I have two computers with intel i9-9900 (new HP dekstop at work + Lenovo home computer), giving the same error on a simple problem – while my laptop (i7) and old work desktop (Dell, Xeon processor?) works fine. Here is the essence of the weird problem:
As you see, the rank is computed incorrectly after a plot, while if I repeat the computation, the answer is correct.
Now, consider the case of using the GR backend:
Some more info:
- I use OpenBLAS
- The incorrect computation of the rank (and SVD…) doesn’t show up for all matrix sizes – for smaller values of
m, the problem may disappear.
- On my old (Dell, Xeon?) and new (HP, i9-9900 high power) work desktops, I have installed exactly the same Julia packages and package versions with Julia v 1.4.2. The installation of other software may vary, though. The above code works with
PyPloton my old desktop but not on my new desktop.
- The Julia packages on my home computer (Lenovo, i9-9900 low power) and my laptop (Microsoft, i7) are probably different, and I think I use Julia v. 1.4.0 on my laptop + Julia v. 1.4.2 on my (new) home computer. The above code works with
PyPloton my laptop (i7), but not with my new (i9) home computer.
- The same error shows up if I run the code in VScode.
I understand that some other Julia user had a similar problem on an i9-9900 gaming computer running model
fit in the
Polynomials package (which is where I, too, came across the problem). To me, it seems like the problem relates to some interaction between
PyPlot on some processors…??
Is anyone with an
i9-9900 (or other
i9 processors) able to recreate this bug?