Papers › votess: A multi-target, GPU-capable, parallel Voronoi tessellator
votess: A multi-target, GPU-capable, parallel Voronoi tessellator
Samridh Dev Singh, Chris Byrohl, Dylan Nelson
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votess is a library for computing parallel 3D Voronoi tessellations on heterogeneous platforms, from CPUs and GPUs, to future accelerator architectures. To do so, it leverages the SYCL abstraction layer to achieve portability and performance across these architectures. The core library is an implementation of a Voronoi cell-by-cell computation algorithm, producing the geometry of the cells and their neighbor connectivity information, rather than a full combinatorial mesh data structure. This simplifies the Voronoi tessellation and makes it more suitable to data parallel architectures than alternatives such as sequential insertion or the Bowyer-Watson algorithm. The library demonstrates significant performance improvements over established single-threaded programs and serves as a foundational tool for performance-critical applications, such as on-the-fly computations in hydrodynamical codes.
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