
Worked on the pyccel/psydac repository to deliver advanced features for finite element and isogeometric analysis, focusing on performance and scalability. Developed and optimized sum factorization algorithms for 3D bilinear form assembly, introduced Dirichlet boundary projectors, and implemented LST preconditioners for mass matrices, all in Python. Enhanced matrix operations and numerical methods, improving both runtime efficiency and code maintainability. Addressed a critical discretization bug to ensure reliable matrix assembly workflows. Contributed comprehensive documentation, robust unit tests, and performance tracking tools, demonstrating expertise in scientific computing, algorithm development, and collaborative software engineering within a complex numerical analysis codebase.
February 2026 performance-focused month for pyccel/psydac. The core delivery centers on the Matrix Assembly - Sum Factorization workflow and associated reliability improvements, with targeted fixes in discretization logic and documentation enhancements to support performance tracking.
February 2026 performance-focused month for pyccel/psydac. The core delivery centers on the Matrix Assembly - Sum Factorization workflow and associated reliability improvements, with targeted fixes in discretization logic and documentation enhancements to support performance tracking.
December 2025: Implemented LST preconditioners for isogeometric mass matrices with optional Dirichlet BCs, delivering faster iterative solves and scalable performance. Core contributions include construct_LST_preconditioner() and LST_preconditioners() across multiple mass matrices, backed by functools.lru_cache for caching. Refactored supporting code into the library (psydac.linalg.direct_solvers; matrix_to_bandsolver -> BandedSolver.from_stencil_mat_1d) and added practical usage example and comprehensive tests validating efficiency. Business impact: reduced solve times for mass-matrix systems, enabling larger simulations and more reliable performance in isogeometric workflows. Technologies/skills demonstrated: Python, SciPy LinearOperator, isogeometric analysis, preconditioning techniques, test automation, and collaborative development.
December 2025: Implemented LST preconditioners for isogeometric mass matrices with optional Dirichlet BCs, delivering faster iterative solves and scalable performance. Core contributions include construct_LST_preconditioner() and LST_preconditioners() across multiple mass matrices, backed by functools.lru_cache for caching. Refactored supporting code into the library (psydac.linalg.direct_solvers; matrix_to_bandsolver -> BandedSolver.from_stencil_mat_1d) and added practical usage example and comprehensive tests validating efficiency. Business impact: reduced solve times for mass-matrix systems, enabling larger simulations and more reliable performance in isogeometric workflows. Technologies/skills demonstrated: Python, SciPy LinearOperator, isogeometric analysis, preconditioning techniques, test automation, and collaborative development.
Delivered two core features in pyccel/psydac that add robust boundary-condition support and accelerate linear algebra workflows, with comprehensive tests and performance gains on preconditioner computations. These changes improve accuracy for Dirichlet BCs on multi-patch FE spaces, and significantly speed up LST preconditioner paths, enabling larger-scale simulations.
Delivered two core features in pyccel/psydac that add robust boundary-condition support and accelerate linear algebra workflows, with comprehensive tests and performance gains on preconditioner computations. These changes improve accuracy for Dirichlet BCs on multi-patch FE spaces, and significantly speed up LST preconditioner paths, enabling larger-scale simulations.
September 2025: Delivered a performance-focused enhancement for 3D bilinear form assembly in psydac by introducing a sum-factorization-based path for volumes, including new modules, tests, and documentation. The change preserves backward compatibility and provides a toggle to revert to the former element-by-element assembly. Architecture refactor improved code clarity and test coverage, with discretization adjusted to select the new path when sum_factorization is requested. This work positions the project for scalable simulations in 3D isogeometric analysis, with measurable performance gains anticipated from sum-factorization techniques.
September 2025: Delivered a performance-focused enhancement for 3D bilinear form assembly in psydac by introducing a sum-factorization-based path for volumes, including new modules, tests, and documentation. The change preserves backward compatibility and provides a toggle to revert to the former element-by-element assembly. Architecture refactor improved code clarity and test coverage, with discretization adjusted to select the new path when sum_factorization is requested. This work positions the project for scalable simulations in 3D isogeometric analysis, with measurable performance gains anticipated from sum-factorization techniques.

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