Create large random boolean matrix with numpy

I am trying to create a huge boolean matrix which is randomly filled with True and False with a given probability p. At first I used this code:

N = 30000
p = 0.1
np.random.choice(a=[False, True], size=(N, N), p=[p, 1-p])  

But sadly it does not seem to terminate for this big N. So I tried to split it up into the generation of the single rows by doing this:

N = 30000
p = 0.1
mask = np.empty((N, N))
for i in range (N):
     mask[i] = np.random.choice(a=[False, True], size=N, p=[p, 1-p])            
     if (i % 100 == 0):
          print(i)

Now There happends something strange (at least on me device): The first ~1100 rows are very fastly generated - but after it, the code becomes horribly slow. Why is this happening? What do I miss here? Are there better ways to create a big matrix which has True entries with probability p and False entries with probability 1-p?