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PTLAS enables the\nefficient reuse of previously constructed parts of the acceleration\nstructure, resulting in much faster build times and supporting a higher\nnumber of instances. From the standpoint of ray tracing shaders and\npipelines, PTLAS functions the same way as the current TLAS.",{"type":10,"tag":11,"props":51,"children":52},{},[53],{"type":15,"value":54},"A PTLAS differs from a non-partitioned TLAS by\norganizing instances into partitions. The PTLAS build process has two\nstages: first, it creates an acceleration structure for each partition\nby grouping instances within it, and second, it combines these partition\nstructures into a single acceleration structure, similar to a TLAS.",{"type":10,"tag":11,"props":56,"children":57},{},[58],{"type":15,"value":59},"The performance benefits of PTLAS depend on how instances and partitions\nare organized. Grouping many instances into fewer partitions may enhance\ntrace performance but slow down rebuilds. 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However, instances in the global partition\nstill affect build performance, so once they are stable, they should be\nmoved to a spatially optimized, non-global partition.",{"type":10,"tag":11,"props":66,"children":67},{},[68],{"type":15,"value":69},"To handle large worlds requiring more precision than 32-bit\nfloating-point numbers offer, the PTLAS supports efficient\npartition translation. Typically, applications manage precision by\npositioning the world center close to the camera, but partition\ntranslation allows an additional translation of instances during\nconstruction without altering their stored transform. This method lets\ninstance transforms be stored relative to their partitions, with the\ntranslation applied to achieve accurate world positions. This approach\nmaintains higher precision with smaller floating-point numbers until the\nstructure is built. Efficient updates to world space coordinates can be\nmade without rebuilding the entire PTLAS. 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