PYCUDA_BUFFER_SIZE_T len; \
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if (PyObject_AsWriteBuffer(buf_py.ptr(), &dstHost, &len)) \
throw py::error_already_set(); \
} \
\
void set_dst_array(array const &ary) \
{ \
dstMemoryType = CU_MEMORYTYPE_ARRAY; \
dstArray = ary.data(); \
} \
\
void set_dst_device(CUdeviceptr devptr) \
{ \
dstMemoryType = CU_MEMORYTYPE_DEVICE; \
dstDevice = devptr; \
}
struct memcpy_2d : public CUDA_MEMCPY2D
{
memcpy_2d()
{
srcXInBytes = 0;
srcY = 0;
dstXInBytes = 0;
dstY = 0;
}
MEMCPY_SETTERS;
void execute(bool aligned) const
{
if (aligned)
{ CUDAPP_CALL_GUARDED_THREADED(cuMemcpy2D, (this)); }
{ CUDAPP_CALL_GUARDED_THREADED(cuMemcpy2DUnaligned, (this)); }
}
void execute_async(const stream &s) const
{ CUDAPP_CALL_GUARDED_THREADED(cuMemcpy2DAsync, (this, s.data())); }
};
#if CUDA_VERSION >= 2000
struct memcpy_3d : public CUDA_MEMCPY3D
{
memcpy_3d()
{
reserved0 = 0;
reserved1 = 0;
srcXInBytes = 0;
srcY = 0;
srcZ = 0;
dstXInBytes = 0;
dstY = 0;
dstZ = 0;
}
MEMCPY_SETTERS;
void execute() const
{
CUDAPP_CALL_GUARDED_THREADED(cuMemcpy3D, (this));
}
void execute_async(const stream &s) const
{ CUDAPP_CALL_GUARDED_THREADED(cuMemcpy3DAsync, (this, s.data())); }
};
#endif
// host memory --------------------------------------------------------------
struct host_allocation : public boost::noncopyable
{
private:
void *m_data;
public:
host_allocation(unsigned bytesize)
: m_data(0)