Name: SCAILFIN - Scalable CyberInfrastructure for Artificial Intelligence and Likelihood Free Inference
Start: 2021-01-14T12:00:00-05:00
End: 2021-01-14T13:00:00-05:00
Location: No location set

SCAILFIN - Scalable CyberInfrastructure for Artificial Intelligence and Likelihood Free Inference

Thursday, 14 January 2021 - 12:00

Monday, 11 January 2021
Tuesday, 12 January 2021
Wednesday, 13 January 2021
Thursday, 14 January 2021
12:00 SCAILFIN - Scalable CyberInfrastructure for Artificial Intelligence and Likelihood Free Inference - Kenyi Hurtado Anampa Kenyi Hurtado Anampa (University of Notre Dame)
SCAILFIN - Scalable CyberInfrastructure for Artificial Intelligence and Likelihood Free Inference
- Kenyi Hurtado Anampa
- Kenyi Hurtado Anampa (University of Notre Dame)
12:00 - 12:30
The NSF-funded Scalable CyberInfrastructure for Artificial Intelligence and Likelihood Free Inference (SCAILFIN) project aims to develop and deploy artificial intelligence (AI) and likelihood-free inference (LFI) techniques and software using scalable cyberinfrastructure (CI) built on top of existing CI elements. Specifically, the project has extended the CERN-based REANA framework, a cloud-based data analysis platform deployed on top of Kubernetes clusters that was originally designed to enable analysis reusability and reproducibility. REANA is capable of orchestrating extremely complicated multi-step workflows, and uses Kubernetes clusters both for scheduling and distributing container-based workloads across a cluster of available machines, as well as instantiating and monitoring the concrete workloads themselves. This work describes the challenges and development efforts involved in extending REANA and the components that were developed in order to enable large scale deployment on High Performance Computing (HPC) resources, by integrating REANA with the Virtual Clusters for Community Computation (VC3) infrastructure as a starting point, while simultaneously removing REANA's dependence on Kubernetes support at the workers level.