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Creators/Authors contains: "Gough, Erik"

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  1. ; ; ; ; ; ; ; (, ACM)
    PEARC'25 (Ed.)
    The Rosen Center for Advanced Computing at Purdue University has recently released two Generative AI inference tools, AnvilGPT and Purdue GenAI Studio, to the research and campus communities. These services support over 1000 users who use 10+ open-source GenAI models to aid their work. Building on HPC’s long history of using open-source tools, these services are based on customized open-source frameworks and hosted entirely on-prem. This pa- per argues that building custom GenAI services from open-source frameworks is a scalable and cost-effective solution for providing access to Generative AI models. This paper shares the methodology and resources required to develop and host these services and seeks to be a resource for other research computing centers that wish to leverage their HPC investment to create similar services. 
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    Free, publicly-accessible full text available July 18, 2026
  2. ; ; ; ; ; (, Proceedings of Gateways 2024)
    This paper reports on the lessons learned from developing and deploying campus-wide large language model (LLM) services at Purdue University for generative AI (GenAI) applications in education and research. We present a frame- work for identifying an LLM solution suite and identify key considerations related to developing custom solutions. While the GenAI ecosystem continues to evolve, the framework is intended to provide a tool- and organization-agnostic approach to guide leaders in conversations and strategy for future work and collaboration in this emerging field. 
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    Full Text Available 
  3. ; ; ; ; ; (, PEARC '22: Practice and Experience in Advanced Research Computing)
    Full Text Available 
  4. ; ; ; ; ; ; ; ; ; ; et al (, PEARC '22: Practice and Experience in Advanced Research Computing)
    Full Text Available 
  5. ; ; ; ; ; ; (, Supercompcloud workshop 2020)
    null (Ed.)
    New usage patterns of computing for research have emerged that rely on the availability of flexible, elastic, and highly specialized services, that may not be well suited to traditional batch HPC. A new approach that updates and evolves the research computing ecosystem is needed to respond to these needs. This new model, a Kubernetes-based "Community Composable Platform", builds upon Purdue's Community Cluster program to provide cost effective, highly responsive, and customizable composable computing solutions for domain science and education in a variety of communities. 
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    Full Text Available 
  6. ; ; ; ; ; ; ; ; ; ; et al (, PEARC 19: Practice and Experience in Advanced Research Computing)
    The Purdue Live Security Analyzer (PULSAR) is a state-of-the-art, high speed network monitoring and intrusion detection system designed to enhance the security of Purdue University's research cyberinfrastructure. PULSAR project goals include empowering domain scientists to conduct research at Purdue with heightened cybersecurity requirements and engaging undergraduate students through the design, deployment and operation of advanced cyberinfrastructure. Deployment strategies and design decisions are discussed, ultimately providing a recipe book for other institutions to use as a guide for effective implementation of a large scale intrusion detection system for Science DMZs. 
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    Accepted Manuscript Full Text Available
  7. ; ; ; ; ; ; ; (, Proceedings of the Practice and Experience on Advanced Research Computing)
    There is a shortage of training programs for research cyber-facilitators and the need is only growing, especially in academia. This paper will discuss the importance of developing a workforce at the undergraduate level, creating a formal program for training and mentoring undergraduates in Research Computing at Purdue University, and how the approach to mentoring has evolved. The hands-on training and mentoring program has changed from one with students working as junior HPC administrators, performing hardware break-fix in a relative vacuum, to one with students working closely with their mentors, building real-world cyberinfrastructure solutions, such as distributed computing environments. More recently, the mentoring program has grown to include facilitating and supporting research applications with the Purdue user community. Finally, outcomes for the students in these programs lessons learned will be discussed. 
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    Full Text Available