About CSG


CSG Team Picture

Mission

Since the dawn of computing, the world has tracked system performance. Yet, computer system performance data is still primarily siloed by benchmark, system, or system component. The Mission of the Computer Systems Genome Project (CSGenome) is to conduct the first scientific effort to catalog the lineage of computer system performance over time to enable knowledge discovery and further understanding of the impact of computing innovations on transformative technologies, the knowledge-based economy, and societal change.

The CSGenome Project is led by Professors Kirk W. Cameron (PI), Godmar Back (co-PI and Technical Advisor), and Margaret Ellis (co-PI and Team Leader) and an extremely talented and highly diverse group of more than a dozen Virginia Tech undergraduate and graduate students.

Data Sources

The data used to create the lineage is drawn from a number of sources, including:

CSG Team - Students

Current Students

Skylar Liang
Summer 2020 - Present
Backend Lead
Backend Development, Client API, GPU Data Collection and Analysis
Ryan Gniadek
Fall 2020 - Present
DevOps Lead and Crowdsourcing Lead
Backend Engineering, DevOps, Infrastructure
Michael Atkins
Fall 2021 - Present
Backend Lead
Full-Stack Development, Client API
Becca Hendricks
Fall 2021 - Present
Design Lead
Frontend Development
Cesar Smokowski
Summer 2020 - Present
Frontend Development, Outreach
Julia Chen
Spring 2021 - Present
Backend Development, Data Analysis
Brendan Doney
Summer 2021 - Present
Full-Stack Development, Machine Learning
Caylie Baughman
Fall 2021 - Present
Full-Stack Development, Client API
Rayhan Biju
Fall 2021 - Present
Full-Stack Development, Crowdsourcing
Todd Cochran
Fall 2021 - Present
Backend Development, GPU Data Collection and Analysis
Sarah Huang
Fall 2021 - Present
Full-Stack Development, Crowdsourcing
Sofia Kazmierczak
Fall 2021 - Present
Frontend Development, Authentication
Ani Ramadoss
Fall 2021 - Present
Backend Development, Client API
Rio Young
Fall 2021 - Present
Full-Stack Development, Crowdsourcing
Alina Bhatti
Fall 2022 - Present
Backend Development, Crowdsourcing
Sophya Hargenrater
Fall 2022 - Present
Frontend Development, Crowdsourcing
Brian Mamani Balderrama
Fall 2022 - Present
Full-Stack Development, Client API
Tai Nunez
Fall 2022 - Present
Backend Development, Crowdsourcing
Justin Turkiewicz
Fall 2022 - Present
Backend Development, Authentication

Previous Students

Nicolas Hardy
Spring 2018 - Spring 2021
Completed MS in CS at Virginia Tech - Amazon
Leads overall design: data collection, data cleaning, database design and storage, API development, testing, front end website, and data visualizations
Sam Furman
Spring 2018 - Spring 2021
Completed MS in CS at Virginia Tech - Bloomberg
Leads data collection, data cleaning, testing, and data analysis and visualization; leader in genome lineage determination
Chandler Jearls
Fall 2017 - Fall 2019
Completed MS in ECE at Virginia Tech - Apple
Data collection and data cleaning; leader in genome lineage determination
Lalitha Kuppa
Fall 2019 - Spring 2022
LinkedIn
Data Lead: Memory and OS data collection/analysis, API development
Aparna Ganesh
Fall 2020 - Spring 2022
Masters of Engineering Program, Virginia Tech
Front-End Lead: Frontend development and visualizations
Eles Jones
Spring 2019 - Spring 2022
Operating system data collection/analysis, API development, data visualization, and lineage determination
Lucy Paul
Summer 2020 - Spring 2022
API development
Nuvya Baliyan
Fall 2020 - Spring 2022
ADP
Analysis, outreach, and frontend visualizations
Jianna George
Fall 2020 - Spring 2022
Capital One
Analysis, outreach, and frontend visualizations
Camila Arbaiza
Spring 2021 - Spring 2022
Masters of Engineering Program, Virginia Tech
Real-world connections
Lauren Osborne
Fall 2021 - Spring 2022
Alarm.com
Backend Development
Kevin Zhou
Fall 2021 - Spring 2022
Backend Development
Evelyn Keeley
Spring 2021 - Fall 2021
Frontend development
Tanvi Haldankar
Spring 2019 - Spring 2021
Bloomberg
Memory data collection/analysis, data visualization, and lineage determination
Ally Johnson
Spring 2021 - Spring 2021
Microsoft
Frontend visualizations
Analisa Wu
Fall 2019 - Spring 2021
GPU data collection
Honghao "Simon" Zhang
Fall 2019 - Spring 2021
Frontend development and maintenance
Grayson Stone
Spring 2019 - Spring 2020
Amazon
Data collection, data cleaning, API development, testing, and logo design
Hamsa Mani
Spring 2019 - Spring 2020
JP Morgan
GPU data collection and data visualizations
Thomas Szydlowski
Spring 2019 - Spring 2020
Mitre
Data collection, data cleaning, and testing
Sameer Dandekar
Fall 2019 - Spring 2020
JP Morgan
Data collection, data cleaning, and testing
Kenneth Powell
Fall 2019 - Spring 2020
Machine learning
Samie Amriui
Fall 2019 - Fall 2020
Frontend Visualizations
Shorya Malhotra
Fall 2019 - Fall 2020
GPU data collection and database design
Allison DeSantis
Summer 2020 - Fall 2020
Booz Allen Hamilton
Outreach
Camellia Pastore
Summer 2020 - Fall 2020
Outreach
Catherine Lee
Fall 2020
Frontend visualizations
Jiayi "JW" Lee
Spring 2018 - Fall 2019
Microsoft
Assisted with overall project management; data collection, data cleaning, website and interactive data visualization
Quyen "Liz" Dao
Spring 2018 - Fall 2019
Facebook
Data collection, data cleaning, data analysis, and mentoring newer members
Zeke Lin
Fall 2019
Website development and visualizations
Luke McCormick
Spring 2018 - Spring 2019
Integrated systems lineage repository(iLORE) data collection and cleaning
Zoe Smith
Spring 2018 - Fall 2018
Integrated systems lineage repository(iLORE), data collection, and cleaning

CSG Team - Faculty

Kirk W. Cameron, Ph.D.
Professor of Computer Science and a Research Fellow in the College of Engineering at Virginia Tech. The central theme of his research is to improve power and performance efficiency in high performance computing (HPC) systems and applications. Accolades for his work include NSF and DOE Career Awards, IBM and AMD Faculty Awards, and being named Innovator of the Week by Bloomberg Businessweek Magazine. In 2017-2018, Prof. Cameron held a Distinguished Visiting Fellowship at Queen’s University Belfast from the U.K. Royal Academy of Engineering. He is Director of the stack@cs Center for Computer Systems and the Scalable Performance Laboratory. Kirk is overall VarSys project lead PI and heads the HPC Systems Team.
Margaret Ellis, M.S.
Associate Professor of the Practice of Computer Science in the College of Engineering at Virginia Tech. As a passionate teacher of key courses such as problem solving and data structures, her work lies at the intersection of computer science research, computer science education, and challenges of diversity and inclusion in the field. Among other accolades for her teaching efforts she was awarded the 2015 Engineering Inclusive Teaching (EIT) Inclusive Educators Award by Women in Engineering ProActive Network (WEPAN). An accomplished entrepreneur and innovator, she received related awards from the regional Roanoke Blacksburg Technology Council in 2010 and 2011 respectively. Margaret contributes substantially to the outreach efforts in the VarSys project and currently leads the Data Analysis and Classification Team of undergraduates creating new protocols for classifying systems for variability.
Godmar Back, Ph.D.
Associate Professor of Computer Science in the College of Engineering at Virginia Tech. His research primarily focuses on computer operating systems while his interests also include collaborative work in computer science education and the library sciences. Accolades for his research include the NSF Career Award. For his educational efforts, he was awarded the 2018 ICPC Foundation Coach Award recognizing mentoring excellence resulting in 5 teams in 6 years competing in the World Finals. He leads the Systems Software Laboratory at Virginia Tech.

Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant Nos. CNS 1565314 and CNS 1939076.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Contact Us

Have any inquiries/suggestion/corrections for our data? Email us at csgenome_website <at> googlegroups <dot> com