Research Computing

About Us

Our Vision

To significantly augment the infrastructure and professional support for accelerating the rate of discoveries, fulfilling research and educational goals of the constituents in a timely and equitable manner, bolstering the leadership position of the institution and the nation by promoting internal and external collaborations that result in groundbreaking discoveries, enhancing human health and productivity, and bringing prosperity to the institution and the country.

Our Mission

To empower the University of Louisville's research community by providing access to cutting-edge computing and storage infrastructure, expert consultation and comprehensive training. We strive to accelerate research timelines and enable discoveries that would otherwise not be possible.

Our Goals

Provide robust, reliable, scalable and high-performance computing and storage systems
Foster a collaborative environment for interdisciplinary research
Deliver expert support and training to researchers at all levels
Innovate and adapt to the evolving needs of the computational research landscape

Our Services

Access to powerful computing systems for complex simulations, large-scale computational tasks, data analyses and AI/machine learning

Secure, high-capacity storage solutions, and data transfer services for research data. Use of HPC resources for large-scale data management

Facilitate navigation of compliance requirements for regulated data by connecting researchers with appropriate compliance, risk, legal and ITS teams

Support to optimize code and workflows, selection of computing resources, scripting and visualization. Grant writing support including system design and budgetary quotes

Comprehensive support for standard and researcher-requested software applications, libraries and computational tools

Support for enabling workflows on non-commercial and commercial cloud computing platforms

A condo-model for hosting, operating and maintaining researcher-funded computing and storage infrastructure

Support for accessing NSF-funded resources at external institutions through the ACCESS program

Computing and Storage Systems

Zurada

Our flagship HPC system is purpose-built for AI, distributed parallel and data-intensive workloads. It features NVIDIA GPUs (H200 and H100), powerful AMD CPUs and high-memory (6 TB, 3 TB, 1.5 TB) compute nodes. Backed by a massive parallel file system and high-speed interconnect, it delivers exceptional performance for demanding research applications.

Click for system details, access request form and user guide.

LARCC

This high-throughput computing system is optimized for running large volumes of independent or loosely coupled tasks across a broad range of applications. With a mix of powerful CPUs, advanced GPUs (NVIDIA H100) and fast interconnects, it efficiently handles workloads that demand rapid job turnaround and scalability.

Click for system details, access request form and user guide.

Big Data

This NVIDIA V100 GPU-accelerated HPC system is designed for small-scale (2-4 servers) distributed-parallel computing and data processing. It features a high-memory server (3 TB), ample local storage and a balanced mix of CPUs and GPUs to support a variety of data-intensive and simulation tasks. This system is bigger than LARCC and smaller than Zurada in terms of the number of CPUs and GPUs.

Click for system details, access request form and user guide.

CARDS

A secure, high-capacity storage system for data persistence (on LARCC), ensuring research data is safe, accessible and usable in near future.

Click for system details, account requests through OSDF (coming in future) and user guide.

Research Enabled

Materials Engineering Leveraging molecular dynamics simulations and AI/ML techniques to accelerate the discovery, design, characterization and synthesis of next-generation energy storage materials

Analyzing vast datasets to identify genetic markers for diseases, paving the way for advancements in personalized medicine

Generative AI-based system for accurate prediction of deceased donor liver-transplant (DDLT) outcome and viability