Does Eigenvalues evaluate in a parallelized way?

I use mathematica on a computer with linux operating system. The computer has 2 cpus and each cpu has 4 cores, so there are totally 8 cores available.

Now I got confused with whether the evaluation of Eigenvalues is parallelized or not. I present two kinds of codes below

one use ParallelDo

ParallelDo[
Eigenvalues[# +
ConjugateTranspose[#] &[Table[RandomReal[], {i, 5000}, {j,5000}]]
];
,{4}]//AbsoluteTiming


the time it takes is 135.12254 second. And use Top command in linux during the evaluation, it shows like below:

It show that 4 cores are trying their best, that's quite reasonable.

the other use Do only

Do[Eigenvalues[# + ConjugateTranspose[#] &[Table[RandomReal[], {i, 5000}, {j,5000}]]];,{4}]//AbsoluteTiming


this time it takes 109.004395 second. It evaluates even faster!!. And use Top, It shows like below:

Almost 800%, it means that this time, the evaluation uses all the cores? I don't know why it shows one 800% instead of eight 100%s. What is the difference?

If Eigenvalues really evaluates in a parallelized way automatically, why Parallelize[Eigenvalues[matrix]] gives error message saying that " Eigenvalues can't be parallized;proceeding with sequential evaluation"??

-
Hit H in top, that should show all user threads –  ssch Jun 1 '13 at 13:44
@ssch yeah! it shows all. I never hit H before. So 800% is the same as eight 100%s in essence, right? –  matheorem Jun 1 '13 at 13:52
@matheorem Because Eigenvalues doesn't use Mathematica's parallelization. Parallelize can only deal with high level Mathematica constructs while Eigenvalues is implemented in a low level language for dense numerical matrices. Mathematica is just calling this low level multithreaeded implementation. –  Szabolcs Jun 1 '13 at 14:58
The reason why top displays 100% four times is because there are four processes (namely subkernels) doing calculation using a single thread each. I guess the idea is that if you explicitly parallelize, you don't want Mathematica to interfere with your parallelization strategy. –  celtschk Jun 1 '13 at 15:53
However it has a natural followup question: Which Mathematica functions use thread-level parallelism? –  celtschk Jun 1 '13 at 19:18