Though also, parallel processing strings and other non-numeric data on that level of granularity is, IME, typically less performant. The parallelism rarely manages to offset the performance penalties incurred by decomposing the problem in a parallel-friendly way. Even on a single machine you’ve got to think about whether organizing the data in a parallel-friendly way also makes it less cache-friendly. For example, a linked list of Unicode code points is 12 bytes per character, and each character might be on a completely different cache line. Depending on language a UTF8 buffer might be 1/10 the size and have a much more compact layout in memory.