Erik W. Draeger

(he/him)

Portrait of  Erik W. Draeger
  • Title
    Group Leader
  • Email
    draeger1@llnl.gov
  • Phone
    (925) 423-3650
  • Organization
    COMP-CASC DIV-CENTER FOR APPLIED SCIENTIFIC COMPUTING DIVISION

Dr. Erik Draeger is the group leader of the Scientific Computing Group in the Center for Applied Scientific Computing. He is also the Director of the High Performance Computing Innovation Center (HPCIC) and the RADIUSS project at LLNL.  Previously, Dr. Draeger was the Deputy Director for Application Development for the DOE Exascale Computing Project and before that the developer of the LLNL qball branch of the open source Qbox code, a massively parallel first-principles molecular dynamics code originally written by Francois Gygi. Dr. Gygi and Dr. Draeger won the 2006 Gordon Bell award for sustained floating point performance on the Blue Gene/L supercomputer. He co-developed the Cardioid cardiac electrophysiology code, a highly scalable biology application used to model arrhythmias in human heart geometries at near-real time, and is one of the main developers of the HARVEY code, a Lattice Boltzmann fluid dynamics code used for circulatory modeling that was a 2015 Gordon Bell Award Finalist.

Dr. Draeger earned a Bachelor's degree in Physics from the University of California, Berkeley in 1995 and later earned a Master's and a Ph.D. in theoretical condensed matter physics from the University of Illinois, Urbana-Champaign in 2001, working with Professor David Ceperley on path integral Monte Carlo simulations of superfluid helium droplets and surfaces.

A Martin, G Liu et al. "Designing a GPU-Accelerated Communication Layer for Efficient Fluid-Structure Interaction Computations on Heterogeneous Systems." Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC24).

C Tanade, E Rakestraw et al. "Cloud computing to enable wearable-driven longitudinal hemodynamic maps." Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC23).

S Roychowdhury, ST Mahmud et al. "Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts."  Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC23).

E. W. Draeger, A. Siegel, "Exascale Was Not Inevitable; Neither Is What Comes Next", Computing in Science & Engineering 25 (3), 79-83 (2023).

A. Z. Yousef, E. W. Draeger et al.  "Low-Cost Post Hoc Reconstruction of HPC Simulations at Full Resolution."  2023 IEEE 13th Symposium on Large Data Analysis and Visualization (LDAV), 17-21.

J. K. Holmen, V. G. Vergara Larrea et al. "Strengthening the US Department of Energy’s Recruitment Pipeline: The DOE/NNSA Predictive Science Academic Alliance Program (PSAAP) Experience." Practice and Experience in Advanced Research Computing (PEARC), 137-144  (2023).

S. Roychowdhury, E. W. Draeger et al.  "Establishing metrics to quantify spatial similarity in spherical and red blood cell distributions."  J. Comp. Sci. 71, 02060 (2023).

W. Ladd, C. Jensen et al.  "Optimizing Cloud Computing Resource Usage for Hemodynamic Simulation."  2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

D. F. Puleri, S. Roychowdhury et al.  "High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory."  2022 IEEE International Conference on Cluster Computing (CLUSTER).

T. M. Evans, A. Siegel, et al.  "A survey of software implementations used by application codes in the Exascale Computing Project."  The International Journal of High Performance Computing Applications, Vol. 36(1) 5–12 (2022).

S. Roychowdhury, E. W. Draeger, A. Randles, "Establishing Metrics to Quantify Underlying Structure in Vascular Red Blood Cell Distributions".  Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13350.  Springer, Cham.

A. Dubey, L. C. McInnes et al., "Performance Portability in the Exascale Computing Project: Exploration Through a Panel Series," in Computing in Science & Engineering, vol. 23, no. 5, pp. 46-54, 1 Sept.-Oct. 2021.

J. Gounley, M. Vardhan et al. "Propagation Pattern for Moment Representation of the Lattice Boltzmann Method," in IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 3, pp. 642-653, 1 March 2022.

L. C. McInnes, M. A. Heroux, E. W. Draeger et al. "How community software ecosystems can unlock the potential of exascale computing." Nat Comput Sci 1, 92–94 (2021).

B. Feiger, J. Gounley et al. "Accelerating massively parallel hemodynamic models of coarctation of the aorta using neural networks." Sci Rep 10, 9508 (2020).

J. Ames, D. F. Puleri et al. "Multi-GPU Immersed Boundary Method Hemodynamics Simulations."  J. Comp. Sci. 44,101153 (2020).

F. Alexandar, A. Almgren et al. "Exascale applications:  skin in the game."  Philosophical Transactions of the Royal Society A 378 (2166), 20190056  (2020).

M. Vardhan, J. Gounley et al. "Moment representation in the lattice Boltzmann method on massively parallel hardware."  Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19).

G. Herschlag, J. Gounley, et al.  “Multi-physics simulations of particle tracking in arterial geometries with a scalable moving window algorithm”, 2019 IEEE International Conference on Cluster Computing (CLUSTER). Albuquerque, NM, 2019.

J. Ames, S. Rizzi, et al. “Low-Overhead In Situ Visualization Using Halo Replay”, 9th IEEE Symposium on Large Data Analysis and Visualization (LDAV). Vancouver, BC, 2019.

J. Gounley, E. W. Draeger, et al.  “Computing the ankle-brachial index with parallel computational fluid dynamics”, Journal of Biomechanics 82, 28-37 (2019).

M. T. Ong, H. Bhatia, et al.  “Complex ion dynamics in carbonate lithium-ion battery electrolytes”, J. Phys. Chem. C 121 (12), 6589-6595 (2017).

J.-L. Fattebert, D. Osei-Kuffuor, et al.  “Modeling dilute solutions using first-principles molecular dynamics: computing more than a million atoms with over a million cores”, Proceedings of the ACM/IEEE Supercomputing 2016 Conference.  Gordon Bell award finalist.

E. W. Draeger, X. Andrade, et al. "Massively Parallel First-Principles Simulation of Electron Dynamics in Materials."  IPDPS 2016 (Best Paper, Applications).

A. Lim, W. M. C. Foulkes, et al"Electron Elevator: Excitations across the Band Gap via a Dynamical Gap State."  Phys. Rev. Lett. 116, 043201 (2016).

A. Randles, E. W. Draeger, et al. "Massively Parallel Models of the Human Circulatory System", Proceedings of the ACM/IEEE Supercomputing 2015 Conference.  Gordon Bell award finalist.

A. Randles, E.W. Draeger, and P.E. Bailey. "Massively Parallel Simulations of Hemodynamics in the Human Vasculature." Journal of Computational Science 9, 70-75 (2015).  (Best Paper Winner, ICCS 2015)

M. T. Ong, O. Verners, et al.  "Lithium Ion Solvation and Diffusion in Bulk Organic Electrolytes from First-Principles and Classical Reactive Molecular Dynamics", J. Phys. Chem. B 115, 1535-1545 (2015).

A. Schleife, E. W. Draeger, et al. "Quantum Dynamics Simulation of Electrons in Materials on High-Performance Computers", Computing in Science & Engineering, 16 (5), 54-60, (2014).

D. F. Richards, J. N. Glosli, et al.  “Towards real-time simulation of cardiac electrophysiology in a human heart at high resolution”, Computer Methods in Biomechanics and Biomedical Engineering 16, 802 (2013).

A. A. Mirin, D. F. Richards, et al.“Toward real-time modeling of human heart ventricles at cellular resolution: simulation of drug-induced arrhythmias”, Proceedings of the ACM/IEEE Supercomputing 2012 Conference.  Gordon Bell Award Finalist.

A. Bhatele, T. Gamblin, et al., “Mapping applications with collectives over sub-communicators on torus networks”, Proceedings of the ACM/IEEE Supercomputing 2012 Conference.

A. Schleife, E. W. Draeger, et al., “Plane-wave pseudopotential implementation of explicit integrators for time-dependent Kohn-Sham equations in large-scale simulations”, J. Chem. Phys. 137, 22A546 (2012).

B. R. de Supinski , M. Schultz, E. W. Draeger, "Flexible Tools Supporting a Scalable First-Principles MD Code" in Scientific Computer Performance, David H. Bailey, Robert F. Lucas and Samuel Williams, editors, Taylor and Francis, New York, 2010

D. F. Richards, J. N. Glosli, et al., “Beyond Homogeneous Decomposition: Scaling Long-Range Forces on Massively Parallel Architectures”, Proceedings of the ACM/IEEE Supercomputing 2009 Conference.  Gordon Bell award finalist.

B. de Supinski, M. Schultz, et al., “BlueGene/L Applications: Parallelism on a Massive Scale”, Int. J. High Perform C. 22, 33 (2008).

François Gygi, Erik W. Draeger, et al., “Large-Scale Electronic Structure Calculations of High-Z Metals on the BlueGene/L Platform”, Proceedings of the ACM/IEEE Supercomputing 2006 Conference.  Gordon Bell award winner. 

François Gygi, Erik W. Draeger, et al., “Large-Scale First-Principles Molecular Dynamics Simulations on the BlueGene/L Platform using the Qbox Code”, Proceedings of the ACM/IEEE Supercomputing 2005 Conference.  Gordon Bell award finalist.