Source code for dpctl._sycl_timer

#                      Data Parallel Control (dpctl)
# Copyright 2020-2024 Intel Corporation
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.

import timeit

from . import SyclQueue

__doc__ = "This module implements :class:`dpctl.SyclTimer`."

class HostDeviceDuration:
    def __init__(self, host_dt, device_dt):
        self._host_dt = host_dt
        self._device_dt = device_dt

    def __repr__(self):
        return f"(host_dt={self._host_dt}, device_dt={self._device_dt})"

    def __str__(self):
        return f"(host_dt={self._host_dt}, device_dt={self._device_dt})"

    def __iter__(self):
        yield from [self._host_dt, self._device_dt]

    def host_dt(self):
        return self._host_dt

    def device_dt(self):
        return self._device_dt

[docs]class SyclTimer: """ Context to measure device time and host wall-time of execution of commands submitted to :class:`dpctl.SyclQueue`. :Example: .. code-block:: python import dpctl # Create a default SyclQueue q = dpctl.SyclQueue(property="enable_profiling") # create the timer milliseconds_sc = 1e-3 timer = dpctl.SyclTimer(time_scale = milliseconds_sc) # use the timer with timer(queue=q): code_block1 # use the timer with timer(queue=q): code_block2 # retrieve elapsed times in milliseconds wall_dt, device_dt = timer.dt .. note:: The timer submits barriers to the queue at the entrance and the exit of the context and uses profiling information from events associated with these submissions to perform the timing. Thus :class:`dpctl.SyclTimer` requires the queue with ``"enable_profiling"`` property. In order to be able to collect the profiling information, the ``dt`` property ensures that both submitted barriers complete their execution and thus effectively synchronizes the queue. Args: host_timer (callable, optional): A callable such that host_timer() returns current host time in seconds. Default: :py:func:`timeit.default_timer`. time_scale (Union[int, float], optional): Ratio of the unit of time of interest and one second. Default: ``1``. """
[docs] def __init__(self, host_timer=timeit.default_timer, time_scale=1): """ Create new instance of :class:`.SyclTimer`. Args: host_timer (callable, optional) A function that takes no arguments and returns a value measuring time. Default: :meth:`timeit.default_timer`. time_scale (Union[int, float], optional): Scaling factor applied to durations measured by the host_timer. Default: ``1``. """ self.timer = host_timer self.time_scale = time_scale self.queue = None self.host_times = [] self.bracketing_events = []
def __call__(self, queue=None): if isinstance(queue, SyclQueue): if queue.has_enable_profiling: self.queue = queue else: raise ValueError( "The given queue was not created with the " "enable_profiling property" ) else: raise TypeError( "The passed queue must have type dpctl.SyclQueue, " f"got {type(queue)}" ) return self def __enter__(self): self._event_start = self.queue.submit_barrier() self._host_start = self.timer() return self def __exit__(self, *args): self.host_times.append((self._host_start, self.timer())) self.bracketing_events.append( (self._event_start, self.queue.submit_barrier()) ) del self._event_start del self._host_start @property def dt(self): """Returns a pair of elapsed times ``host_dt`` and ``device_dt``. The ``host_dt`` is the duration as measured by the host timer, while the ``device_dt`` is the duration as measured by the device timer and encoded in profiling events. Returns: HostDeviceDuration: Data class with ``host_dt`` and ``device_dt`` members which supports unpacking into a 2-tuple. :Example: .. code-block:: python import dpctl from dpctl import tensor q = dpctl.SyclQueue(property="enable_profiling") device = tensor.Device.create_device(q) timer = dpctl.SyclTimer() with timer(q): x = tensor.linspace(-4, 4, num=10**6, dtype="float32") e = tensor.exp(-0.5 * tensor.square(x)) s = tensor.sin(2.3 * x + 0.11) f = e * s host_dt, device_dt = timer.dt .. note:: Since different timers are used to measure host and device durations, one should not expect that ``host_dt`` is always strictly greater than ``device_dt``. Use tracing tools like ``onetrace``, or ``unitrace`` from `intel/pti-gpu <>`_ repository for more accurate measurements. """ for es, ef in self.bracketing_events: es.wait() ef.wait() host_dt = sum(tf - ts for ts, tf in self.host_times) * self.time_scale dev_dt = sum( ef.profiling_info_start - es.profiling_info_end for es, ef in self.bracketing_events ) * (1e-9 * self.time_scale) return HostDeviceDuration(host_dt, dev_dt)