Kirk Cameron
· Assistant ProfessorVirginia Tech · Computer Science
Active 1991–2025
Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.
About
Kirk Cameron is a Professor and Managing Director at the Virginia Tech Institute for Advanced Computing, located in Alexandria, VA. His research interests include systems data analytics, high-performance computing, computational science, machine learning, and software engineering. He holds a Ph.D. in computer science from Louisiana State University earned in 2000 and a B.S. in mathematics from the University of Florida obtained in 1994. Cameron is involved in advancing computational methods and data analysis techniques within the field of computer science. His professional activities are centered at the Institute for Advanced Computing, where he contributes to research and development in these areas.
Research topics
- Computer Science
- Parallel computing
- Engineering
- Algorithm
- Engineering management
- Data Mining
- Machine Learning
- Mathematics
- Artificial Intelligence
- Knowledge management
Selected publications
Quality Engineering · 2021 · 15 citations
Senior authorCorrespondingPerformance variability is an important measure for a reliable high performance computing (HPC) system. Performance variability is affected by complicated interactions between numerous factors, such as CPU frequency, the number of input/output (IO) threads, and the IO scheduler. In this paper, we focus on HPC IO variability. The prediction of HPC variability is a challenging problem in the engineering of HPC systems and there is little statistical work on this problem to date. Although there are…
Interpolation of sparse high-dimensional data
Numerical Algorithms · 2020-11-13 · 14 citations
articleSenior authorACM Transactions on Mathematical Software · 2020 · 14 citations
DELAUNAYSPARSE contains both serial and parallel codes written in Fortran 2003 (with OpenMP) for performing medium- to high-dimensional interpolation via the Delaunay triangulation. To accommodate the exponential growth in the size of the Delaunay triangulation in high dimensions, DELAUNAYSPARSE computes only a sparse subset of the complete Delaunay triangulation, as necessary for performing interpolation at the user specified points. This article includes algorithm and implementation details, c…
Journal of Parallel and Distributed Computing · 2020 · 11 citations
Translation-optimized Memory Compression for Capacity
2022 · 10 citations
The demand for memory is ever increasing. Many prior works have explored hardware memory compression to increase effective memory capacity. However, prior works compress and pack/migrate data at a small - memory block-level - granularity; this introduces an additional block-level translation after the page-level virtual address translation. In general, the smaller the granularity of address translation, the higher the translation overhead. As such, this additional block-level translation exacerb…
Recent grants
CSR: Large: VarSys: Managing Variability in High-Performance Computing Systems
NSF · $1.2M · 2016–2019
CAREER: High-Performance, Power-Aware, Distributed Computing
NSF · $243k · 2005–2009
NSF · $181k · 2013–2017
Frequent coauthors
- 52 shared
Sam Blanchard
Virginia Tech
- 50 shared
Aditya Johri
George Mason University
- 49 shared
Bushra Chowdhury
Virginia Tech
- 21 shared
Dimitrios S. Nikolopoulos
Virginia Tech
- 20 shared
Layne T. Watson
- 20 shared
Yili Hong
- 19 shared
Thomas Lux
- 19 shared
Ali R. Butt
Virginia Tech
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