pyarrow.cuda.Context#

classpyarrow.cuda.Context(*args,**kwargs)#

Bases:_Weakrefable

CUDA driver context.

__init__()#

Create a CUDA driver context for a particular device.

If a CUDA context handle is passed, it is wrapped, otherwisea default CUDA context for the given device is requested.

Parameters:

device_numberint (default 0)

Specify the GPU device for which the CUDA driver context isrequested.

handleint, optional

Specify CUDA handle for a shared context that has been createdby another library.

Methods

__init__	Create a CUDA driver context for a particular device.
buffer_from_data(self, data, ...)	Create device buffer and initialize with data.
buffer_from_object(self, obj)	Create device buffer view of arbitrary object that references device accessible memory.
foreign_buffer(self, address, size[, base])	Create device buffer from address and size as a view.
from_numba([context])	Create a Context instance from a Numba CUDA context.
get_device_address(self, uintptr_t address)	Return the device address that is reachable from kernels running in the context
get_num_devices()	Return the number of GPU devices.
new_buffer(self, int64_t nbytes)	Return new device buffer.
open_ipc_buffer(self, ipc_handle)	Open existing CUDA IPC memory handle
synchronize(self)	Blocks until the device has completed all preceding requested tasks.
to_numba(self)	Convert Context to a Numba CUDA context.

Attributes

bytes_allocated	Return the number of allocated bytes.
device	The device instance associated with this context.
device_number	Return context device number.
handle	Return pointer to context handle.
memory_manager	The default memory manager tied to this context's device.

buffer_from_data(self,data,int64_toffset=0,int64_tsize=-1)#

Create device buffer and initialize with data.

Parameters:

data{CudaBuffer,HostBuffer,Buffer,array-like}

Specify data to be copied to device buffer.

offsetint

Specify the offset of input buffer for device databuffering. Default: 0.

sizeint

Specify the size of device buffer in bytes. Default: all(starting from input offset)

Returns:

cbufCudaBuffer

Device buffer with copied data.

buffer_from_object(self,obj)#

Create device buffer view of arbitrary object that referencesdevice accessible memory.

When the object contains a non-contiguous view of deviceaccessible memory then the returned device buffer will containcontiguous view of the memory, that is, including theintermediate data that is otherwise invisible to the inputobject.

Parameters:

obj{object,Buffer,HostBuffer,CudaBuffer, …}

Specify an object that holds (device or host) address thatcan be accessed from device. This includes objects withtypes defined in pyarrow.cuda as well as arbitrary objectsthat implement the CUDA array interface as defined by numba.

Returns:

cbufCudaBuffer

Device buffer as a view of device accessible memory.

bytes_allocated#

Return the number of allocated bytes.

device#

The device instance associated with this context.

Returns:

Device

device_number#

Return context device number.

foreign_buffer(self,address,size,base=None)#

Create device buffer from address and size as a view.

The caller is responsible for allocating and freeing thememory. Whenaddress==size==0 then a new zero-sized bufferis returned.

Parameters:

addressint

Specify the starting address of the buffer. The address canrefer to both device or host memory but it must beaccessible from device after mapping it withget_device_address method.

sizeint

Specify the size of device buffer in bytes.

base{None, object}

Specify object that owns the referenced memory.

Returns:

cbufCudaBuffer

Device buffer as a view of device reachable memory.

staticfrom_numba(context=None)#

Create a Context instance from a Numba CUDA context.

Parameters:

context{numba.cuda.cudadrv.driver.Context,None}

A Numba CUDA context instance.If None, the current Numba context is used.

Returns:

shared_contextpyarrow.cuda.Context

Context instance.

get_device_address(self,uintptr_taddress)#

Return the device address that is reachable from kernels running inthe context

Parameters:

addressint

Specify memory address value

Returns:

device_addressint

Device address accessible from device context

Notes

The device address is defined as a memory address accessibleby device. While it is often a device memory address but itcan be also a host memory address, for instance, when thememory is allocated as host memory (using cudaMallocHost orcudaHostAlloc) or as managed memory (using cudaMallocManaged)or the host memory is page-locked (using cudaHostRegister).

staticget_num_devices()#

Return the number of GPU devices.

handle#

Return pointer to context handle.

memory_manager#

The default memory manager tied to this context’s device.

Returns:

MemoryManager

new_buffer(self,int64_tnbytes)#

Return new device buffer.

Parameters:

nbytesint

Specify the number of bytes to be allocated.

Returns:

bufCudaBuffer

Allocated buffer.

open_ipc_buffer(self,ipc_handle)#

Open existing CUDA IPC memory handle

Parameters:

ipc_handleIpcMemHandle

Specify opaque pointer to CUipcMemHandle (driver API).

Returns:

bufCudaBuffer

referencing device buffer

synchronize(self)#

Blocks until the device has completed all preceding requestedtasks.

to_numba(self)#

Convert Context to a Numba CUDA context.

Returns:

contextnumba.cuda.cudadrv.driver.Context

Numba CUDA context instance.