Louis Jenkins

  • Program Year: 4
  • Academic Institution: University of Rochester
  • Field of Study: Computer Science
  • Academic Advisor: Michael Scott
  • Practicum(s):
    Sandia National Laboratories, New Mexico (2021)
  • Degree(s):
    B.S. Computer Science, Bloomsburg University, 2017
  • Personal URL: https://louisjenkinscs.github.io/

Summary of Research

Typical HPC workloads use batch-processing systems, such as PBS and Slurm, for allocating resources for a period of time to run compute-intensive jobs. This model, while appropriate for conventional scientific computing such as simulations, PDE solvers, and the like, they are not ideal for more modern workloads that require resources that HPC systems can provide, such as ones rooted in data science. In particular, Exploratory Data Analysis (EDA) often has bursts of high-compute followed by idleness centered around human interaction and interpretation of the data itself. Utilization of Persistent Memory can allow for a "stop-and-go" on-demand system, where progress can be made to be incrementally persisted and then be quickly restored, allowing valuable resources to be relinquished. Research will focus on enabling interactivity in places where there are not, and enhancing interactivity in places where there are.

Publications

**Publications**

Louis Jenkins, Tingzhe Zhou, and Michael Spear. "Redesigning Go's Built-In Map to Support Concurrent Operations." 26th International Conference on Parallel Architectures and Compilation Techniques (PACT), IEEE, 2017.

Louis Jenkins. "RCUArray: An RCU-Like Parallel-Safe Distributed Resizable Array." 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, 2018.

G. Dewan and L. Jenkins, "Paving the way for Distributed Non-Blocking Algorithms and Data Structures in the Partitioned Global Address Space model," 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), New Orleans, LA, USA, 2020, pp. 659-666, doi: 10.1109/IPDPSW50202.2020.00111.

Louis Jenkins, Marcin Zalewski, and Michael Ferguson. "Chapel Aggregation Library (CAL)." To Appear @ "Supercomputing 2018: Parallel Applications Workshop - Alternatives to MPI"

Louis Jenkins, et al. "Chapel HyperGraph Library (CHGL)." 2018 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2018.

Joslyn, Cliff A., Sinan Aksoy, Dustin Arendt, Jesun Firoz, Louis Jenkins, Brenda Praggastis, Emilie Purvine, and Marcin Zalewski. "Hypergraph analytics of domain name system relationships." In International Workshop on Algorithms and Models for the Web-Graph, pp. 1-15. Springer, Cham, 2020.

J. S. Firoz, L. Jenkins, C. Joslyn, B. Praggastis, E. Purvine and M. Raugas, "Computing Hypergraph Homology in Chapel," 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), New Orleans, LA, USA, 2020, pp. 667-670, doi: 10.1109/IPDPSW50202.2020.00112.


Louis Jenkins, et al. "Graph Algorithms in PGAS: Chapel and UPC++" 2019 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2019.

Haosen Wen, Wentao Cai, Mingzhe Du, Louis Jenkins, Benjamin Valpey, Michael L. Scott: A Fast, General System for Buffered Persistent Data Structures. ICPP 2021: 73:1-73:11


**Posters**

Louis Jenkins, et al. "Chapel HyperGraph Library (CHGL)", presented at Richland, WA, URL: http://louisjenkinscs.github.io/posters/CHGL.pdf

Awards

Departmental Outstanding Graduate Teaching Assistant Award @ University of Rochester (2020)
Outstanding Performance Award @ Pacific Northwest National Laboratory (2019)
Peer's Choice for Outstanding Project @ Lehigh University (2016)
Honorable Mention @ Computing Research Association's Outstanding Undergraduate Researcher's Competition, 2017
Dean's List @ Bloomsburg University, Spring 2014, Fall 2015, Spring 2017