9a.011.SBU - Foundational Workload Scheduling and Parallel Computing Stack for Tensor and Mathematical Operations for AI and Quantum Workloads

Project - Summary

This project is inactive.

  • Develop tensor computation on multi-GPU though technologies like slurm/docker swarm.
  • Develop notebook applications through multiple language bindings - Python/Julia/C++.
  • Create a shared, collaborative, efficient AI infrastructure, GPU cluster for ML and Quantum Simulation

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Arie Kaufman PI (631) 632-8441 Stony Brook University
Fnu Chetan Student N/A Stony Brook University
Xinye Bai Student (609) 401-1667 Stony Brook University
Ken Gladky Director of Operations N/A N/A Stony Brook University
Funded by: Zeblok

Project - Novelty of Approach

  • Involves research and evaluation of technologies to implement ML capabilities across a vast array of computational nodes and GPU
  • Produces library, which is a foundational component

Project - Deliverables

1 High-performance HPC shared computational environment for SBU faculty/students and enterprises to utilize at CEWIT
2 Delivery of foundational libraries for parallel computation of tensors on GPU based clusters

Project - Benefits to IAB

  • Opportunities to obtain research experience and hands-on software programming and machine learning skills.
  • Computational infrastructure could be utilized in the area of AI and Quantum Computing.
  • Increased productivity of researchers and easier collaboration

Project - Documents

projects/year9/9a.011.sbu.txt · Last modified: 2022/10/19 09:03 by sally.johnson