{"id":31476063,"url":"https://github.com/zonca/python_hpc_2025","last_synced_at":"2025-10-02T00:51:11.299Z","repository":{"id":313946983,"uuid":"1053553408","full_name":"zonca/python_hpc_2025","owner":"zonca","description":null,"archived":false,"fork":false,"pushed_at":"2025-09-09T17:33:35.000Z","size":47,"stargazers_count":10,"open_issues_count":0,"forks_count":2,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-09-09T19:05:45.171Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/zonca.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-09-09T15:52:35.000Z","updated_at":"2025-09-09T18:36:52.000Z","dependencies_parsed_at":"2025-09-09T19:05:55.872Z","dependency_job_id":"47b97fb1-4758-46fe-ac7f-85d7120c9086","html_url":"https://github.com/zonca/python_hpc_2025","commit_stats":null,"previous_names":["zonca/python_hpc_2025"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/zonca/python_hpc_2025","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zonca%2Fpython_hpc_2025","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zonca%2Fpython_hpc_2025/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zonca%2Fpython_hpc_2025/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zonca%2Fpython_hpc_2025/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/zonca","download_url":"https://codeload.github.com/zonca/python_hpc_2025/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zonca%2Fpython_hpc_2025/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":277936834,"owners_count":25902302,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-01T02:00:09.286Z","response_time":88,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-10-02T00:51:10.260Z","updated_at":"2025-10-02T00:51:11.294Z","avatar_url":"https://github.com/zonca.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Python for HPC\n\n**Summary**: In this session we will introduce 2 key technologies in the Python ecosystem that provide significant benefits for scientific applications run in supercomputing environments. Previous Python experience is recommended but not required. \n* (1) First, we will learn how to speed up Python code compiling it on-the-fly with numba\n* (2) Then we will introduce the threads, processes and the Global Interpreter lock and we will leverage first numba then dask to use all available cores on a machine\n* (3) Finally we will distribute computations across multiple nodes launching dask workers on a separate Expanse job.\n\n**Presented by:** [Andrea Zonca](https://www.sdsc.edu/research/researcher_spotlight/zonca_andrea.html), Lead of the Scientific Computing Applications Group. Our purpose is to help US scientists use high-performance computing and AI resources effectively, including supercomputers not at SDSC. You can find my email and contact information on my profile page.\n\n## Repository Structure\n\nThis repository is organized into several modules, each focusing on a specific aspect of Python for HPC:\n\n*   **0_python_condaenv_scratch**: Contains scripts and examples for managing and deploying Python Conda environments on HPC clusters, specifically demonstrating staging to local scratch space for improved performance.\n*   **1_python_singularity**: Provides guidance and scripts for using Singularity to run Docker containers on HPC systems like Expanse, including pulling images and launching containers with Galyleo.\n*   **2_ai_code_assist**: Offers an overview of setting up and utilizing AI code assistants for Python development, with a focus on VS Code with GitHub Copilot and the Gemini CLI.\n*   **3_threads_vs_processes**: Explores the concepts of threads, processes, and the Global Interpreter Lock (GIL) in Python, likely through an interactive notebook.\n*   **4_numba**: Features examples and notebooks demonstrating how to use Numba for speeding up Python code, including basics, NumPy integration, and threading.\n*   **5_dask**: Contains notebooks and examples illustrating the use of Dask for parallel and distributed computing, covering Dask graphs, delayed computations, and distributed arrays.\n*   **dask_slurm**: Includes scripts for launching Dask schedulers and workers on SLURM-managed HPC clusters, enabling distributed Dask computations across multiple nodes.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzonca%2Fpython_hpc_2025","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzonca%2Fpython_hpc_2025","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzonca%2Fpython_hpc_2025/lists"}