Murali Emani (memani@anl.gov), Varuni Sastry (vsastry@anl.gov), Bill Arnold (arnoldw@anl.gov), Sid Raskar (sraskar@anl.gov), Venkat Vishwanath (venkat@anl.gov)
Scientific 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.
We will cover an overview of the AI accelerators landscape with a focus on SambaNova, Cerebras, Graphcore, and Groq 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.
To gain access to AI Testbeds at ALCF after tutorial allocation expires apply for Director’s Discretionary Allocation Program
The ALCF Director’s Discretionary program provides “start up” awards to researchers working to achieve computational readiness for for a major allocation award.
- Overview of AI Testbeds at ALCF
- ALCF AI Testbed Documentation
- Director’s Discretionary Allocation Program
- Slack Workspace
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.