[Doc] sampler readme update. (#581)

examples/mxnet/sampling/README.md

@@ -66,12 +66,14 @@ DGLBACKEND=mxnet python3 train.py --model graphsage_cv --batch-size 1000 --test-
 
 ### Run multi-processing training
 
-Run the graph store server that loads the reddit dataset with four workers.
+When training a GNN model with multiple processes, there are two steps.
+
+Step 1: run a graph store server separately that loads the reddit dataset with four workers.
 ```
 python3 examples/mxnet/sampling/run_store_server.py --dataset reddit --num-workers 4
 ```
 
-Run four workers to train GraphSage on the reddit dataset.
+Step 2: run four workers to train GraphSage on the reddit dataset.
 ```
-python3 ../incubator-mxnet/tools/launch.py -n 4 -s 1 --launcher local python3 multi_process_train.py --model graphsage_cv --batch-size 1000 --test-batch-size 5000 --n-epochs 1 --graph-name reddit --num-neighbors 1 --n-hidden 128 --dropout 0.2 --weight-decay 0
+python3 ../incubator-mxnet/tools/launch.py -n 4 -s 1 --launcher local python3 multi_process_train.py --model graphsage_cv --batch-size 2500 --test-batch-size 5000 --n-epochs 1 --graph-name reddit --num-neighbors 1 --n-hidden 128 --dropout 0.2 --weight-decay 0
 ```