wave4-ijobparallelfor-array-transform

To parallelize NativeArray transforms without ECS, use IJobParallelFor to distribute independent per-index work across worker threads. This approach accelerates CPU-heavy math-only operations on large arrays while avoiding entity component data patterns.

For IJobParallelFor NativeArray performance, start with a batchSize of 64 and profile to confirm speedup. A sensible batchSize reduces scheduling overhead, and measurable gains typically appear on large arrays exceeding 1000 elements.

Yes, Burst works with IJobParallelFor by optimizing simple arithmetic and SIMD-friendly operations. Structure your loops to be Burst-compatible, ensuring the job code writes only to the owning index to maintain safety and maximize throughput.

Your IJobParallelFor job may not speed up NativeArray processing if cross-index writes are present or the array is too small. Avoid cross-index writes, ensure work is independent per index, and verify your array is large enough for parallel gains.

You should avoid IJobParallelFor for NativeArray transformations if your operations have cross-index dependencies or involve ECS entity component data patterns. This approach fits only independent per-index math-only work on large non-entity arrays.