If the question appears vague, I'll gladly clarify. It's not tied to a programing language. If there is a language dependency in the answer, one can place it in the context of Python, R, VB, Mathematica, Matlab, or seek clarification.
Are there situations when a vectorized (aka element-wise application of a function or array programming (AP)) computation cannot be parallelized?
When coding, I frequently replace loops with a vectorized computation, if possible. At times, it's an interesting exercise or (arguably) makes the code more readable. Other times, in hopes of parallelizing it in the future, if need be.
Is there a constraint that would prevent me from parallelizing a vectorized code.
Note that even seemingly tight loop can be vectorized. For example, cumulative sum of vector elements
(1, 2, 3) can be transformed to a matrix form
((1,1,1),(0,2,2),(0,0,3)) and then vectorization is done as column sums producing the desired
(1,3,6) cumulative sum. However, vectorization of fibonacci sequence is unlikely(?).
Many thanks for your explanations and references.