Does scipy.stats produce different random numbers for different computer hardware?

I'm having a problem where I'm getting different random numbers across different computers despite

• scipy.__version__ == '1.2.1' on all computers
• numpy.__version__ == '1.15.4' on all computers
• random_state seed is fixed to the same number (42) in every function call that generates random numbers for reproducible results

The code is a bit to complex to post in full here, but I noticed results start to diverge specifically when sampling from a multivariate normal:

import numpy as np
from scipy import stats
seed = 42
n_sim = 1000000
d = corr_mat.shape[0] # corr_mat is a 15x15 correlation matrix, numpy.ndarray
# results diverge from here across different hardware
z = stats.multivariate_normal(mean=np.zeros(d), cov=corr_mat).rvs(n_sim, random_state=seed)

corr_mat is a correlation matrix (see Appendix below) and is the same across all computers.

The two different computers we are testing on are

Computer 1

---

• OS: Windows 7
• Processor: Intel(R) Xeon(R) CPU E5-2623 v4 @ 2.60Ghz 2.60 Ghz (2 processors)
• RAM: 64 GB
• System type: 64-bit

---

Computer 2

---

• OS: Windows 7
• Processor: Intel(R) Xeon(R) CPU E5-2660 v3 @ 2.10Ghz 2.10 Ghz (2 processors)
• RAM: 64 GB
• System type: 64-bit

---

Appendix

corr_mat
>>> array([[1.  , 0.15, 0.25, 0.25, 0.25, 0.25, 0.1 , 0.1 , 0.1 , 0.25, 0.25,
        0.25, 0.1 , 0.1 , 0.1 ],
       [0.15, 1.  , 0.  , 0.  , 0.  , 0.  , 0.15, 0.05, 0.15, 0.15, 0.15,
        0.  , 0.15, 0.15, 0.15],
       [0.25, 0.  , 1.  , 0.25, 0.25, 0.25, 0.2 , 0.  , 0.2 , 0.2 , 0.2 ,
        0.25, 0.2 , 0.2 , 0.2 ],
       [0.25, 0.  , 0.25, 1.  , 0.25, 0.25, 0.2 , 0.  , 0.2 , 0.2 , 0.2 ,
        0.25, 0.2 , 0.2 , 0.2 ],
       [0.25, 0.  , 0.25, 0.25, 1.  , 0.25, 0.2 , 0.  , 0.2 , 0.2 , 0.2 ,
        0.25, 0.2 , 0.2 , 0.2 ],
       [0.25, 0.  , 0.25, 0.25, 0.25, 1.  , 0.2 , 0.  , 0.2 , 0.2 , 0.2 ,
        0.25, 0.2 , 0.2 , 0.2 ],
       [0.1 , 0.15, 0.2 , 0.2 , 0.2 , 0.2 , 1.  , 0.15, 0.25, 0.25, 0.25,
        0.2 , 0.25, 0.25, 0.25],
       [0.1 , 0.05, 0.  , 0.  , 0.  , 0.  , 0.15, 1.  , 0.15, 0.15, 0.15,
        0.  , 0.15, 0.15, 0.15],
       [0.1 , 0.15, 0.2 , 0.2 , 0.2 , 0.2 , 0.25, 0.15, 1.  , 0.25, 0.25,
        0.2 , 0.25, 0.25, 0.25],
       [0.25, 0.15, 0.2 , 0.2 , 0.2 , 0.2 , 0.25, 0.15, 0.25, 1.  , 0.25,
        0.2 , 0.25, 0.25, 0.25],
       [0.25, 0.15, 0.2 , 0.2 , 0.2 , 0.2 , 0.25, 0.15, 0.25, 0.25, 1.  ,
        0.2 , 0.25, 0.25, 0.25],
       [0.25, 0.  , 0.25, 0.25, 0.25, 0.25, 0.2 , 0.  , 0.2 , 0.2 , 0.2 ,
        1.  , 0.2 , 0.2 , 0.2 ],
       [0.1 , 0.15, 0.2 , 0.2 , 0.2 , 0.2 , 0.25, 0.15, 0.25, 0.25, 0.25,
        0.2 , 1.  , 0.25, 0.25],
       [0.1 , 0.15, 0.2 , 0.2 , 0.2 , 0.2 , 0.25, 0.15, 0.25, 0.25, 0.25,
        0.2 , 0.25, 1.  , 0.25],
       [0.1 , 0.15, 0.2 , 0.2 , 0.2 , 0.2 , 0.25, 0.15, 0.25, 0.25, 0.25,
        0.2 , 0.25, 0.25, 1.  ]])