Publications

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Productivity and Sustainability Improvement Planning (PSIP) is a lightweight, iterative workflow that allows software development teams to identify development bottlenecks and track progress to overcome them. In this paper, we present an overview of PSIP and how it compares to other software process improvement (SPI) methodologies, and provide two case studies that describe how the use of PSIP led to successful improvements in team effectiveness and efficiency.

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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.

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The Trilinos Project produces, maintains and distributes a large collection of reusable, parallel scientific libraries. Docker provides container technologies that support compilation, packaging, distribution and execution of software on Linux, Mac OS and Windows systems, with emerging support for Cray platforms. In this short article we describe recent efforts to explore the potential for using Docker in a variety of settings to enhance several Trilinos Project workflows. The technical foundation for this article is presented in an Honors thesis of one of the authors.

"BLIS: A Framework for Rapidly Instantiating BLAS Functionality" includes single-platform BLIS performance results for both level-2 and level-3 operations that is competitive with OpenBLAS, ATLAS, and Intel MKL. A detailed description of the configuration used to generate the performance results was provided to the reviewer by the authors. All the software components used in the comparison were reinstalled and new performance results were generated and compared to the original results. After completing this process, the published results are deemed replicable by the reviewer.

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The Trilinos Project is an effort to facilitate the design, development, integration and ongoing support of mathematical software libraries within an object-oriented framework. It is intended for large-scale, complex multiphysics engineering and scientific applications [2, 4, 3]. Epetra is one of its basic packages. It provides serial and parallel linear algebra capabilities. Before Trilinos version 11.0, released in 2012, Epetra used the C++ int data-type for storing global and local indices for degrees of freedom (DOFs). Since int is typically 32-bit, this limited the largest problem size to be smaller than approximately two billion DOFs. This was true even if a distributed memory machine could handle larger problems. We have added optional support for C++ long long data-type, which is at least 64-bit wide, for global indices. To save memory, maintain the speed of memory-bound operations, and reduce further changes to the code, the local indices are still 32-bit. We document the changes required to achieve this feature and how the new functionality can be used. We also report on the lessons learned in modifying a mature and popular package from various perspectives design goals, backward compatibility, engineering decisions, C++ language features, effects on existing users and other packages, and build integration.

The Trilinos Project is an effort to develop algorithms and enabling technologies within an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific problems. A new software capability is introduced into Trilinos as a package. A Trilinos package is an integral unit and, although there are exceptions such as utility packages, each package is typically developed by a small team of experts in a particular algorithms area such as algebraic preconditioners, nonlinear solvers, etc. The Trilinos Developers SQE Guide is a resource for Trilinos package developers who are working under Advanced Simulation and Computing (ASC) and are therefore subject to the ASC Software Quality Engineering Practices as described in the Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan: ASC Software Quality Engineering Practices Version 3.0 document [1]. The Trilinos Developer Policies webpage [2] contains a lot of detailed information that is essential for all Trilinos developers. The Trilinos Software Lifecycle Model [3] defines the default lifecycle model for Trilinos packages and provides a context for many of the practices listed in this document.