
Emily Bourne developed core computational and geometry infrastructure for the gyselax/gyselalibxx scientific computing library, focusing on high-performance simulation workflows. She engineered GPU-accelerated solvers, tensor and vector type systems, and robust coordinate mapping frameworks using C++ and Kokkos, enabling scalable, accurate physics simulations. Her work included modernizing build systems with CMake, strengthening CI/CD pipelines, and refactoring APIs for clarity and maintainability. By integrating MPI for distributed runs and automating profiling and documentation, Emily improved both runtime efficiency and developer experience. Her contributions demonstrated technical depth in numerical methods, code organization, and performance optimization, resulting in a reliable, extensible codebase.

October 2025: Focused on stabilizing and accelerating development across gyselalibxx by delivering tooling improvements, API extensions, safety fixes, and documentation enhancements. Key outcomes include a hardened CI/build environment, GPU safety checks to prevent undefined behavior, new DerivField index-range getters, runtime domain assertions for PolarSplines, and clearer, more consistent API/docs. The changes reduce CI flakiness, prevent critical runtime crashes, shorten onboarding, and improve API usability for downstream projects.
October 2025: Focused on stabilizing and accelerating development across gyselalibxx by delivering tooling improvements, API extensions, safety fixes, and documentation enhancements. Key outcomes include a hardened CI/build environment, GPU safety checks to prevent undefined behavior, new DerivField index-range getters, runtime domain assertions for PolarSplines, and clearer, more consistent API/docs. The changes reduce CI flakiness, prevent critical runtime crashes, shorten onboarding, and improve API usability for downstream projects.
In September 2025, the gyselax/gyselalibxx project delivered notable documentation and release improvements, focusing on reliability, traceability, and open science compliance. Key outcomes include stabilizing the documentation build, preparing the 0.3.0 release, and enhancing citation visibility. These work items reduce support overhead, improve developer and user trust, and position the project for ongoing growth.
In September 2025, the gyselax/gyselalibxx project delivered notable documentation and release improvements, focusing on reliability, traceability, and open science compliance. Key outcomes include stabilizing the documentation build, preparing the 0.3.0 release, and enhancing citation visibility. These work items reduce support overhead, improve developer and user trust, and position the project for ongoing growth.
August 2025 performance and reliability upgrade for gyselax/gyselalibxx. Delivered major component modernization, GPU acceleration, reliability enhancements, and comprehensive profiling/documentation improvements. These efforts improve maintainability, scalability, and runtime performance while reducing build and runtime risk.
August 2025 performance and reliability upgrade for gyselax/gyselalibxx. Delivered major component modernization, GPU acceleration, reliability enhancements, and comprehensive profiling/documentation improvements. These efforts improve maintainability, scalability, and runtime performance while reducing build and runtime risk.
July 2025 performance summary for gyselax/gyselalibxx. Focused on delivering high-value features, stabilizing numerical correctness, and improving developer experience. Key work spanned GPU-accelerated PolarSpline computations, enhanced documentation and release notes, API cleanup, and targeted robustness fixes across derivatives, tensor handling, and math utilities. The combined work delivered performance gains, easier debugging, clearer API boundaries, and stronger numerical reliability aligned with product goals.
July 2025 performance summary for gyselax/gyselalibxx. Focused on delivering high-value features, stabilizing numerical correctness, and improving developer experience. Key work spanned GPU-accelerated PolarSpline computations, enhanced documentation and release notes, API cleanup, and targeted robustness fixes across derivatives, tensor handling, and math utilities. The combined work delivered performance gains, easier debugging, clearer API boundaries, and stronger numerical reliability aligned with product goals.
June 2025 monthly performance-focused summary for gyselax/gyselalibxx. Focused on delivering high-impact features, improving numerical accuracy, enabling more efficient GPU-enabled workflows, and tightening test terminology to reduce confusion across the CI suite. The month highlighted cross-cutting improvements in coordinate mappings, solver interfaces, and hardware utilization, driving downstream business value in simulation accuracy, throughput, and maintainability.
June 2025 monthly performance-focused summary for gyselax/gyselalibxx. Focused on delivering high-impact features, improving numerical accuracy, enabling more efficient GPU-enabled workflows, and tightening test terminology to reduce confusion across the CI suite. The month highlighted cross-cutting improvements in coordinate mappings, solver interfaces, and hardware utilization, driving downstream business value in simulation accuracy, throughput, and maintainability.
May 2025 monthly summary for gyselax/gyselalibxx. This period focused on delivering core physics capabilities, modernizing the codebase, and strengthening CI/CD and documentation to accelerate production-readiness. Key outcomes include new operators, enhanced tensor/space handling, cross-compiler support, and stability improvements that drive business value by enabling more accurate simulations and faster release cycles.
May 2025 monthly summary for gyselax/gyselalibxx. This period focused on delivering core physics capabilities, modernizing the codebase, and strengthening CI/CD and documentation to accelerate production-readiness. Key outcomes include new operators, enhanced tensor/space handling, cross-compiler support, and stability improvements that drive business value by enabling more accurate simulations and faster release cycles.
April 2025 focused on performance, reliability, and geometry expansion in gyselalibxx. Key outcomes include batching the polar spline foot finder, storing the advection field in Vector, CI improvements via splitting CPU/GPU workflows, expanding polar advection to multiple geometries, and introducing coverage monitoring. Notable bug fixes included regex validation for library names and Cartesian-to-Circular equations corrections. These changes speed up throughput, reduce maintenance burden, and broaden the library's applicability, with improved test visibility and faster feedback cycles.
April 2025 focused on performance, reliability, and geometry expansion in gyselalibxx. Key outcomes include batching the polar spline foot finder, storing the advection field in Vector, CI improvements via splitting CPU/GPU workflows, expanding polar advection to multiple geometries, and introducing coverage monitoring. Notable bug fixes included regex validation for library names and Cartesian-to-Circular equations corrections. These changes speed up throughput, reduce maintenance burden, and broaden the library's applicability, with improved test visibility and faster feedback cycles.
March 2025 monthly summary for the gyselalibxx development effort. The team delivered a broad modernization of the Tensor/ND ecosystem, expanded MPI/GPU capabilities, and strengthened CI/documentation, all while improving reliability and code quality. The following highlights emphasize business value, performance, and technical leadership.
March 2025 monthly summary for the gyselalibxx development effort. The team delivered a broad modernization of the Tensor/ND ecosystem, expanded MPI/GPU capabilities, and strengthened CI/documentation, all while improving reliability and code quality. The following highlights emphasize business value, performance, and technical leadership.
February 2025: Delivered GPU-accelerated geometry workflows and foundational tensor/vector type enhancements in gyselalibxx, with targeted tests and CI improvements. Key features include porting core geometry components to GPU (Foot Finders and related interpolators), introducing a new tensor/vector type system and integrating it into the solver, and stabilizing interpolation point initialization to reduce rounding errors. Major CI/CD improvements added GPU testing workflow, a GitLab mirror, environment fixes, and explicit formatting standards, resulting in more reliable builds. Fixed critical build issues in VectorFields and norm_inf, and updated repository clone guidance for clearer onboarding. These efforts reduce runtime costs, improve numerical stability, and accelerate development feedback cycles, strengthening performance and maintainability.
February 2025: Delivered GPU-accelerated geometry workflows and foundational tensor/vector type enhancements in gyselalibxx, with targeted tests and CI improvements. Key features include porting core geometry components to GPU (Foot Finders and related interpolators), introducing a new tensor/vector type system and integrating it into the solver, and stabilizing interpolation point initialization to reduce rounding errors. Major CI/CD improvements added GPU testing workflow, a GitLab mirror, environment fixes, and explicit formatting standards, resulting in more reliable builds. Fixed critical build issues in VectorFields and norm_inf, and updated repository clone guidance for clearer onboarding. These efforts reduce runtime costs, improve numerical stability, and accelerate development feedback cycles, strengthening performance and maintainability.
January 2025: Key features delivered include Getting started documentation, host-prefix support in R-theta geometry with FieldRTheta default device, and extensive repo reorganization (move matrix functions to src/, relocate Gauss-Legendre to src/quadrature, polar splines relocation, and code cleanup such as removing the SLL folder and advection domain). Major bugs fixed include public_mirror reliability improvements and CI workflow fixes, plus documentation corrections. Overall impact: improved onboarding and developer experience, GPU-accelerated Poisson R-theta weak integrals boosting compute performance, and a more maintainable, reliable codebase. Technologies/skills demonstrated: GPU acceleration, modularization and refactoring, CMake/CI reliability, documentation discipline, and naming-convention standardization.
January 2025: Key features delivered include Getting started documentation, host-prefix support in R-theta geometry with FieldRTheta default device, and extensive repo reorganization (move matrix functions to src/, relocate Gauss-Legendre to src/quadrature, polar splines relocation, and code cleanup such as removing the SLL folder and advection domain). Major bugs fixed include public_mirror reliability improvements and CI workflow fixes, plus documentation corrections. Overall impact: improved onboarding and developer experience, GPU-accelerated Poisson R-theta weak integrals boosting compute performance, and a more maintainable, reliable codebase. Technologies/skills demonstrated: GPU acceleration, modularization and refactoring, CMake/CI reliability, documentation discipline, and naming-convention standardization.
December 2024/monthly summary for gyselax/gyselalibxx. Focus areas: CI automation, mapping enhancements, vector/mapping generalization, and integration of code branches culminating in improved stability, testability, and performance for geometry and simulation workflows. Key features delivered: - Set up GitHub CI for pull requests to enable automatic CI checks and faster feedback on PRs (commit 068e04afd8969c9400ccd3c3422a952cd7df2731). - Mappings: added is_curvilinear_2d_mapping_v check and inverse mapping helpers to improve validation and reliability (commits 0499ae21a7b00ad3d9cb99b4f4a55c94e49fdbc0 and f085958ebef89feac27268956eb9b9fdd1e296cf). - Integrate kokkos profiling regions for polar Poisson simulations to aid performance profiling and optimization (d11f1b1d0926b89bfe5337999cb1b69cfa7acb73). - Generalise VectorMapper class to broaden reuse and reduce code duplication (42a4dba38131d4bcc4c7853e42ed669fbf1595f7). - Merge/Integrate important branches into main: ebourne_vector_mapping (25bc61a0940a32eca6b327a0cd9df1f25e72f743) and ebourne_has_singular_o_point_inv_jacobian (c336e77c9ac0c116616a2ac57d4ef14be5eeaac4); introduction of has_singular_o_point_inv_jacobian_v for singular O-point inverse Jacobian checks (b258d8f47c13dcbba24d3230ec975decb9c4bc2f). - Default to Greville points for geometryXVx simulations (b7cc19977ec04e390f47ba31a91399d9dfbba7c0). Major bugs fixed: - Public mirror: ensure backticks in commit messages are handled correctly (44fe00435d04a1858de6f32091de568283a4bac3). - Remove template argument added in an earlier commit to fix build issues (!779) (1dd3963dabea42d332f5c7e94a6a631ef376a9da). - Various stability/fix commits related to documentation tests, GitHub workflow robustness, and convergence logging (e2303a2082a662062559a4e73e8259640f6e5bf5; eff51012f516c9c3390145c1f85b351996611b60; 4debd886e16cf5fcbaf41aa6dc39fe40d8853f96). Overall impact and accomplishments: - Improved release quality and developer productivity through automated PR validation and broader, reusable components. - Strengthened numerical mapping infrastructure and geometry handling, enabling more robust simulations and easier extension. - Streamlined integration of experimental branches, accelerating delivery of performance and reliability improvements. Technologies/skills demonstrated: - CI/CD (GitHub Actions), codebase integration, C++ class design and inheritance refactoring, mapping frameworks, performance profiling with Kokkos, static analysis tooling, and robust testing.
December 2024/monthly summary for gyselax/gyselalibxx. Focus areas: CI automation, mapping enhancements, vector/mapping generalization, and integration of code branches culminating in improved stability, testability, and performance for geometry and simulation workflows. Key features delivered: - Set up GitHub CI for pull requests to enable automatic CI checks and faster feedback on PRs (commit 068e04afd8969c9400ccd3c3422a952cd7df2731). - Mappings: added is_curvilinear_2d_mapping_v check and inverse mapping helpers to improve validation and reliability (commits 0499ae21a7b00ad3d9cb99b4f4a55c94e49fdbc0 and f085958ebef89feac27268956eb9b9fdd1e296cf). - Integrate kokkos profiling regions for polar Poisson simulations to aid performance profiling and optimization (d11f1b1d0926b89bfe5337999cb1b69cfa7acb73). - Generalise VectorMapper class to broaden reuse and reduce code duplication (42a4dba38131d4bcc4c7853e42ed669fbf1595f7). - Merge/Integrate important branches into main: ebourne_vector_mapping (25bc61a0940a32eca6b327a0cd9df1f25e72f743) and ebourne_has_singular_o_point_inv_jacobian (c336e77c9ac0c116616a2ac57d4ef14be5eeaac4); introduction of has_singular_o_point_inv_jacobian_v for singular O-point inverse Jacobian checks (b258d8f47c13dcbba24d3230ec975decb9c4bc2f). - Default to Greville points for geometryXVx simulations (b7cc19977ec04e390f47ba31a91399d9dfbba7c0). Major bugs fixed: - Public mirror: ensure backticks in commit messages are handled correctly (44fe00435d04a1858de6f32091de568283a4bac3). - Remove template argument added in an earlier commit to fix build issues (!779) (1dd3963dabea42d332f5c7e94a6a631ef376a9da). - Various stability/fix commits related to documentation tests, GitHub workflow robustness, and convergence logging (e2303a2082a662062559a4e73e8259640f6e5bf5; eff51012f516c9c3390145c1f85b351996611b60; 4debd886e16cf5fcbaf41aa6dc39fe40d8853f96). Overall impact and accomplishments: - Improved release quality and developer productivity through automated PR validation and broader, reusable components. - Strengthened numerical mapping infrastructure and geometry handling, enabling more robust simulations and easier extension. - Streamlined integration of experimental branches, accelerating delivery of performance and reliability improvements. Technologies/skills demonstrated: - CI/CD (GitHub Actions), codebase integration, C++ class design and inheritance refactoring, mapping frameworks, performance profiling with Kokkos, static analysis tooling, and robust testing.
Monthly summary for 2024-11 focused on gyselax/gyselalibxx workstream. Delivered substantial enhancements to numerical integration, improved performance visibility, and extended API surface for multipatch workflows, while driving stability through targeted bug fixes and code hygiene. All work reinforces the product's accuracy, scalability, and developer productivity. Key deliverables and outcomes: - Numerical integration enhancements: Implemented Simpson quadrature with trapezoidal extension, fixed trapezoid coefficients, and added support for user-defined uniform points, enabling more flexible, accurate quadrature for users. (Commit references: f28ca44ac9b22b26d7ef1ca9fc589df96b814724; ea97cac1c647ce680022c4045c886b58eea8497b; f689d88656c6912d0997adddb61023e0b1cdb285) - Profiling and performance instrumentation: Introduced kokkos regions and cmake options to facilitate targeted profiling and performance analysis in complex simulations. (Commit: 7795a1f0e7c6c2f056675e0a0d6717abf6f22a6f) - Crank-Nicolson timestepper: Added Crank-Nicolson timestepper support for multipatch objects, improving stability and accuracy of time integration in multi-region simulations. (Commit: ded4c22c7706b7c8ad3a144feb34db0693c83d5f) - Collision geometry cleanup and validation: Added assertions on collision properties and removed invalid 5D geometry to ensure physics validity and avoid downstream errors. (Commit: 5519c3cee8e69a9459c4139f12baedf1b3e6ba9a) - MultipatchBuilder API extension: Extended template arguments with BcTransition to enable richer boundary condition coupling in multipatch workflows. (Commit: 4757c2fbd9763558b3fa56e20223eb5bffcdaad8) Major achievements reflect an emphasis on delivering business value through accurate numerical methods, measurable performance tooling, safer geometry handling, and enhanced API capabilities for complex simulations. Top 3-5 achievements: - Numerical integration enhancements (Simpson with trapezoidal extension; user-defined uniform points; corrected coefficients) - Profiling-ready build scaffolding (kokkos regions, cmake options) - Crank-Nicolson timestepper for multipatch objects - Collision geometry cleanup and validation (assertions; removal of 5D geometry) - MultipatchBuilder API extension (BcTransition in template args)
Monthly summary for 2024-11 focused on gyselax/gyselalibxx workstream. Delivered substantial enhancements to numerical integration, improved performance visibility, and extended API surface for multipatch workflows, while driving stability through targeted bug fixes and code hygiene. All work reinforces the product's accuracy, scalability, and developer productivity. Key deliverables and outcomes: - Numerical integration enhancements: Implemented Simpson quadrature with trapezoidal extension, fixed trapezoid coefficients, and added support for user-defined uniform points, enabling more flexible, accurate quadrature for users. (Commit references: f28ca44ac9b22b26d7ef1ca9fc589df96b814724; ea97cac1c647ce680022c4045c886b58eea8497b; f689d88656c6912d0997adddb61023e0b1cdb285) - Profiling and performance instrumentation: Introduced kokkos regions and cmake options to facilitate targeted profiling and performance analysis in complex simulations. (Commit: 7795a1f0e7c6c2f056675e0a0d6717abf6f22a6f) - Crank-Nicolson timestepper: Added Crank-Nicolson timestepper support for multipatch objects, improving stability and accuracy of time integration in multi-region simulations. (Commit: ded4c22c7706b7c8ad3a144feb34db0693c83d5f) - Collision geometry cleanup and validation: Added assertions on collision properties and removed invalid 5D geometry to ensure physics validity and avoid downstream errors. (Commit: 5519c3cee8e69a9459c4139f12baedf1b3e6ba9a) - MultipatchBuilder API extension: Extended template arguments with BcTransition to enable richer boundary condition coupling in multipatch workflows. (Commit: 4757c2fbd9763558b3fa56e20223eb5bffcdaad8) Major achievements reflect an emphasis on delivering business value through accurate numerical methods, measurable performance tooling, safer geometry handling, and enhanced API capabilities for complex simulations. Top 3-5 achievements: - Numerical integration enhancements (Simpson with trapezoidal extension; user-defined uniform points; corrected coefficients) - Profiling-ready build scaffolding (kokkos regions, cmake options) - Crank-Nicolson timestepper for multipatch objects - Collision geometry cleanup and validation (assertions; removal of 5D geometry) - MultipatchBuilder API extension (BcTransition in template args)
Month 2024-10 performance summary for gyselax/gyselalibxx focusing on business value, robustness, and scalability across core computational components and the buildchain.
Month 2024-10 performance summary for gyselax/gyselalibxx focusing on business value, robustness, and scalability across core computational components and the buildchain.
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