xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit

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

doi:10.14529/jsfi170104

Cited by 11 publications

(7 citation statements)

References 15 publications

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“…ECP used the existing math libraries SDK, the xSDK, as a model to establish SDK efforts in the areas of Programming Models and Runtimes (PMR), Data and Visualization, Development Tools, Software Ecosystems (which E4S was part of), workflows, and code analysis and data mining tools. The xSDK began in 2014 [9] as part of the initial Interoperable Design of Extreme-scale Application Software (IDEAS) project 2 . The first xSDK release in 2016, version 0.1, contained six software products.…”

Section: Theme/feature/departmentmentioning

confidence: 99%

Providing a Flexible and Comprehensive Software Stack Via Spack, an Extreme-Scale Scientific Software Stack, and Software Development Kits

Willenbring,

Shende,

Gamblin

2024

Comput. Sci. Eng.

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To manage the complex demands of modern high-performance computing (HPC), software applications increasingly depend on software developed by other teams, often at other institutions. An HPC software ecosystem approach is required to support dependencies on third-party scientific software. An ecosystem approach provides layers of activity above the individual software product level that promote interoperability, quality improvement, porting, testing and deployment. The U.S. Exascale Computing Project (ECP) developed its HPC software ecosystem using a three-pronged approach. First, ECP adopted and invested in Spack, a package manager designed to handle complex HPC package dependencies. Second, ECP created the Extreme Scale Scientific Software Stack (E4S), an effort that supports developing, deploying and running scientific applications on HPC platforms. Third, ECP supported software product communities, or Software Development Kits (SDKs) to develop and promote best practices, improve software interoperability, and other collaborative efforts. This paper describes ECP contributions to HPC software ecosystem challenges.

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Section: Theme/feature/departmentmentioning

confidence: 99%

Providing a Flexible and Comprehensive Software Stack Via Spack, an Extreme-Scale Scientific Software Stack, and Software Development Kits

Willenbring,

Shende,

Gamblin

2024

Comput. Sci. Eng.

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“…The discretized system of linear equations formulated in Section 3, in conjunction with the constitutive model described in Section 2.3 were implemented using deal.II version 9.0 [11], an open-source finite element library. This library offers a number of paradigms by which to parallelize a finite-element code, and as a member of the xSDK (Extreme-scale Scientific Software Development Kit) ecosystem [15] aims to support exascale computing. In this work we employ deal.II's interface to p4est [16] library to perform a standard domain decomposition, whereafter each MPI process "owns" only a subset of elements and the mesh is distributed across all MPI processes.…”

Section: Description Of the Utilized Numerical Frameworkmentioning

confidence: 99%

A matrix‐free approach for finite‐strain hyperelastic problems using geometric multigrid

Davydov

Pelteret

Arndt

et al. 2020

Numerical Meth Engineering

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The performance of finite element solvers on modern computer architectures is typically memory bound for sufficiently large problems. The main cause for this is that loading matrix elements from RAM into CPU cache is significantly slower than performing the arithmetic operations when solving the problem. In order to improve the performance of iterative solvers within the high-performance computing context, so-called matrix-free methods are widely adopted in the fluid mechanics community, where matrix-vector products are computed on-the-fly.To date, there have been few (if any) assessments into the applicability of the matrix-free approach to problems in solid mechanics. In this work, we perform an initial investigation on the application of the matrix-free approach to problems in quasi-static finite-strain hyperelasticity to determine whether it is viable for further extension. Specifically, we study different numerical implementations of the finite element tangent operator, and determine whether generalized methods of incorporating complex constitutive behavior might be feasible. In order to improve the convergence behavior of iterative solvers, we also propose a method by which to construct level tangent operators and employ them to define a geometric multigrid preconditioner. The performance of the matrix-free operator and the ge- * Corresponding author. ometric multigrid preconditioner is compared to the matrix-based implementation with an algebraic multigrid preconditioner on a single node for a representative numerical example of a heterogeneous hyperelastic material in two and three dimensions. We conclude that the application of matrix-free methods to finite-strain solid mechanics is promising, and that is it possible to develop numerically efficient implementations that are independent of the hyperelastic constitutive law.

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“…This section gives an overview of the status of our software, most of which is now publicly available under a three-clause BSD license. Many of the efforts have been integrated in the PHIST library so that they can easily be used together, and we made part of the software available in larger contexts like Spack [27] and the extreme-scale scientific software development kit xSDK [11]. The xSDK is an effort to define common standards for high-performance, scientific software in terms of software engineering and interoperability.…”

Section: Scalable and Sustainable Softwarementioning

confidence: 99%

“…The former allows using it with any backend supported by PHIST. • CRAFT is available stand-alone 11 or (in a fixed version) as part of PHIST.…”

Section: Scalable and Sustainable Softwarementioning

confidence: 99%

ESSEX: Equipping Sparse Solvers For Exascale

Alappat¹,

Alvermann²,

Basermann³

et al. 2020

Software for Exascale Computing - SPPEXA 2016-2019

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The ESSEX project has investigated programming concepts, data structures, and numerical algorithms for scalable, efficient, and robust sparse eigenvalue solvers on future heterogeneous exascale systems. Starting without the burden of legacy code, a holistic performance engineering process could be deployed across the traditional software layers to identify efficient implementations and guide sustainable software development. At the basic building blocks level, a flexible MPI+X programming approach was implemented together with a new sparse data structure (SELL-C-σ) to support heterogeneous architectures by design. Furthermore, ESSEX focused on hardware-efficient kernels for all relevant architectures and efficient data structures for block vector formulations of the eigensolvers. The algorithm layer addressed standard, generalized, and nonlinear eigenvalue problems and provided some widely usable solver implementations including a block Jacobi-Davidson algorithm, contour-based integration schemes, and filter polynomial approaches. Adding to the highly efficient kernel implementations, algorithmic advances such as adaptive precision, optimized filtering coefficients, and preconditioning have further improved time to solution. These developments

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xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit

Cited by 11 publications

References 15 publications

Providing a Flexible and Comprehensive Software Stack Via Spack, an Extreme-Scale Scientific Software Stack, and Software Development Kits

Providing a Flexible and Comprehensive Software Stack Via Spack, an Extreme-Scale Scientific Software Stack, and Software Development Kits

A matrix‐free approach for finite‐strain hyperelastic problems using geometric multigrid

ESSEX: Equipping Sparse Solvers For Exascale

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