Indiana Jetstream2 GPU
Indiana University
Resource Type: Compute
User Guide: https://docs.jetstream-cloud.org/
Recommended Use: For the researcher needing GPUs for virtual machine services on demand as well as for software creators and researchers needing to create their own customized virtual machine environments. Additional use cases are for research-supporting infrastructure services that need to be "always on" as well as science gateway services and for education support, providing virtual machines for students. For the educators needing GPUs for virtual machine services for interactive or on demand purposes, and classroom-related use such as Jupyter notebooks or customized virtual machine environments. Additional use cases are education-supporting infrastructure services that need to be “always on” as well as science gateway services that support education, or providing virtual machines for students. The A100 GPUs on Jetstream2-GPU are well-suited for machine learning/deep learning projects and other codes optimized for GPU usage. They also may be utilized for some graphical/desktop applications through convenient web-based interfaces such as Exosphere and CACAO which can be leveraged for special topic workshops or courses. The service supports partial GPU instances through use of virtual GPUs (vGPUs) allowing large-scale education use. The A100 GPUs on Jetstream2-GPU are well-suited for machine learning/deep learning projects and other codes optimized for GPU usage. They also may be utilized for some graphical/desktop applications with some effort.
Latitude: 39.168321739926945
Longitude: -86.52278736833607
Production Dates: 10/01/2021 - 09/30/2025
Public URL: https://cider.access-ci.org/public/resources/RDR_000904
Description: Jetstream2 GPU is a hybrid-cloud platform that provides flexible, on-demand, programmable cyberinfrastructure tools ranging from interactive virtual machine services to a variety of infrastructure and orchestration services for research and education. This particular portion of the resource is allocated separately from the primary resource and contains 360 NVIDIA A100 GPUs -- 4 GPUs per node, 128 AMD Milan cores, and 512gb RAM connected by 100gbps ethernet to the spine.