- Maintains our primary shared resource for research computing, ManeFrame II (M2), in collaboration with OIT
- Provides research computing tools, support, and training to all faculty, staff, and students using research computing resources www.smu.edu/csc has documentation and news
- [email protected] or [email protected] for help
Date | Workshop |
---|---|
January 21 | M2 Introduction |
January 28 | Introduction to LAPACK and BLAS |
February 4 | Text Mining with Python on M2 (Lead by Dr. Eric Godat) |
February 11 | Using the New HPC Portal |
February 18 | Using GitHub |
February 25 | Writing Portable Accelerator Code with KOKKOS, RAJA, and OCCA |
March 3 | M2 Introduction |
March 10 | Introduction to Parallelization Using MPI |
March 17 | No Workshop Spring Break |
March 24 | Writing High Performance Python Code |
March 31 | Creating Portable Environments with Docker and Singularity |
April 7 | M2 Introduction |
April 14 | Introduction to Parallelization Using OpenMP and OpenACC |
April 21 | Profiling Applications on M2 |
April 28 | Improving Code Vectorization |
- Go to hpc.smu.edu.
- Sign in using your SMU ID and SMU password.
- Select "JupyterLab from the "Interactive Apps" drop-down menu.
- Select options required for your JupyterLab instance. These options are the same as those requested via a standard Slurm script on M2. For this tutorial: beginning with the "Partition" field the values should be: "htc", 4, 1, 2, 0, 6.
- Select "Launch" Wait for the job to start on M2. When the job starts a new button "Connect to JupyterLab" button will appear.
- Select "Connect to JupyterLab" The JupyterLab graphical interface will be presented and running on the M2 resource requested.
- From "Launcher" tab select "Terminal".
- Type
git clone https://github.com/SouthernMethodistUniversity/fast_python.git
and press "Enter" - In the file browser on the left double-click "Text_Mining_Python" and then double click "text_mining_python.ipynb"