Sidharth Kumar
Assistant Professor at
UAB
CS
My research lies at the intersection of HPC and Data Analytics. More broadly, I work on problems in parallel computing, big data processing, parallel I/O, scalable algorithms, large data file formats and performance modeling. I am looking for students! |
Conference Papers | |
![]() |
Compiling Data-Parallel Datalog Thomas Gilray, Sidharth Kumar, Kristopher Micinski. International Conference on Compiler Construction (CC 2021) [CC 2021] |
![]() |
Adaptive Spatially Aware I/O for Multiresolution Particle Data Layouts Will Usher, Xuan Huang , Steve Petruzza, Sidharth Kumar, Stuart R. Slattery, Sam T. Reeve, Feng Wang, Chris R. Johnson and Valerio Pascucci. International Parallel and Distributed Processing Symposium (IPDPS 2021) [IPDPS 2021] |
![]() |
Load-balancing Parallel Relational Algebra Sidharth Kumar, Thomas Gilray. The International Supercomputing Conference [ISC 2020][Hans Meuer Best Paper Award] |
![]() |
Distributed Relational Algebra at Scale Sidharth Kumar, Thomas Gilray IEEE Conference On High Performance Computing, Data, and Analytics. [HiPC 2019][Best Paper Award] |
![]() |
Spatially-aware Parallel I/O for Particle Data, Sidharth Kumar, Steve Petruzza, Will Usher, Valerio Pascucci. ACM International Conference on Parallel Processing [ICPP 2019] |
![]() |
VisIt-OSPRay: Toward an Exascale Volume Visualization System. Qi Wu, Will Usher, Steve Petruzza, Sidharth Kumar , Feng Wang, Ingo Wald, Valerio Pascucci and Charles D. Hansen. Eurographics Symposium on Parallel Graphics and Visualization 2018. [EGPGV 2018] |
![]() |
Scalable Data Management of the Uintah Simulation Framework for Next-Generation Engineering Problems with Radiation. Sidharth Kumar, Alan Humphrey, Will Usher, Steve Petruzza, Brad Peterson, John A. Schmidt, Derek Harris, Ben Isaac, Jeremy Thornock, Todd Harman, Valerio Pascucci, Martin Berzins. Supercomputing Asia 2018. [SCA 2018] |
![]() |
Reducing network congestion and synchronization overhead during aggregation of hierarchical data. Sidharth Kumar, Duong Hoang, Steve Petruzza, John Edwards, Valerio Pascucci. IEEE Conference On High Performance Computing, Data, and Analytics. [HiPC 2017] |
![]() |
Evaluation of
In-Situ Analysis Strategies at Scale
for Power Efficiency and Scalability.
Aaditya Landge, Ivan Rodero, Sidharth Kumar,
Manish Parasar, Valerio Pascucci, Peer-Timo
Bremer. IEEE/ACM International Symposium
on Cluster, Cloud and Grid Computing. |
![]() |
Efficient I/O and storage of adaptive resolution data. Sidharth Kumar, John Edwards, Peer-Timo Bremer, Aaron Knoll, Cameron Christensen, Venkatram Vishwanath, Phil Carns, John A. Schmidt, Valerio Pascucci. IEEE Conference On High Performance Computing Networking, Storage And Analysis. [SC 2014] |
![]() |
Fast
multi-resolution reads of massive
simulation datasets.
Sidharth Kumar, Cameron Christensen, John. A
Schmidt, Peer-Timo Bremer, Eric
Brugger,Venkatram Vishwanath, Philip Carns,
Giorgio Scorzelli, Hemanth Kolla, Ray Grout,
Jacqueline Chen, and Valerio Pascucci. The
International
Supercomputing Conference. |
![]() |
Characterization
and modeling of pidx parallel I/O for
performance optimization.
Sidharth Kumar, Avishek Saha, Venkatram
Vishwanath, Philip Carns, John A Schmidt,
Giorgio Scorzelli, Hemanth Kolla, Ray Grout,
Robert Latham, Robert Ross, Michael E Papkafa,
Jacqueline Chen, Valerio Pascucci. IEEE
Conference
On High Performance Computing Networking,
Storage And Analysis. |
![]() |
Efficient data
restructuring and aggregation for I/O
acceleration in PIDX.
Sidharth Kumar, Venkatram Vishwanath, Phil
Carns, Joshua A. Levine, Robert Latham, Giorgio
Scorzelli, Robert Ross, Hemanth
Kolla, Ray Grout, Jackie Chen. IEEE Conference
On High Performance Computing Networking,
Storage And Analysis. |
![]() |
PIDX: efficient
parallel I/O for multiresolution
multi-dimensional scientific datasets.
Sidharth Kumar, Venkatram Vishwanath, Phil
Carns, Brian Summa, Giorgio Scorzelli, Valerio
Pascucci, Robert Ross, Jackie Chen,
Hemanth Kolla. IEEE International Conference on
Cluster Computing. |
Book Chapters |
|
![]() |
Big Data From
Scientific Simulations.
John Edwards, Sidharth Kumar, Valerio Pascucci.
Big Data and High Performance Computing,
Advances in Parallel Computing,
Volume 26, L. Grandinetti, G. Joubert, M.
Kunze, V. pascucci, Eds. IOS Press, 2015, pages
32-46. |
![]() |
Scalable
Visualization and Interactive Analysis
Using Massive Data Streams. V.
Pascucci,
P.-T. Bremer, A. Gyulassy, G. Scorzelli, C.
Christensen, B. Summa, S. Kumar. Cloud
Computing
and Big Data, Advances in Parallel Computing,
Volume 23, C. Catlett, W. Gentzsch, L.
Grandinetti,
G. Joubert, J. L. Vazquez-Poletti, Eds. IOS
Press, 2013, pages 212-230. |
![]() |
The ViSUS
Visualization Framework. V.
Pascucci, G. Scorzelli, B. Summa, P.-T. Bremer,
A. Gyulassy, C. Christensen, S. Philip, and S. Kumar. In High Performance Visualization:
Enabling Extreme-Scale Scientific Insight, E.
W. Bethel, H. Childs, C. Hansen, Eds. Chapman
& Hall/CRC Computational Science, 2012. |
Workshop Papers |
|
![]() |
Toward
Parallelizing Control-flow Analysis
with Datalog. Thomas Gilray,
Sidharth Kumar.
Scheme and Functional Programming Workshop. |
![]() |
Towards parallel access of multidimensional, multiresolution scientific data. Sidharth Kumar, Valerio Pascucci, Venkatram Vishwanath, Phil Carns, Robert Latham, Tom Peterka, Michael Papka, Robert Ross. Petascale Data Storage Workshop. [PDSW 2010] |
Dissertation |
|
![]() |
A Scalable and Tunable Adaptive Resolution Parallel I/O Framework |
Technical Reports |
|
![]() |
An Integrated Approach
to Scaling Task-Based Runtime Systems for Next
Generation Engineering
Problems.
Alan Humphrey, Bradley Peterson, John Schmidt, Martin Berzins, Derek Harris, Ben Isaac, Jeremy Thornoc, Todd Harman, Sidharth Kumar, Steve Petruzza, Allen Sanderson and Valerio Pascucci. Technical report, SCI Institute, The university of Utah. [Tech Report 2017] |
![]() |
Symmetry as an organizational principle in cognitive sensor networks. Thomas C Henderson, Y Fan, Sanjay Devnani, Sidharth Kumar, Elaine Cohen, Edward Grant. Technical Report UUCS-09- 005, 2009, The University of Utah [Tech Report 2009] |