rmm (top-level)#

class rmm.DeviceBuffer#

Bases: object

Attributes:

nbytes: Gets the size of the buffer in bytes.
ptr: Gets a pointer to the underlying data.
size: Gets the size of the buffer in bytes.

Methods

`capacity`(self)
`copy`(self)	Returns a copy of this `DeviceBuffer`.
`copy_from_device`(self, cuda_ary, ...)	Copy from a buffer on host to `self`
`copy_from_host`(self, ary, ...)	Copy from a buffer on host to `self`
`copy_to_host`(self[, ary])	Copy from a `DeviceBuffer` to a buffer on host.
`prefetch`(self[, device, stream])	Prefetch buffer data to the specified device on the specified stream.
`reserve`(self, size_t new_capacity, ...)
`resize`(self, size_t new_size, ...)
`to_device`(const unsigned char[, ...)	Calls `to_device` function on arguments provided.
`tobytes`(self, Stream stream=DEFAULT_STREAM)

capacity(self) → size_t#

copy(self)#

Returns a copy of this DeviceBuffer.

Returns:

DeviceBuffer: A deep copy of this DeviceBuffer

Examples

>>> import rmm
>>> db = rmm.DeviceBuffer.to_device(b"abc")
>>> db_copy = db.copy()
>>> db.copy_to_host()
array([97, 98, 99], dtype=uint8)
>>> db_copy.copy_to_host()
array([97, 98, 99], dtype=uint8)
>>> assert db is not db_copy
>>> assert db.ptr != db_copy.ptr

copy_from_device(self, cuda_ary, Stream stream=DEFAULT_STREAM)#

Copy from a buffer on host to self

Parameters:

cuda_ary: Object to copy from that has __cuda_array_interface__
streamoptional: CUDA stream to use for copying, defaults to the default stream

Examples

>>> import rmm
>>> db = rmm.DeviceBuffer(size=5)
>>> db2 = rmm.DeviceBuffer.to_device(b"abc")
>>> db.copy_from_device(db2)
>>> hb = db.copy_to_host()
>>> print(hb)
array([97, 98, 99,  0,  0], dtype=uint8)

copy_from_host(self, ary, Stream stream=DEFAULT_STREAM)#

Copy from a buffer on host to self

Parameters:

ary: bytes-like buffer to copy from
streamoptional: CUDA stream to use for copying, defaults to the default stream

Examples

>>> import rmm
>>> db = rmm.DeviceBuffer(size=10)
>>> hb = b"abcdef"
>>> db.copy_from_host(hb)
>>> hb = db.copy_to_host()
>>> print(hb)
array([97, 98, 99,  0,  0,  0,  0,  0,  0,  0], dtype=uint8)

copy_to_host(self, ary=None, Stream stream=DEFAULT_STREAM)#

Copy from a DeviceBuffer to a buffer on host.

Parameters:

ary: bytes-like buffer to write into
streamoptional: CUDA stream to use for copying, defaults to the default stream

Examples

>>> import rmm
>>> db = rmm.DeviceBuffer.to_device(b"abc")
>>> hb = bytearray(db.nbytes)
>>> db.copy_to_host(hb)
>>> print(hb)
bytearray(b'abc')
>>> hb = db.copy_to_host()
>>> print(hb)
bytearray(b'abc')

nbytes#: Gets the size of the buffer in bytes.

prefetch(self, device=None, stream=None)#

Prefetch buffer data to the specified device on the specified stream.

Assumes the storage for this DeviceBuffer is CUDA managed memory (unified memory). If it is not, this function is a no-op.

Parameters:

deviceoptional: The CUDA device to which to prefetch the memory for this buffer. Defaults to the current CUDA device. To prefetch to the CPU, pass cudaCpuDeviceId as the device.
streamoptional: CUDA stream to use for prefetching. Defaults to self.stream

ptr#: Gets a pointer to the underlying data.

reserve(self, size_t new_capacity, Stream stream=DEFAULT_STREAM) → void#

resize(self, size_t new_size, Stream stream=DEFAULT_STREAM) → void#

size#: Gets the size of the buffer in bytes.

static to_device(const unsigned char[::1] b, Stream stream=DEFAULT_STREAM)#: Calls to_device function on arguments provided.

tobytes(self, Stream stream=DEFAULT_STREAM) → bytes#

exception rmm.RMMError(errcode, msg)#: Bases: Exception

rmm.disable_logging()#: Disable logging if it was enabled previously using rmm.reinitialize() or rmm.enable_logging().

rmm.enable_logging(log_file_name=None)#

Enable logging of runtime events for all devices.

Parameters:

log_file_namestr, optional: Name of the log file. If not specified, the environment variable RMM_LOG_FILE is used. A ValueError is thrown if neither is available. A separate log file is produced for each device, and the suffix ".dev{id}" is automatically added to the log file name.

Notes

Note that if you use the environment variable CUDA_VISIBLE_DEVICES with logging enabled, the suffix may not be what you expect. For example, if you set CUDA_VISIBLE_DEVICES=1, the log file produced will still have suffix 0. Similarly, if you set CUDA_VISIBLE_DEVICES=1,0 and use devices 0 and 1, the log file with suffix 0 will correspond to the GPU with device ID 1. Use rmm.get_log_filenames() to get the log file names corresponding to each device.

rmm.flush_logger()#

Flush the debug logger. This will cause any buffered log messages to be written to the log file.

Debug logging prints messages to a log file. See Debug Logging for more information.

See also

set_flush_level: Set the flush level for the debug logger.
get_flush_level: Get the current debug logging flush level.

Examples

>>> import rmm
>>> rmm.flush_logger() # flush the logger

rmm.get_flush_level()#

Get the current debug logging flush level for the RMM logger. Messages of this level or higher will automatically flush to the file.

Debug logging prints messages to a log file. See Debug Logging for more information.

Returns:

logging_level: The current flush level, an instance of the logging_level enum.

See also

set_flush_level: Set the flush level for the logger.
flush_logger: Flush the logger.

Examples

>>> import rmm
>>> rmm.flush_level() # get current flush level
<logging_level.INFO: 2>

rmm.get_log_filenames()#

Returns the log filename (or None if not writing logs) for each device in use.

Examples

>>> import rmm
>>> rmm.reinitialize(devices=[0, 1], logging=True, log_file_name="rmm.log")
>>> rmm.get_log_filenames()
{0: '/home/user/workspace/rapids/rmm/python/rmm.dev0.log',
 1: '/home/user/workspace/rapids/rmm/python/rmm.dev1.log'}

rmm.get_logging_level()#

Get the current debug logging level.

Debug logging prints messages to a log file. See Debug Logging for more information.

Returns:

levellogging_level: The current debug logging level, an instance of the logging_level enum.

See also

set_logging_level: Set the debug logging level.

Examples

>>> import rmm
>>> rmm.get_logging_level() # get current logging level
<logging_level.INFO: 2>

rmm.is_initialized()#: Returns True if RMM has been initialized, False otherwise.

class rmm.level_enum(*values)#

Bases: IntEnum

Attributes:

denominator: the denominator of a rational number in lowest terms
imag: the imaginary part of a complex number
numerator: the numerator of a rational number in lowest terms
real: the real part of a complex number

Methods

`as_integer_ratio`(/)	Return a pair of integers, whose ratio is equal to the original int.
`bit_count`(/)	Number of ones in the binary representation of the absolute value of self.
`bit_length`(/)	Number of bits necessary to represent self in binary.
`conjugate`(/)	Returns self, the complex conjugate of any int.
`from_bytes`(/, bytes[, byteorder, signed])	Return the integer represented by the given array of bytes.
`is_integer`(/)	Returns True.
`to_bytes`(/[, length, byteorder, signed])	Return an array of bytes representing an integer.

critical = 5#

debug = 1#

error = 4#

info = 2#

n_levels = 7#

off = 6#

trace = 0#

warn = 3#

rmm.register_reinitialize_hook(func, *args, **kwargs)#

Add a function to the list of functions (“hooks”) that will be called before reinitialize().

A user or library may register hooks to perform any necessary cleanup before RMM is reinitialized. For example, a library with an internal cache of objects that use device memory allocated by RMM can register a hook to release those references before RMM is reinitialized, thus ensuring that the relevant device memory resource can be deallocated.

Hooks are called in the reverse order they are registered. This is useful, for example, when a library registers multiple hooks and needs them to run in a specific order for cleanup to be safe. Hooks cannot rely on being registered in a particular order relative to hooks registered by other packages, since that is determined by package import ordering.

Parameters:

funccallable: Function to be called before reinitialize()
args, kwargs: Positional and keyword arguments to be passed to func

rmm.reinitialize(pool_allocator=False, managed_memory=False, initial_pool_size=None, maximum_pool_size=None, devices=0, logging=False, log_file_name=None)#

Finalizes and then initializes RMM using the options passed. Using memory from a previous initialization of RMM is undefined behavior and should be avoided.

Parameters:

pool_allocatorbool, default False: If True, use a pool allocation strategy which can greatly improve performance.
managed_memorybool, default False: If True, use managed memory for device memory allocation
initial_pool_sizeint | str, default None: When pool_allocator is True, this indicates the initial pool size in bytes. By default, 1/2 of the total GPU memory is used. When pool_allocator is False, this argument is ignored if provided. A string argument is parsed using parse_bytes.
maximum_pool_sizeint | str, default None: When pool_allocator is True, this indicates the maximum pool size in bytes. By default, the total available memory on the GPU is used. When pool_allocator is False, this argument is ignored if provided. A string argument is parsed using parse_bytes.
devicesint or List[int], default 0: GPU device IDs to register. By default registers only GPU 0.
loggingbool, default False: If True, enable run-time logging of all memory events (alloc, free, realloc). This has a significant performance impact.
log_file_namestr: Name of the log file. If not specified, the environment variable RMM_LOG_FILE is used. A ValueError is thrown if neither is available. A separate log file is produced for each device, and the suffix “.dev{id}” is automatically added to the log file name.

Notes

Note that if you use the environment variable CUDA_VISIBLE_DEVICES with logging enabled, the suffix may not be what you expect. For example, if you set CUDA_VISIBLE_DEVICES=1, the log file produced will still have suffix 0. Similarly, if you set CUDA_VISIBLE_DEVICES=1,0 and use devices 0 and 1, the log file with suffix 0 will correspond to the GPU with device ID 1. Use rmm.get_log_filenames() to get the log file names corresponding to each device.

rmm.set_flush_level(level)#

Set the flush level for the debug logger. Messages of this level or higher will automatically flush to the file.

Debug logging prints messages to a log file. See Debug Logging for more information.

Parameters:

levellogging_level: The debug logging level. Valid values are instances of the logging_level enum.

Raises:

TypeError: If the logging level is not an instance of the logging_level enum.

See also

get_flush_level: Get the current debug logging flush level.
flush_logger: Flush the logger.

Examples

>>> import rmm
>>> rmm.flush_on(rmm.logging_level.WARN) # set flush level to warn

rmm.set_logging_level(level)#

Set the debug logging level.

Debug logging prints messages to a log file. See Debug Logging for more information.

Parameters:

levellogging_level: The debug logging level. Valid values are instances of the logging_level enum.

Raises:

TypeError: If the logging level is not an instance of the logging_level enum.

See also

get_logging_level: Get the current debug logging level.

Examples

>>> import rmm
>>> rmm.set_logging_level(rmm.logging_level.WARN) # set logging level to warn

rmm.should_log(level)#

Check if a message at the given level would be logged.

A message at the given level would be logged if the current debug logging level is set to a level that is at least as verbose than the given level, and the RMM module is compiled for a logging level at least as verbose. If these conditions are not both met, this function will return false.

Debug logging prints messages to a log file. See Debug Logging for more information.

Parameters:

levellogging_level: The debug logging level. Valid values are instances of the logging_level enum.

Returns:

should_logbool: True if a message at the given level would be logged, False otherwise.

Raises:

TypeError: If the logging level is not an instance of the logging_level enum.

rmm.unregister_reinitialize_hook(func)#

Remove func from list of hooks that will be called before reinitialize().

If func was registered more than once, every instance of it will be removed from the list of hooks.

rmm (top-level)#

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