equation solving - best way for finding approximate root of monotonic sawtooth like function

First I will generate such kind of monotonic sawtooth like function called func

n = 50;

block = Symmetrize[RandomReal[1., {n, n}], Symmetric[{1, 2}]];
diagF = SparseArray[Band[{1, 1}] -> Normal /@ #] &;
mat = diagF[{block, block, block, block}];
dim = Length@mat;
eigs = Transpose@Sort@Transpose@Eigensystem@mat;
eigsdensity = {eigs[[1]], Abs[eigs[[2]]]^2};
fermiCom = 
  Compile[{{e, _Real}, {u, _Real}, {t, _Real}}, 
   Module[{tmp}, tmp = Exp[(u - e)/t]; tmp = 1./(1. + tmp); 
    tmp = 1. - tmp], RuntimeOptions -> "Speed"];

Clear[fermi];
fermi[e_?NumericQ, u_?NumericQ, t_?NumericQ] := fermiCom[e, u, t];
num = Length@Select[eigs[[1]], # < 0 &] + 1;
Clear[func];
func[u_] := 
 Total[Sum[
   eigsdensity[[2, i]] fermi[eigs[[1, i]], u, 0.0001], {i, 1, dim}]]

The plot of func is like this

Plot[func[u], {u, -3, 3}]

This is what I call monomotic sawtooth like function

Now I want to know at which u value, func[u] is closest to num ( num = Length@Select[eigs[[1]], # < 0 &] + 1)

Normally, FindRoot fastest for this kind of task. However it is not working for this problem

FindRoot[func[u] - num == 0, {u, 0}]

gives error

FindRoot::jsing: Encountered a singular Jacobian at the point {u} = {0.}. Try perturbing the initial point(s). >>

This is because num is a value guaranteed to be between two plateaus (the fermi function is very close to step function, while not exactly the same), so it can't find such a root.

Then, we can transform the problem into a minimization problem. That is to minimize Abs[func[u] - num]

HoweverFindMinimum is also not working.

FindMinimum[Abs[func[u] - num], u]

FindMinimum::fmgz: Encountered a gradient that is effectively zero. The result returned may not be a minimum; it may be a maximum or a saddle point. >>

The only working, I know at the moment is NMinimize

NMinimize[Abs[func[u] - num], u] // AbsoluteTiming
(*{0.934564, {1., {u -> 0.0116856}}}*)

But as you can see NMinimize is really expensive. So I wonder, since the func such a good monotonic property, is there a better way than direct NMinimize?

Answer

From the FindRoot documentation:

FindRoot[lhs == rhs, {x, x0, x1}] searches for a solution using $x_0$ and $x_1$ as the first two values of $x$, avoiding the use of derivatives. ... If you specify two starting values, FindRoot uses a variant of the secant method.

Indeed, that does the job pretty much instantly:

FindRoot[func[u] - num == 0, {u, -3, 3}]
(* {u -> 0.00249415} *)