DeepLearningExamples/TensorFlow2/LanguageModeling/ELECTRA/gpu_affinity.py
2020-10-26 12:19:47 +01:00

64 lines
1.9 KiB
Python

# Copyright (c) 2020 NVIDIA CORPORATION. All rights reserved.
#
# 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import math
import os
import pynvml
pynvml.nvmlInit()
def systemGetDriverVersion():
return pynvml.nvmlSystemGetDriverVersion()
def deviceGetCount():
return pynvml.nvmlDeviceGetCount()
class device:
# assume nvml returns list of 64 bit ints
_nvml_affinity_elements = math.ceil(os.cpu_count() / 64)
def __init__(self, device_idx):
super().__init__()
self.handle = pynvml.nvmlDeviceGetHandleByIndex(device_idx)
def getName(self):
return pynvml.nvmlDeviceGetName(self.handle)
def getCpuAffinity(self):
affinity_string = ''
for j in pynvml.nvmlDeviceGetCpuAffinity(
self.handle, device._nvml_affinity_elements
):
# assume nvml returns list of 64 bit ints
affinity_string = '{:064b}'.format(j) + affinity_string
affinity_list = [int(x) for x in affinity_string]
affinity_list.reverse() # so core 0 is in 0th element of list
return [i for i, e in enumerate(affinity_list) if e != 0]
def set_affinity(gpu_id=None):
if gpu_id is None:
gpu_id = int(os.getenv('LOCAL_RANK', 0))
dev = device(gpu_id)
os.sched_setaffinity(0, dev.getCpuAffinity())
# list of ints representing the logical cores this process is now affinitied with
return os.sched_getaffinity(0)