I am a Computer Scientist at Lawrence Livermore National Laboratory working on High Performance Computing. My current research is on developing batch job scheduling algorithms for next-generation HPC clusters.

2018 - Present

Lawrence Livermore National Laboratory

Computer Scientist

Creating next-generation job schedulers for HPC clusters through development of the Flux resource manager.

2012 - 2018

University of Delaware

Research Assistant

2014-2018: Created next-generation I/O-aware and hierarchical job schedulers for HPC clusters utilizing the Flux resource manager.

2014: Developed a suite of tools to profile, auto-tune, and optimize applications developed with the parallel I/O library ADIOS.

2013: Integrated in-transit analysis and staging into the scientific application QMCPack to improve I/O performance and scalability.

2012: Developed a crowdsourcing web application, ExSciTecH, to complement the volunteer computing project [email protected]

2014 - 2017
(Summers)

Lawrence Livermore National Laboratory

Research Intern

2017: Integrated my hierarchical scheduler with the Uncertainty Quantification Pipeline (UQP), resulting in a 37% improvement in workload runtime

2016: Added dynamicity to my hierarchical scheduler to eliminate resource fragmentation

2015: Developed an automatic job aggregator and hierarchical scheduler, resulting in a 4x speed up over the existing scheduler

2014: Developed a discrete-event simulator for the next-generation resource manager, Flux

Summer 2013

Oak Ridge National Laboratory

Science Undergraduate Laboratory Intern (SULI)

Integrated ADIOS, ORNL's IO framework, into QMCPack, a quantum monte-carlo simulator.

Examined the performance of various IO methods and techniques on peta-scale systems like Titan.

Summer 2012

University of Houston

Research Experience for Undergraduates (REU) Intern

Optimized VolpexMPI library for use on large-scale clusters.

2014 - 2018

University of Delaware

PhD in Computer & Information Sciences

4.0 GPA

2014 - 2016

University of Delaware

M.S. in Computer Science

4.0 GPA

2010 - 2014

University of Delaware

B.S. in Computer Science

Honors Degree with Distinction
3.932 GPA

Conference Papers

2016

R. McKenna, S. Herbein, A. Moody, T. Gamblin, and M. Taufer. Scalable I/O-Aware Job Scheduling for Burst Buffer Enabled HPC Clusters. In Proceedings of the IEEE Cluster Conference. Taipei, Taiwan, September 2016.

S. Herbein, D. H. Ahn, D. Lipari, T. R.W. Scogland, M. Stearman, M. Grondona, J. Garlick, B. Springmeyer, and M. Taufer. Scalable I/O-Aware Job Scheduling for Burst Buffer Enabled HPC Clusters. In Proceedings of the 25th International Symposium on High-Performance Parallel and Distributed Computing (HPDC). Kyoto, Japan, June 2016.

S. Herbein, A. Dusia, A. Landwehr, S. McDaniel, J. Monsalve, Y. Yang, S. R. Seelam, and M. Taufer. Resource Management for Running HPC Applications in Container Clouds. In Proceedings of the 31st International Supercomputing Conference (ISC). Leipzig, Germany, June 2016.

2014

S. Herbein, S. Klasky, and M. Taufer. Benchmarking the Performance of Scientific Applications with Irregular I/O at the Extreme Scale. In the Proceedings of the Seventh International Workshop on Parallel Programming Models and Systems Software for High-End Computing (P2S2). Minneapolis, Minnesota, September 2014.

2013

S. Herbein, M. Matheny, M. Wezowicz, J. Kroger, J. Kim, S. Klasky, and M. Taufer. Performance Impact of I/O on QMCPack Simulations at the Petascale and Beyond. In the Proceedings of the 16th IEEE International Conferences on Computational Science and Engineering, Sydney, Australia, December 2013.

S. Schlachter, S. Herbein, S. Ou, J.S. Logan, S. Patel, and M. Taufer. Efficient Sodium Dodecyl Sulfate (SDS) Simulations on Multi-GPU Nodes of XSEDE High-end Clusters. In the Proceedings of the Eighth IEEE International Conference on e-Science and Grid Technologies (eScience), Beijing, China, October 2013.

Journal Papers

2014

S. Schlachter, S. Herbein, S. Ou, J. S. Logan, S. Patel, and M. Taufer. Pursuing Resource Utilization and Coordinated Progression in GPU-enabled Molecular Simulations. IEEE Design & Test of Computers, February 2014.

Workshop Papers

2016

R. Searles*, S. Herbein*, and S. Chandrasekaran. A Portable, High-Level Graph Analytics Framework Targeting Distributed, Heterogeneous Systems. In the Third Workshop on Accelerator Programming Using Directives (WACCPD), Salt Lake City, UT, November 2016. (*Equal contribution).

This is by no means an exhaustive list of the languages I know, just the ones I use most frequently.

Python

C

Bash

C++