PEARC 2021

Python 201: Building Better Scientific Software in Python Tutorial

Geoffrey Lentner (Purdue), Lev Gorenstein (Purdue), Amiya Maji (Purdue)

The goal of this tutorial is to expose researchers to several best practices in scientific software engineering that may otherwise take several years to become acquainted with. Though the implementation of these lessons is Python-specific, the essential ideas can be exported to other languages or platforms.

Interactive Scientific Computing on the Anvil Composable Platform Tutorial

Eric Adams (Purdue), Erik Gough (Purdue), Brian Werts (Purdue), Stephen Kelley (Purdue), Alan Chalker (Ohio Supercomputer Center)

In this introductory-level tutorial, participants will get hands-on experience with interactive scientific computing using Anvil’s Thinlinc remote desktop and Open OnDemand (OOD) services as well as the Anvil Composable Platform, a service providing web-based access to a Kubernetes-based private cloud.

Research Computing on Campus - Application of a Production Function to the Value of Academic High-Performance Computing Paper

Preston Smith (Purdue), Stephen Harrell

In this paper we present an analysis of value metrics gathered at Purdue University to measure the return on investment (ROI) of institutional investment in cyberinfrastructure resources; and an application of an economic production function to measure the cyberinfrastructure's impact on the institution's academic, financial, and reputational output.

Research Computing on Campus - Application of a Production Function to the Value of Academic High-Performance Computing Paper

Preston Smith (Purdue), Stephen Harrell

In this paper we present an analysis of value metrics gathered at Purdue University to measure the return on investment (ROI) of institutional investment in cyberinfrastructure resources; and an application of an economic production function to measure the cyberinfrastructure's impact on the institution's academic, financial, and reputational output.

Defining Performance of Scientific Application Workloads on the AMD Milan Platform Paper

Geoffrey Lentner (Purdue), Amiya Maji (Purdue), Sam Weekly (Purdue), Tsai-Wei Wu (Purdue), Stephen Lien Harrell, Alex Younts (Purdue), Zoey Mertes (Purdue), Preston Smith (Purdue), Xiao Zhu (Purdue)

In this paper single node performance is gathered for seven popular scientific applications and benchmark test-suites.

Securing CHEESEHub: A Cloud-based, Containerized Cybersecurity Education Platform Paper

Rajesh Kalyanam (Purdue)

In this short paper, we describe the security model of CHEESEHub and specifically the various Kubernetes security features that have been leveraged to secure CHEESEHub. This ensures that the various cybersecurity exploits hosted in the containers cannot be misused, and that potential malicious users of the platform are cordoned off from impacting not just other legitimate users, but also the underlying hosting cloud.