add README with directory structure and run instructions

Author: KWang1998

examples/MNIST/README.md

@@ -0,0 +1,46 @@
+# PnetCDF-python MNIST example
+
+This directory contains the description and run instructions for the MNIST example Python programs that utilize PnetCDF for file I/O and parallel training with MNIST data.
+
+## Directory Structure
+
+- **MNIST_data**: This folder contains a mini MNIST test dataset stored in a NetCDF file (`mnist_images_mini.nc`). The file includes:
+  - 60 training samples
+  - 12 testing samples
+
+- **MNIST_codes**: This folder contains the example MNIST training code. The example code is based on the [PyTorch MNIST example](https://github.com/pytorch/examples/tree/main/mnist) and uses `DistributedDataParallel` for parallel training.
+
+## Running the MNIST Example Program
+
+To run the MNIST example program, use the `mpiexec` command. The example below runs the program on 4 MPI processes.
+
+### Command:
+
+```sh
+mpiexec -n 4 python main.py
+```
+
+### Expected Output:
+
+When using 4 MPI processes, the output is expected to be similar to the following:
+
+```sh
+nprocs = 4  rank = 0  device = cpu  mpi_size = 4  mpi_rank = 0
+nprocs = 4  rank = 2  device = cpu  mpi_size = 4  mpi_rank = 2
+nprocs = 4  rank = 1  device = cpu  mpi_size = 4  mpi_rank = 1
+nprocs = 4  rank = 3  device = cpu  mpi_size = 4  mpi_rank = 3
+
+Train Epoch: 1  Average Loss: 2.288340
+Test set: Average loss: 2.7425, Accuracy: 0/12 (0%)
+
+Train Epoch: 2  Average Loss: 2.490800
+Test set: Average loss: 1.9361, Accuracy: 6/12 (50%)
+
+Train Epoch: 3  Average Loss: 2.216520
+Test set: Average loss: 1.8703, Accuracy: 7/12 (58%)
+```
+
+### Notes:
+- The test set accuracy may vary slightly depending on how the data is distributed across the MPI processes.
+- The accuracy and loss reported after each epoch are averaged across all MPI processes.
+