2026-03-11 –, Breakout Room
As HPC expands beyond computer science, many users encounter command-line interfaces for the first time. HPCMosaic addresses this gap with a modular OOD dashboard that simplifies cluster management for non-technical researchers while staying customizable for experienced users. This talk presents a framework that reduces support burden by enabling self-service for common tasks (file quotas, account management, and job control) decreasing repetitive tickets. Targeted at HPC developers and cluster admins, this session covers modern dashboard development focused on customizability and user experience. Attendees will learn how to build accessible HPC interfaces that let researchers focus on their work instead of troubleshooting, reducing user frustration and support workload.
The democratization of high-performance computing has created a paradox, as clusters become more powerful and essential for research across disciplines, the gap between computational capability and user technical proficiency also widens. Biologists, social scientists, and domain experts increasingly need HPC resources but often lack the specialized computer skills traditionally required to interact with these systems effectively.
HPCMosaic emerged from observing this friction point at A&M's HPRC group, where support teams handle numerous daily tickets for simple, repetitive tasks (quota checks, account status inquiries, job status monitoring) that often require multiple follow-ups due to incomplete information. Each ticket represents time lost for both researchers and support staff, time that could be better spent on actual research or complex technical challenges.
This talk introduces HPCMosaic, a modular and replicable Open OnDemand dashboard framework designed with two core principles: accessibility for non-technical users and customizability for diverse institutional needs. Rather than forcing users to navigate command-line interfaces for routine tasks, HPCMosaic provides an intuitive web interface that proactively surfaces relevant information and enables self-service resource management.
Talk Outline:
Problem context (5 min): The evolving HPC user landscape and support burden
HPCMosaic architecture (8 min): Modular design philosophy, customization points, and replicability considerations
Key features (7 min): Self-service tools, proactive information display, and support ticket reduction strategies
Implementation considerations (3 min): Deployment approaches for different institutional contexts
Q&A (2 min)
Target Audience:
HPC system administrators, research computing support staff, and developers at universities or research institutions managing computing clusters. No advanced web development experience required, though familiarity with HPC environments and Open OnDemand is helpful.
Key Takeaways:
Attendees will understand architectural patterns for building accessible HPC dashboards, learn strategies for reducing support burden through better UX design, and gain practical insights into deploying customizable interfaces that scale across different institutional needs. The modular approach enables institutions to adapt HPCMosaic to their specific requirements while maintaining core accessibility benefits.
Sahil Vartak is a Master's student in Computer Engineering at Texas A&M University specializing in full-stack development and AI integration. As Lead Web Developer at Texas A&M High Performance Research Computing, he builds and maintains production software serving over 1,000 researchers daily. His work spans modern web applications, backend services, and machine learning pipelines. Previously, he developed ML-driven analytics dashboards at McDermott International and contributed to AI research published in PerCom 2025. Sahil is passionate about building reliable, scalable software and leveraging AI tools to accelerate development.