"For example, what if the parallel sums are of different lengths? On GPUs, fast parallel reductions only work when inputs all have the same length. [...] Vexpr’s vectorizer groups the inputs by length and performs a reduced number of operations—one for each unique length."

I'm surprised this is necessary, I thought modern vectorization on both CPU and GPU handled heterogenous vectorization cases like this handily with conditional execution (on SMT GPUs) or mask registers (on SIMD CPUs)