Published June 18, 2021
CCR has an on-going program that provides undergraduate students with advanced training in software engineering and computational science while employing them to work on a wide range of active research projects. Students not only gain valuable experience working in a state-of-the-art research environment as part of a team, often applying knowledge in their chosen fields, but also utilize new technologies, including cloud computing, machine learning, software engineering, database design, parallel computing, and user interface development.
Meet the 2021 Summer Intern Team!
Farhan Chowdhury is a senior studying Computer Science at the University at Buffalo, SUNY. He is working as a Bioinformatics Computational Intern at the UB Genomics & Bioinformatics Core (GBC). This summer he is working on increasing the competencies in bioinformatic analysis of next-generation sequencing data using a Linux-based massively parallel compute environment. Specifically, he will be analyzing bacterial genome sequencing to look for variant, diversity and much more in water samples collected from WNY. Some of the tools he is using include the Linux command line environment, Python snakemake pipeline, R Studio, open-source nanopore and minion sequencing analysis tools. The project activities are in support of the NIH Science Educational Partnership Award received by UB's Dr. Stephen Koury - The Metagenomics Education Partnership: Harnessing the Power of Microbial Genome Sequencing and Big Data with High School Students and Teachers.
William Mathias is a Computer Science Engineering major at the University of Michigan and is working on the Slurm Simulator project. Slurm is an open-source job scheduling system used to manage HPC resources. Slurm has many parametric settings so that it can be adjusted to work on different HPC systems. The issue is that it can be difficult to tell how changes in Slurm's settings will affect the overall performance of the HPC resources. The purpose of the Slurm Simulator is to predict how these changes in the Slurm parameters will affect performance.
Joshua Moraes is a rising senior at UC Berkeley majoring in Electrical Engineering and Computer Science. His work focuses on testing potential database changes for the development of XDMoD. The main goal of his project is figuring out what it will take to change the MySQL database table engine currently being used from MyISAM to InnoDB, and determining what the effect of the change will be in terms of performance and other metrics.
Brian Scorcia is a rising senior at the University at Buffalo. He working on the development of ColdFront under the mentorship of Dori Sajdak and Andrew Bruno. ColdFront is an open resource allocation management system built for high performance computing centers that allows the management of Center resources and User allocations to those resources. He will be responsible for building out a test infrastructure for the project, adding brand new features, and fixing known bugs in the application. Brian is also helping take care of much needed CCR website updates!
Elliot Snitzer attends the University of Pittsburgh and is working under the direction of Jeanette Sperhac and assists tool development for the Ghub users at CCR. His primary responsibility is to develop tools for the purpose of data analyses and model validation. This data generally involves measurements of ice sheets around the world such as the Greenland and Antarctic Ice Sheets. His current project is a tool that provides a visual comparison of the differences between ice sheet data retrieved via different satellite imaging technologies. This is Elliot's third year as a summer intern at CCR.
Jason Steiger is currently a University at Buffalo sophomore student. He is researching adding Event Streaming as an ingestion source to XDMoD. Through the integration of public clouds, performance analytics will be added to XDMoD via Kafka.
Matthew Zhou, a Computer Science major at The Ohio State University, is working with Dr. Joseph White on a SUPReMM plugin that can accurately classify job performance. This includes categorizing jobs based on their CPU usage and finding jobs that could be more efficient at utilizing their cores. For the plugin in its current state, they have also set up a server that allows faculty to view the results on a webpage and tell us how accurate they are.