[GitHub] [incubator-mxnet] stu1130 opened a new pull request #14887: [Dependency Update] CUDA10.1 Support

[GitBox <gi...@apache.org>]

stu1130 opened a new pull request #14887: [Dependency Update] CUDA10.1 Support
URL: https://github.com/apache/incubator-mxnet/pull/14887
 
 
   ## Description ##
   Upgrade the CUDA 10.1 with latest cuDNN **7.5.1** & NCCL **2.4.2**
   
   ## Checklist ##
   Run three models ResNet50 with ImageNet & LSTM with PTB & MLP with MNIST
   Performance shown below
   Environment: P3.16xlarge Deep Learning Base AMI
   Codebase: commit 1540a84f1eca937235c51b507ea716c614f40805
   I also applied the #14837 PR change
   The unit of thoughput is **samples/per second**
   Each throughput is calcuated by average of 5 runs
   ### ResNet ###
   **model**: Resnet50
   **dataset**: Imagenet
   **number of gpu**: 8
   **epochs**: 3 (only to test throughput)
   **preprocess command**: sudo pip install gluoncv==0.2.0b20180625
   **command**: python mxnet_benchmark/train_imagenet.py --use-rec --batch-size 128 --dtype float32 —num-data-workers 40 —num-epochs 3 —gpus 0,1,2,3,4,5,6,7 --lr 0.05 --last-gamma —mode symbolic —model resnet50_v1b —rec-train /home/ubuntu/data/train-passthrough.rec —rec-train-idx /home/ubuntu/data/train-passthrough.idx —rec-val /home/ubuntu/data/val-passthrough.rec —rec-val-idx /home/ubuntu/data/val-passthrough.idx
   **github repo**: https://github.com/rahul003/deep-learning-benchmark-mirror.git*
   
   |    |  CUDA10.1 cuDNN 7.5.1/NCCL 2.4.2     | CUDA 10 cuDNN 7.3.1/NCCL 2.3.4 | Perforamnce Difference|
   |:----------|:------------------------:|:--------------------:|:---------------------:|
   | Throughput | 2853.89469 | 2831.54405 | 0.789%  |
   
   
   ### LSTM ###
   **model**: LSTM
   **dataset**: PTB(Penn Treebank)
   **number of gpu**: 1
   **epochs**: 10
   **command**:
   python2 benchmark_driver.py --framework mxnet --task-name mkl_lstm_ptb_symbolic --num-gpus 1 --epochs 10 --metrics-suffix test --kvstore local
   python word_language_model/lstm_bucketing.py —num-hidden 650 —num-embed 650 —gpus 0 --epochs 10 --kv-store local
   
   |    |  CUDA10.1 cuDNN 7.5.1/NCCL 2.4.2     | CUDA 10 cuDNN 7.3.1/NCCL 2.3.4 | Perforamnce Difference|
   |:----------|:------------------------:|:--------------------:|:---------------------:|
   | Throughput | 1027.52625 | 847.98222(Performance Regression) | 21.173%  |
   
   **The CUDA 10 have a performance regression issue, please see #14725 to find more details.**
   
   ### MLP ###
   **model**: 3 dense layers with num_hidden=64 and relu as activation
   **dataset**: MNIST
   **number of gpu**: 1
   **epochs**: 10
   **command**:
   python2 benchmark_runner.py —framework mxnet —metrics-policy mlp —task-name mlp —metrics-suffix test —num-gpus 1 —command-to-execute 'python3 mlp.py' —data-set mnist
   
   |    |  CUDA10.1 cuDNN 7.5.1/NCCL 2.4.2     | CUDA 10 cuDNN 7.3.1/NCCL 2.3.4 | Perforamnce Difference|
   |:----------|:------------------------:|:--------------------:|:---------------------:|
   | Throughput | 4386.67838 | 4192.20685 | 4.639%  |
   
   ## Comments ##
   @szha @lanking520 @eric-haibin-lin 

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