Intel-oneAPI-CodeMaven

Environment set up for demo:

Step 1: Open the condaenvsetup.ipynb and activate Python 3(Intel oneAPI 2022.3) kernel
Step 2: Run through the cells one by one. "qsub" submits the job to do all the setup and "qstat" shows the job status. (all details related to devcloud job submission is in the Welcome.ipyb file)
Step 3: Once the job is finished, the setup should be completed.
Step 4: Now you will have stock-tensorflow kernel to run the demo for second exercise.

Running the notebooks:

Exercise 1: Basics of the oneDNN programming model.

Step 1: Open terminal and clone oneAPI samples
git clone https://github.com/oneapi-src/oneAPI-samples.git
Step 2: Browse the oneAPI-samples/Libraries/oneDNN/tutorials/
Step 3: Open the tutorial_getting_started.ipynb
Step 4: oneDNN has four different configuration, we will build and run with oneAPI DPC++ Compiler only.
Step 5: Run through each cell and while running cell for writing for build file remove the cmake parameters.
Step 6: Output showing "example passed on CPU" will appear if the oneDNN sample has been successfully compiled.

Exercise 2: Performance benifits with oneDNN optimization for Stock Tensorflow.

Step 1: Open terminal, and clone oneAPI samples
git clone https://github.com/oneapi-src/oneAPI-samples.git
Step 2: Browse the oneAPI-samples/AI-and-Analytics/Features-and-Functionality/IntelTensorFlow_ModelZoo_Inference_with_FP32_Int8/
Step 3: Open the ResNet50_Inference.ipynb
Step 4: First select stock-tensorflow kernel and add the following env variable [os.environ["TF_ENABLE_ONEDNN_OPTS"]='0'] to disable onednn and run through each cell of the notebook to get the average time and throughput.
Step 5: Follow step 4 but now with onednn on by changing the env variable [os.environ["TF_ENABLE_ONEDNN_OPTS"]='1'] and note the performance

Exercise 3: Understand oneMKL GEMM routine for matrix multiplication.

Step 1: Open terminal, and clone oneAPI samples
Step 2: Change directory to the oneAPI-samples/Libraries/oneMKL/matrix_mul_mkl
Step 3: Run make to build and run the sample.
Step 4: Output showing "Results are accurate" will appear if the sample has been successfully compiled and build.

Documentation Links:

Intel® Devcloud for oneAPI documentation https://devcloud.intel.com/oneapi/get_started/

Github link for Intel® oneAPI-samples https://github.com/oneapi-src/oneAPI-samples.git