Presenters-0613: Difference between revisions
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|CSDMS meeting abstract presentation=Developers of solvers for PDE-based models and other computationally intensive tasks are confronted with myriad complexity, from science requirements to algorithms and data structures to GPU programming models. We will share a fresh approach that has delivered order of magnitude speedups in computational mechanics workloads, minimizing incidental complexity while offering transparency and extensibility. In doing so, we'll examine the PETSc and libCEED libraries, validate performance models, and discuss sustainable architecture for community development. We'll also check out Enzyme, an LLVM-based automatic differentiation tool that can be used with legacy code and multi-language projects to provide adjoint (gradient) capabilities. | |CSDMS meeting abstract presentation=Developers of solvers for PDE-based models and other computationally intensive tasks are confronted with myriad complexity, from science requirements to algorithms and data structures to GPU programming models. We will share a fresh approach that has delivered order of magnitude speedups in computational mechanics workloads, minimizing incidental complexity while offering transparency and extensibility. In doing so, we'll examine the PETSc and libCEED libraries, validate performance models, and discuss sustainable architecture for community development. We'll also check out Enzyme, an LLVM-based automatic differentiation tool that can be used with legacy code and multi-language projects to provide adjoint (gradient) capabilities. | ||
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Latest revision as of 16:34, 11 June 2025
CSDMS 2023: Patterns and Processes Across Scales
Building solvers for sustainable performance
Abstract
Developers of solvers for PDE-based models and other computationally intensive tasks are confronted with myriad complexity, from science requirements to algorithms and data structures to GPU programming models. We will share a fresh approach that has delivered order of magnitude speedups in computational mechanics workloads, minimizing incidental complexity while offering transparency and extensibility. In doing so, we'll examine the PETSc and libCEED libraries, validate performance models, and discuss sustainable architecture for community development. We'll also check out Enzyme, an LLVM-based automatic differentiation tool that can be used with legacy code and multi-language projects to provide adjoint (gradient) capabilities.
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Of interest for: