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    A new task-parallel approach proactively computes mesh connectivity for unstructured meshes, improving performance. The Accelerated Clustered TOPOlogical (ACTOPO) data structure offers memory efficiency and speedups.

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    Area of Science:

    • Computer Science
    • Computational Geometry
    • Data Structures

    Background:

    • Unstructured meshes have irregularly distributed data points, making connectivity computation time-consuming and memory-intensive.
    • Existing dynamic data structures compute connectivity on-the-fly, which slows down algorithms and impacts performance.
    • Current data-parallel models limit threads to identical instructions, hindering parallel processing efficiency.

    Purpose of the Study:

    • To introduce a novel task-parallel approach for proactive mesh connectivity computation.
    • To develop a new data structure, Accelerated Clustered TOPOlogical (ACTOPO), that supports algorithms requiring mesh connectivity.
    • To enhance the performance of algorithms operating on unstructured meshes.

    Main Methods:

    • Implemented a task-parallel approach where threads execute different functions concurrently.
    • Developed the Accelerated Clustered TOPOlogical (ACTOPO) data structure to manage mesh connectivity proactively.
    • Compared ACTOPO against state-of-the-art memory-efficient (TTK CompactTriangulation) and time-efficient (TTK ExplicitTriangulation) structures.

    Main Results:

    • ACTOPO demonstrates comparable memory usage to TTK CompactTriangulation.
    • ACTOPO achieves up to a 5x speedup compared to TTK CompactTriangulation.
    • ACTOPO provides performance similar to TTK ExplicitTriangulation while utilizing only half the memory.

    Conclusions:

    • The task-parallel approach and ACTOPO data structure effectively address the challenges of unstructured mesh connectivity.
    • ACTOPO offers a balanced solution, combining memory efficiency and significant time performance improvements.
    • This approach benefits algorithms requiring mesh connectivity, paving the way for more efficient scientific computations.