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Hello Otter team!
I have encounter an issue when installing the environments:
× python setup.py bdist_wheel did not run successfully.
│ exit code: 1
ERROR: Failed building wheel for hor…
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## Description
environment：
python 3.8
ubuntu 18.04
gcc 7.5 g++7.5
mxnet1.9(build from source)
openmpi 4.0
horovod 0.24
instructions
HOROVOD_WITHOUT_TENSORFLOW=1 HOROVOD_WITHOUT_PYTORC…
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https://github.com/apache/incubator-mxnet/tree/master/example/distributed_training-horovod
the examples as follow:
$ mpirun -np 8 \
-H server1:4,server2:4 \
-bind-to none -map-by slot \
…
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**Is your feature request related to a problem? Please describe.**
Slightly, both DALI and Horovod help decrease training time which has been a problem in the past. Theoretically those are not mutual…
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### 简介
horovod是支持pytorch,tensorflow,mxnet多机分布式训练的库，其底层机器间通讯依赖nccl或mpi，所以安装前通常需要先安装好nccl、openmpi，且至少安装了一种深度学习框架，譬如mxnet:
```shell
python3 -m pip install gluonnlp==0.10.0 mxnet-cu102mkl==1.6.0.post0…
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I have run the following command to test horovod pytorch frame,
the error occurs:
jovyan@560c5fd869da:~$ mpirun -np 1 -bind-to none -map-by slot -x NCCL_DEBUG=INFO -x LD_LIBRARY_PATH -x PATH -mca…
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running distributed training gives below issue,
1462.worker.1 | [2019-06-04T14:59:47Z] WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value …
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When the training crashes (e.g. GPU out-of-memory, or got inf/nan, or whatever), it often happens that the process (SGE job, Slurm job) is just hanging and not exiting.
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We are running distributed training using Horovod with NCCL 2.7.3, using 4 workers 8 ranks per worker. We observed that 1 rank out of 8 ranks is not running with zero CPU usage. Attached the NCCL debu…
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**Environment:**
1. Framework: Tensorflow
2. Framework version: 2.6.0
3. Horovod version: 0.27.0
4. MPI version:
5. CUDA version: 11.7
6. NCCL version: 2.17.1
7. Python version: 3.7.16
8. S…