Borderline Racing - Optimisation (breakdown)
James Marland
Proposed by Jan Mróz
Visit resource ↗Description
Borderline Racing - Optimisation is a James Marland case study on tuning a large Unreal scene with more than 2,500 actors. Topics include Nanite versus manual LOD trade-offs, cheap shared master materials via static switches, batch Asset Action utilities, and Insights-driven profiling.
Intermediate developers learning student-game optimization benefit from before-and-after reasoning tied to a real vertical slice.
Complements other Borderline Racing and Project UMBRAE optimization write-ups on the same portfolio.
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