Publications

Bartlett, Roscoe B.

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Bartlett, Roscoe B.; Galbreath, Zack G.

We describe the accomplishments jointly achieved by Kitware and Sandia over the fiscal years 2016 through 2020 to benefit the Advanced Scientific Computed (ASC) Advanced Technology Development and Mitigation (ATDM) project. As a result of our collaboration, we have improved the Trilinos and ATDM application developer experience by decreasing the time to build, making it easier to identify and resolve build and test defects, and addressing other issues . We have also reduced the turnaround time for continuous integration (CI) results. For example, the combined improvements likely cut the wall clock time to run automated builds of Trilinos posting to CDash by approximately 6x or more in many cases. We primarily achieved these benefits by contributing changes to the Kitware CMake/CTest/CDash suite of open source software development support tools. As a result, ASC developers can now spend more time improving code and less time chasing bugs. And, without this work, one can argue that the stabilization of Trilinos for the ATDM platforms would not have been feasible which would have had a large negative impact on an important internal FY20 L1 milestone.

Bartlett, Roscoe B.

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Bartlett, Roscoe B.

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Bartlett, Roscoe B.; Harvey, Evan C.; Frye, Joseph R.

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Bartlett, Roscoe B.

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Bartlett, Roscoe B.

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Bartlett, Roscoe B.

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Bartlett, Roscoe B.

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Proceedings - 2019 IEEE/ACM 14th International Workshop on Software Engineering for Science, SE4Science 2019

Bartlett, Roscoe B.; Frye, Joseph R.

The Sandia National Laboratories (SNL) Advanced Technology Development and Mitigation (ATDM) project focuses on R&D for exascale computational science and engineering (CSE) software. Exascale application (APP) codes are co-developed and integrated with a large number of 2^nd generation Trilinos packages built on top of Kokkos for achieving portable performance. These efforts are challenged by needing to develop and test on many unstable and constantly changing pre-exascale platforms using immature compilers and other system software. Challenges, experiences, and lessons learned are presented for creating stable development and integration workflows for these types of difficult projects. In particular, we describe automated workflows, testing, and integration processes as well as new tools and multi-team collaboration processes for effectively keeping a large number of automated builds and tests working on these unstable platforms.

Bartlett, Roscoe B.

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Hoekstra, Robert J.; Bartlett, Roscoe B.; Hammond, Simon D.; Cook, Jeanine C.; Dinge, Dennis D.; Frye, Joseph R.; Hughes, Clayton H.; Lin, Paul L.; Vaughan, Courtenay T.; Hammond, Simon D.

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Bartlett, Roscoe B.

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Bartlett, Roscoe B.

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Bartlett, Roscoe B.

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Toth, Alexander R.; Pawlowski, Roger P.; Bartlett, Roscoe B.

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Bartlett, Roscoe B.

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Ober, Curtis C.; Bartlett, Roscoe B.; Coffey, Todd S.; Pawlowski, Roger P.

Time integration is a central component for most transient simulations. It coordinates many of the major parts of a simulation together, e.g., a residual calculation with a transient solver, solution with the output, various operator-split physics, and forward and adjoint solutions for inversion. Even though there is this variety in these transient simulations, there is still a common set of algorithms and proce- dures to progress transient solutions for ordinary-differential equations (ODEs) and differential-alegbraic equations (DAEs). Rythmos is a collection of these algorithms that can be used for the solution of transient simulations. It provides common time-integration methods, such as Backward and Forward Euler, Explicit and Im- plicit Runge-Kutta, and Backward-Difference Formulas. It can also provide sensitivities, and adjoint components for transient simulations. Rythmos is a package within Trilinos, and requires some other packages (e.g., Teuchos and Thrya) to provide basic time-integration capabilities. It also can be cou- pled with several other Trilinos packages to provide additional capabilities (e.g., AztecOO and Belos for linear solutions, and NOX for non-linear solutions). The documentation is broken down into three parts: Theory Manual, User's Manual, and Developer's Guide. The Theory Manual contains the basic theory of the time integrators, the nomenclature and mathematical structure utilized within Rythmos, and verification results demonstrating that the designed order of accuracy is achieved. The User's Manual provides information on how to use the Rythmos, description of input parameters through Teuchos Parameter Lists, and description of convergence test examples. The Developer's Guide is a high-level discussion of the design and structure of Rythmos to provide information to developers for the continued development of capabilities. Details of individual components can be found in the Doxygen webpages. Notice: This document is a collection of notes gathered over many years, however its development has been dormant for the past several years due to the lack of funding. Pre-release copies of this document have circulated to internal Sandia developers, who have found it useful in their application development. Also external Sandia developers have made inquiries for additional Rythmos documentation. To make this documentation publicly available, we are releasing this documentation in an " as-is " condition. We apologize for its incomplete state and obvious lack of readability, however we hope that the information contained in this document will still be helpful to users in their application development.

Bartlett, Roscoe B.

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Pawlowski, Roger P.; Bartlett, Roscoe B.; Bettencourt, Matthew T.; Carleton, James B.; Conde, Sidafa C.; Cyr, Eric C.; Kim, Kyungjoo K.; Mota, Alejandro M.; Perego, Mauro P.; Shadid, John N.; Sjaardema, Gregory D.; Toth, Alexander R.; Bradley, Andrew M.; Spotz, William S.; Ober, Curtis C.; Kalashnikova, Irina

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Supercomputing Frontiers and Innovations

Bartlett, Roscoe B.; Demeshko, Irina; Gamblin, Todd; Hammond, Glenn E.; Heroux, Michael A.; Johnson, Jeffrey; Klinvex, Alicia M.; Li, Xiaoye; McInnes, Lois C.; Moulton, J.D.; Osei-Kuffuor, Daniel; Sarich, Jason; Smith, Barry; Willenbring, James M.; Yang, Ulrike M.

Extreme-scale computational science increasingly demands multiscale and multiphysics formulations. Combining software developed by independent groups is imperative: no single team has resources for all predictive science and decision support capabilities. Scientific libraries provide high-quality, reusable software components for constructing applications with improved robustness and portability. However, without coordination, many libraries cannot be easily composed. Namespace collisions, inconsistent arguments, lack of third-party software versioning, and additional difficulties make composition costly. The Extreme-scale Scientific Software Development Kit (xSDK) defines community policies to improve code quality and compatibility across independently developed packages (hypre, PETSc, SuperLU, Trilinos, and Alquimia) and provides a foundation for addressing broader issues in software interoperability, performance portability, and sustainability. The xSDK provides turnkey installation of member software and seamless combination of aggregate capabilities, and it marks first steps toward extreme-scale scientific software ecosystems from which future applications can be composed rapidly with assured quality and scalability.

Bartlett, Roscoe B.; Belcourt, Kenneth N.; Hooper, Russell H.; Schmidt, Rodney C.

The Lightweight Integrating Multi-physics Environment (LIME) is a software package for creating multi-physics simulation codes. Its primary application space is when computer codes are currently available to solve different parts of a multi-physics problem and now need to be coupled with other such codes. In this report we define a common domain language for discussing multi-physics coupling and describe the basic theory associated with multiphysics coupling algorithms that are to be supported in LIME. We provide an assessment of coupling techniques for both steady-state and time dependent coupled systems. Example couplings are also demonstrated.

Edwards, Harold C.; Arguello, Jose G.; Bartlett, Roscoe B.; Bouchard, Julie F.; Freeze, Geoffrey A.; Knupp, Patrick K.; Schultz, Peter A.; Urbina, Angel U.; Wang, Yifeng

The objective of the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation Waste Integrated Performance and Safety Codes (NEAMS Waste IPSC) is to provide an integrated suite of computational modeling and simulation (M&S) capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive-waste storage facility or disposal repository. To meet this objective, NEAMS Waste IPSC M&S capabilities will be applied to challenging spatial domains, temporal domains, multiphysics couplings, and multiscale couplings. A strategic verification and validation (V&V) goal is to establish evidence-based metrics for the level of confidence in M&S codes and capabilities. Because it is economically impractical to apply the maximum V&V rigor to each and every M&S capability, M&S capabilities will be ranked for their impact on the performance assessments of various components of the repository systems. Those M&S capabilities with greater impact will require a greater level of confidence and a correspondingly greater investment in V&V. This report includes five major components: (1) a background summary of the NEAMS Waste IPSC to emphasize M&S challenges; (2) the conceptual foundation for verification, validation, and confidence assessment of NEAMS Waste IPSC M&S capabilities; (3) specifications for the planned verification, validation, and confidence-assessment practices; (4) specifications for the planned evidence information management system; and (5) a path forward for the incremental implementation of this V&V plan.

Bartlett, Roscoe B.

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Bartlett, Roscoe B.

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