Parallelize elements of a vector or array

Question

Suppose I want to calculate a vector or an array (say, for simplicity a 4-by-1 vector), but each element contains independent numerically evaluated functions $f_1,f_2,f_3,f_4$ and each takes long time. Is there a way to parallelize computation of $f_i$?

The documentation and Stackexchange I searched so far (maybe I missed some) seems to be catering for a situation where we have a "master function" $F[i]$ whose entries are parallelized by using ParallelTable. Does that mean the only way (perhaps valid anyway) to do this is to simply define $F[i\_]:= f_i$? What is the "best practice" for this?

Update: the functions $f_i$ are a priori unrelated, but they depend on the same set of variable, so I was trying to Parallelize this inside a Module. I am also trying to avoid defining too many functions which is why if I can help it I want to avoid defining $F$ (because this will occur many times in the notebook).

Answer 1

Here is an example using ParallelSubmit:

f1[x_] = x;
f2[x_] = x^2;
f3[x_] = x^3;
f4[x_] = x^4;
WaitAll[{
  ParallelSubmit[f1[2]],
  ParallelSubmit[f2[2]],
  ParallelSubmit[f3[2]],
  ParallelSubmit[f4[2]]
  }]

(* {2, 4, 8, 16} *)

Answer 2

ParallelMap[Construct[#, x] &, {f1, f2, f3, f4}]
(*    {f1[x], f2[x], f3[x], f4[x]}    *)