[GitHub] [singa] chrishkchris opened a new pull request #564: SINGA-487 Asynchronous training algorithm with partial parameters synchronization

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chrishkchris opened a new pull request #564: SINGA-487 Asynchronous training algorithm with partial parameters synchronization
URL: https://github.com/apache/singa/pull/564
 
 
   In this PR, there are two things added:
   
   1. An experimental feature for distributed training is added in opt.py, which is referred as
   "Asynchronous training algorithm with partial parameters synchronization"
   
   2. The example codes using CIFAR-10 dataset on Resnet-50 to test the above algorithm (i.e. cifar10_multiprocess.py), as well as doing single GPU training (i.e. resnet_cifar10.py).
   
   ```
   ubuntu@ip-172-31-18-205:~/singa/examples/autograd$ python3 cifar10_multiprocess.py
   Starting Epoch 0:
   Training loss = 3731.784668, training accuracy = 0.222937
   Evaluation accuracy = 0.100761, Elapsed Time = 162.025833s
   Starting Epoch 1:
   Training loss = 3086.915039, training accuracy = 0.274960
   Evaluation accuracy = 0.199519, Elapsed Time = 162.342712s
   Starting Epoch 2:
   Training loss = 2764.083984, training accuracy = 0.341326
   Evaluation accuracy = 0.247997, Elapsed Time = 162.180337s
   
   ```

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