Cody Balos is a computational scientist and research software engineer in the Center for Applied Scientific Computing (CASC). He joined the lab in 2018. Cody's work focuses on the research and development of scalable algorithms and software for high-performance scientific computing. He is core developer and team member of the SUNDIALS project as well as the Extreme-scale Scientific Software Development Kit (xSDK). He is also member of the FASTMath SciDAC-5 Institute and NUCLEI SciDAC-5 partnership project. Cody has experience with a wide variety of scientific applications including ones from combustion, nuclear physics and fusion energy sciences.

Before joining LLNL, Cody worked on enterprise web applications for a healthcare company. He holds a B.S. in Computer Engineering from the University of the Pacific as well as a M.S. in Computational and Applied Mathematics from the University of Washington.

Research Interests

• Numerical time integration algorithms at extreme scales / on next-generation hardware
• Numerical algorithms for multiscale and multiphysics problems
• Scientific machine learning
• Software engineering practices in scientific software, particularly math libraries

M.S. Computational and Applied Mathematics, University of Washington, Seattle, Washington

B.S. Computer Engineering, University of the Pacific, Stockton, California

Selected Publications

See https://scholar.google.com/citations?hl=en&user=wMS-K7oAAAAJ for a full list.

2022

• Balos, C. J., Luszczek, P., Osborn, S., Willenbring, J., & Yang, U. M. (2022). Challenges of and Opportunities for a Large Diverse Software Team. Computing in Science & Engineering. 10.1109/MCSE.2022.3172873. 
• Balos, C. J. (2022). Reproduced Computational Results Report for “Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing”. ACM Transactions on Mathematical Software (TOMS), 48(1), 1-7. https://doi.org/10.1145/3480936.

2021

• Aggarwal, I., Kashi, A., Nayak, P., Balos, C. J., Woodward, C. S., & Anzt, H. (2021, November). Batched Sparse Iterative Solvers for Computational Chemistry Simulations on GPUs. In 2021 12th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA) (pp. 35-43). IEEE. 10.1109/ScalA54577.2021.00010.

• Balos, C. J., Gardner, D. J., Woodward, C. S., & Reynolds, D. R. (2021). Enabling GPU accelerated computing in the SUNDIALS time integration library. Parallel Computing, 102836. https://doi.org/10.1016/j.parco.2021.102836. 

2020

• D.S. Khan, C.J. Balos, et al. A2Cloud‐RF: A random forest based statistical framework to guide resource selection for high‐performance scientific computing on the cloud. Concurrency Computat Pract Exper. 2020; 32:e5942. https://doi.org/10.1002/cpe.5942

2018

• C. Balos, D. De La Vega, Z. Abuelhaj, C. Kari, D. Mueller and V. K. Pallipuram, "A2Cloud: An Analytical Model for Application-to-Cloud Matching to Empower Scientific Computing," 2018 IEEE 11th International Conference on Cloud Computing (CLOUD), San Francisco, CA, USA, 2018, pp. 548-555.

Presentations

2022

• C.S. Woodward, C.J. Balos,  D.J. Gardner, and D.R. Reynolds, "Overview and Use of New Features in the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers," In Exascale Computing Project Annual Meeting 2022, Virtual. May 2-May 6.

2021

• C.J. Balos, D.J. Gardner, D.R. Reynolds, and C.S. Woodward, "From API Design to Tuning GPU Kernels: Experiences Preparing Sundials for use in Diverse Applications at Exascale," In 2021 SIAM Conference on Computational Science and Engineering (CSE21), Virtual, March 1- March 5 2021

2020

• C.J. Balos, D.J. Gardner, D.R. Reynolds, C.S. Woodward, "Preparing the SUNDIALS Library for Heterogeneous Architectures," In 2020 Performance, Portability, and Productivity in HPC Forum, Virtual, September 1-September 2 2020
• C.J. Balos, D.J. Gardner, D.R. Reynolds, C.S. Woodward, and A.C. Hindmarsh, "Strategies, Challenges, and Lessons Learned in Developing GPU Support for SUNDIALS," In 2020 SIAM Conference on Parallel Processing (PP20), Seattle, WA, USA, February 12-February 15 2020
• C.S. Woodward, D.R. Reynolds, D.J. Gardner, and C.J. Balos, "Introduction to the Capabilities and Use of the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers," In Exascale Computing Project Annual Meeting 2020, Houston, TX, USA, February 3-February 6 2020

2019

• C.S. Woodward, D.R. Reynolds, D.J. Gardner, and C.J. Balos, "Introduction to the Capabilities and Use of the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers," In Exascale Computing Project Annual Meeting 2019, Houston, TX, USA, January 14-January 18 2019

Posters/Other

2021

• Francisquez, M., Ernst, D., Reynolds, D., & Balos, C. (2021). A 2D gyrofluid model for coupled toroidal ITG/ETG multiscale turbulence and its comparison to gyrokinetics. In APS Division of Plasma Physics Meeting Abstracts (Vol. 2021, pp. ZO08-011).

2020

• Francisquez, Manaure, Darin R. Ernst, Daniel Reynolds, and Cody Balos. "Cross-Scale Interactions in Multi-scale Turbulence Explored Through a Reduced Model." In APS Division of Plasma Physics Meeting Abstracts, vol. 2020, pp. VP11-020. 2020.

2019

• C.J. Balos, D.J. Gardner, D.R. Reynolds, C.S. Woodward, S. Peles, A.C. Hindmarsh, "Shaping a Sustainable SUNDIALS: Applying Software Sustainability Practices to a CSE Library,'' In 2019 SIAM Conference on Computational Science and Engineering (CSE'19), Spokane, WA, USA, February 25-March 1 2019.

• 2023 SIAM/ACM Prize in Computational Science and Engineering. Awarded to the core developers of SUNDIALS.