nudles edited a comment on issue #14: rearrange contents in dist-train.md URL: https://github.com/apache/singa-doc/pull/14#issuecomment-608989769 The [DIST](https://github.com/apache/singa/blob/master/examples/autograd/mnist_cnn.py#L153) variable can be inferred based on the num of gpus? for MPI, you do not need to pass `num_gpus` explicitly to `DistOpt`? but for multiprocessing, you need? The format of the docString is very good! Some arguments may need more explanations: 1. [nccl_id](https://github.com/apache/singa/blob/master/python/singa/opt.py#L191) is compulsory for multiprocessing? and should be none for MPI? 2. how about num_gpu and gpu_per_node? 3. give a concrete example for `rank_in_local` and `rank_in_global` In addition, we may need to introduce the implementation of distributed training code in SINGA at the end of this documentation. We have given the overview of the synchronous training algorithm at the beginning in this documentation. But how what is done at the Python side and C++ side is unknown. When NCCL and MPI APIs are called. This part is mainly for developers (not for end users). You can refer to the [tensor documentation](https://github.com/apache/singa-doc/blob/master/docs-site/docs/tensor.md) Thanks!
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