Hewlett Packard Enterprise Data Science Institute

Containers, which are software packages that house necessary elements for running programs, are often used in high performance computing (HPC) applications. For the University of Houston’s HPC clusters, users can optimize their workloads through Apptainer (formerly Singularity), a flexible and user-friendly container system designed specifically for HPC workloads. The Apptainer platform provides an increased level of security, portability, customization and performance.

In the first half of the seminar, Pasunuri introduced basic commands in Apptainer through practical examples: launching a shell, running Apptainer as an executable and executing container commands. Pasunuri also explained the process of acquiring container images, which can be pulled from the Docker registry through the Singularity hub. Container images can also be built through a definition file on the hub. However, users will need sufficient disk space and memory to create an image. According to Pasunuri, this can be mitigated by requesting more resources and memory space in a user’s project directory.

In the second half of the seminar, Pasunuri discussed the advantage of using Apptainer in UH HPC clusters, highlighting the platform’s ability to create and run commands inside a job script. Pasunuri then demonstrated how to use and run Apptainer image containers inside a job script. This feature enables users to handle dependencies and maintain reproducibility within their workload. Additionally, Apptainer incorporates a bind option in its software, facilitating the integration of directories and external applications, such as UH HPC clusters.

Aravind Kumar Reddy Pasunuri is a teaching assistant and front desk support for the Hewlett Packard Enterprise Data Science Institute. In this role, he has had the opportunity to work with Apptainer, gaining practical experience in containerization technology and its role in modern software development practices.

To access the UH’s HPC clusters, faculty and researchers can request cluster access online. For more information about RCDC resources and information, please visit the RCDC website.

52 participants across 16 teams presented research in the fields of computing, data science and artificial intelligence at the annual Data Science Showcase hosted by the HPE Data Science Institute and the Department of Computer Science at UH. The event, held last December, was first launched in 2022 to provide a platform for highlighting the accomplishments of outstanding young researchers and encouraging them to pursue a future in data science. 

"This showcase allowed students to apply their knowledge and develop new skills through their research activities,” said Nouhad Rizk, Ph.D., instructional professor in the Department of Computer Science. “Many students enjoyed interacting with their mentors outside of the classroom, providing exceptional opportunities for them to learn and build lasting relationships."

The event featured presentations by UH students from various academic disciplines. Each group gave an overview of their abstract, background, results and more. Many research topics centered around applying AI techniques, such as neural networks, deep learning and machine learning models, toward real-life industry practices like disease detection systems and cybersecurity measures.

“We were excited to partner with Dr. Nouhad Rizk and the Department of Computer Science to support the Data Science Showcase for undergraduate students across UH,” said Andrew Kapral, Ph.D., Director of Engaged Data Science at the HPE DSI. “From classifying geologic formations in the Athabasca Oil Sands to predictive analysis of outcomes for patients with heart disease, the projects presented this year covered a broad range of topics and were of outstanding quality.”

The showcase offered students the opportunity to educate themselves on communicating their research, while also providing them a channel of peer support for a future in data science. 

“Project-based learning is essential for honing data science skills, and we look forward to expanding opportunities for UH students to engage in these kinds of experiences in future,” Kapral said.

At the end of the event, a jury voted on the best student projects. The panel consisted of faculty and staff from the Department of Computer Science and the HPE Data Science Institute. Each winning group received an Amazon gift card. 

Showcase Winners 

First Place

Team: William Le, Ruben Daniel Montemayor, Charlies Tian
Project: Heart Disease Prediction Using Deep Learning

Second Place

Team: William Brieden, Khanh Nguyen, Osasenaga Obano
Project: Diabetic Retinopathy Classification Using Neural Networks

Third Place

Team: Wian van Dyk, Joshua Folh, Sammy Hamdi
Project: Brain Tumor Classification in MRI With Deep Learning

Fourth Place

Team: Jusvin Charles, James Graham, Justin Hose
Project: Retinal Disease Detection Using Convolutional Neural Networks

Fifth Place

Team: Nirorn Hong, Maximus Furtado, Erik Perales
Project: Age and Gender Prediction Using Convolutional Neural Networks