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Description
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This paper proposes a novel efficient algorithm to calculate a 2.5D shadow map based on a coherent math-ematic formula concerning the sun's position in a specific location, date and time. This work attempts to improve the understanding of the underlying equations and data structures from an analytical, a geometric and a dynamical systems perspective. By using scalable tensor data structure and inherent parallelism offered by data-flow based implementation the proof of concept is developed to test the technical feasibility of the proposed algorithm. Results show noticeable and significant improvements in overall performance keeping accuracy at negligible differences. (2019-01-01)
***This entry has been automatically imported via OpenAlex by LIST harvest scripts. Please refer to https://doi.org/10.5220/0007748602740281 for the original and latest version of the publication*** (2026-07-01)
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Keyword
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Parallelism (grammar), Shadow (psychology), Scalability, Computer science, Algorithm, Perspective (graphical), Position (finance), Tensor (intrinsic definition), Work (physics), Mathematics, Parallel computing, Artificial intelligence, Database, Engineering |