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:
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
Skylar Liang
Summer 2020 - Spring 2022
Blizzard
Backend Development, Client API, GPU Data Collection and Analysis
Cesar Smokowski
Summer 2020 - Fall 2022
Completed MS in CS at Virginia Tech - Amazon
Frontend Development, Outreach
Julia Chen
Spring 2021 - Spring 2022
MEng in CS at Virginia Tech - Cvent
Backend Development, Data Analysis
Lalitha Kuppa
Fall 2019 - Spring 2022
LinkedIn
Data Lead: Memory and OS data collection/analysis, API development
Aparna Ganesh
Fall 2020 - Spring 2022
MEng in CS at Virginia Tech - Alias Intelligence
Front-End Lead: Frontend development and visualizations
Eles Jones
Spring 2019 - Spring 2022
Completed MS in CS at Virginia Tech
Operating system data collection/analysis, API development, data visualization, and lineage determination
Lucy Paul
Summer 2020 - Spring 2022
Lockheed Martin
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
MEng in CS at Virginia Tech - Systems Planning and Analysis, Inc.
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
MEng Program
Machine learning
Samie Amriui
Fall 2019 - Fall 2020
Fannie Mae
Frontend Visualizations
Shorya Malhotra
Fall 2019 - Fall 2020
MS in CS, PWC and MQBIT
GPU data collection and database design
Allison DeSantis
Summer 2020 - Fall 2020
Booz Allen Hamilton
Outreach
Camellia Pastore
Summer 2020 - Fall 2020
Accenture
Outreach
Catherine Lee
Fall 2020
Deloitte
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
Reinventing Geospatial
Integrated systems lineage repository(iLORE) data collection and cleaning
Zoe Smith
Spring 2018 - Fall 2019
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
