{"id":21181951,"url":"https://github.com/argonne-lcf/aiaccelerators-sc24-tutorial","last_synced_at":"2025-10-28T19:36:20.223Z","repository":{"id":255229158,"uuid":"848932438","full_name":"argonne-lcf/AIaccelerators-SC24-tutorial","owner":"argonne-lcf","description":"AI Accelerators-SC24-tutorial Repository","archived":false,"fork":false,"pushed_at":"2024-11-20T16:59:15.000Z","size":63951,"stargazers_count":4,"open_issues_count":0,"forks_count":2,"subscribers_count":7,"default_branch":"main","last_synced_at":"2025-01-12T16:38:50.521Z","etag":null,"topics":["accelerator","ai","argonne","cerebras","graphcore","groq","habana","sambanova"],"latest_commit_sha":null,"homepage":"https://sc24.conference-program.com/presentation/?id=tut111\u0026sess=sess413","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/argonne-lcf.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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}},"created_at":"2024-08-28T17:07:53.000Z","updated_at":"2024-12-16T13:14:21.000Z","dependencies_parsed_at":null,"dependency_job_id":"daca54c7-4040-4c6c-90f9-f3e948fe7dda","html_url":"https://github.com/argonne-lcf/AIaccelerators-SC24-tutorial","commit_stats":null,"previous_names":["argonne-lcf/aiaccelerators-sc24-tutorial"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/argonne-lcf%2FAIaccelerators-SC24-tutorial","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/argonne-lcf%2FAIaccelerators-SC24-tutorial/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/argonne-lcf%2FAIaccelerators-SC24-tutorial/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/argonne-lcf%2FAIaccelerators-SC24-tutorial/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/argonne-lcf","download_url":"https://codeload.github.com/argonne-lcf/AIaccelerators-SC24-tutorial/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":234948106,"owners_count":18911761,"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","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":["accelerator","ai","argonne","cerebras","graphcore","groq","habana","sambanova"],"created_at":"2024-11-20T17:53:21.139Z","updated_at":"2025-10-28T19:36:20.128Z","avatar_url":"https://github.com/argonne-lcf.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Programming Novel AI Accelerators for Scientific Computing\n\nScientific applications are increasingly adopting Artificial Intelligence (AI) techniques to advance science. There are specialized hardware accelerators designed and built to run AI applications efficiently. With a wide diversity in the hardware architectures and software stacks of these systems, it is challenging to understand the differences between these accelerators, their capabilities, programming approaches, and how they perform, particularly for scientific applications. \n\nIn this tutorial, we will cover an overview of the AI accelerators landscape focusing on SambaNova, Cerebras, Graphcore, Groq, and Habana systems along with architectural features and details of their software stacks. We will have hands-on exercises to help attendees understand how to program these systems by learning how to refactor codes and compile and run the models on these systems. The tutorial will provide the attendees with an understanding of the key capabilities of emerging AI accelerators and their performance implications for scientific applications\n\n\u003c!-- In this tutorial, we will cover an overview of the AI accelerators landscape with a focus on SambaNova, Cerebras, Graphcore, Groq, and Habana systems along with architectural features and details of their software stacks. We will have hands-on exercises that will help attendees understand how to program these systems by learning how to refactor codes written in standard AI framework implementations and compile and run the models on these systems. The tutorial will enable the attendees with an understanding of the key capabilities of emerging AI accelerators and their performance implications for scientific applications. --\u003e\n\n\n## Tutorial at SC24\n\n| Date      | 17 November 2024       |\n|-----------|------------------------|\n| Time      |  8:30am - 5pm EST      |\n| Location  |  B201                  |\n\n\n## Agenda\n\n|      Time (EST)       |                        Topic/ Speaker                                                              |\n|-----------------------|----------------------------------------------------------------------------------------------------|\n|    08.30 - 08.40 AM   |  Programming Novel AI Accelerators for Scientific Computing \u003cbr\u003e Murali Emani (ANL) \u003cbr\u003e [[Slides](./Slides/ALCF-AITestbed-SC24-tutorial.pdf)]        |\n|    08.40 - 09.10 AM   |  The Power of Wafer-Scale Systems \u003cbr\u003e Cerebras HPC Research and SDK Overview \u003cbr\u003e Leighton Wilson (Cerebras) \u003cbr\u003e [[Slides AI](./Slides/Sc24%20Cerebras%20AI%20Overview.pdf)]  [[Slides SDK](./Slides/SC24%20Cerebras%20SDK.pdf)]                                       |\n|    09.10 - 10.00 AM   |  Hands-on With Cerebras Systems \u003cbr\u003e Leighton Wilson (Cerebras), Varuni Sastry (ANL) \u003cbr\u003e [[Instructions](./Cerebras/)] | \n|    10.00 - 10.30 AM   |  Coffee Break | \n|    10.30 - 11.00 AM   |  Programming Intel Habana Gaudi 2 for Scientific Computing \u003cbr\u003e Buke Ao (Intel Habana) \u003cbr\u003e [[Slides](./Slides/SC24%20Intel%20Habana.pdf)]  |\n|    11.00 - 11.30 AM   |  Hands-on with Intel Habana Gaudi2 \u003cbr\u003e Buke Ao (Intel Habana) \u003cbr\u003e [[Instructions](./Habana/)]  |\n|    11.30 - 12.00 PM   |  GenAI Training and Inference at Scale with SambaNova Systems \u003cbr\u003e Petro Junior Milan (Sambanova) \u003cbr\u003e [[Slides](./Slides/SC24%20SambaNova.pdf)]  |\n|    12.00 - 01.30 PM   |  Lunch Break | \n|    01.30 - 02.00 PM   |  Hands-on with Sambanova Systems \u003cbr\u003e Petro Junior Milan (Sambanova), Varuni Sastry (ANL) \u003cbr\u003e [[Instructions](./Sambanova/)]  |\n|    02.00 - 02.30 PM   |  Groq’s approach to HW/SW Systems for LLM Inference \u003cbr\u003e Sanjif Shanmugavelu (Groq) \u003cbr\u003e [[Slides](./Slides/SC24%20Groq.pdf)]  |\n|    02.30 - 03.00 PM   |  Hands-on with Groq Systems \u003cbr\u003e Sanjif Shanmugavelu (Groq), Varuni Sastry (ANL) \u003cbr\u003e [[Instructions](./Groq/)]  |\n|    03.00 - 03.30 PM   |  Coffee Break | \n|    03.30 - 04.00 PM   |  Introduction to Graphcore's IPU and Programming model : Sid Raskar (ANL) \u003cbr\u003e [[Slides](./Slides/SC24%20Graphcore.pdf)]  |\n|    04.00 - 04.30 PM   |  Hands-on with Grapchore Systems \u003cbr\u003e Sid Raskar (ANL) \u003cbr\u003e [[Instructions](./Graphcore/)]  |\n\n\n\n\u003c!-- ## Instructions for Hands-On Session\n\n* [SambaNova](./SambaNova/README.md)                                    \n* [Graphcore](./Graphcore/README.md)  \n* [Cerebras](./Cerebras/README.md)    \n* [Groq](./Groq/README.md)        \n* [Habana](./Habana/README.md)       --\u003e\n\n\n## Request Account on AI Testbeds At ALCF\n\n* Request an [ALCF Computer User Account](https://accounts.alcf.anl.gov/accountRequest) if you do not currently have one\n* If you have an ALCF Account that is currently inactive, submit an [account reactivation](https://accounts.alcf.anl.gov/accountReactivate) request*.\n* If you have an active ALCF account, click [Join Project](https://accounts.alcf.anl.gov/joinProject) to submit a membership request. \n  \n  \u003c!-- Specify the following in your request: \n  Project Name: `aitestbed_tutorial` --\u003e\n\nContact accounts@alcf.anl.gov M-F 9am to 5pm CT. \nReach out to us on slack channel `#help-accounts` on [ALCF-AIAccelerator-tutorials](https://join.slack.com/t/alcf-aiacc-tutorials/shared_invite/zt-25yjc7tnm-AlqTNcWrbH0c1KVNEExTuw) Slack. \n\n\u003eSC24 Tutorial allocation will stay active till end of November 2024. \n\n### Director’s Discretionary Allocation Program\n\nTo gain access to AI Testbeds at ALCF after tutorial allocation expires apply for [Director’s Discretionary Allocation Program](https://www.alcf.anl.gov/science/directors-discretionary-allocation-program)\n\nThe ALCF Director’s Discretionary program provides “start up” awards to researchers working to achieve computational readiness for for a major allocation award.\n\n\n\n## Useful Links \n\n* [SC24 Tutorial Webpage](https://sc24.conference-program.com/presentation/?id=tut111\u0026sess=sess413)\n* [Github Tutorial Repository](https://github.com/argonne-lcf/AIaccelerators-SC24-tutorial)\n* [Overview of AI Testbeds at ALCF](https://www.alcf.anl.gov/alcf-ai-testbed)\n* [ALCF AI Testbed Documentation](https://www.alcf.anl.gov/support/ai-testbed-userdocs/)\n* [Director’s Discretionary Allocation Program](https://www.alcf.anl.gov/science/directors-discretionary-allocation-program)\n* [Join Slack Workspace](https://join.slack.com/t/alcf-aiacc-tutorials/shared_invite/zt-2uma9x2zm-PDm9dlnGZqtO~_DkANZwWA)\n\n##### Acknowledgements\n\nContributors: [Siddhisanket (Sid) Raskar](https://sraskar.github.io/), Varuni Sastry, Bill Arnold, [Murali Emani](https://memani1.github.io/). \n\n\u003e This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fargonne-lcf%2Faiaccelerators-sc24-tutorial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fargonne-lcf%2Faiaccelerators-sc24-tutorial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fargonne-lcf%2Faiaccelerators-sc24-tutorial/lists"}