To add a little bit of detail to what others have said:
If you are using the same version of R, on the same operating system,
with the same processor (e.g. there will be differences between
Intel/M1/M2 Macs), then as far as I know the only source of
non-determinism, which could even affect successive runs on the same
machine, would be parallel operations in BLAS/LAPACK resulting in
mathematically equivalent operations being done in a different order
(floating point arithmetic is not associative, so (a+b)+c != a + (b+c)
in general).
On 10/3/25 05:57, Jeanne Moreau wrote:
Good Morning,
I am working with LDA models in R (using both topicmodels::LDA and
quanteda::textmodel_lda) and noticed that the results differ slightly
across different machines, even when I use set.seed(1234) and the same
dataset.
So, I have a few questions:
Is this expected due to BLAS/LAPACK or low-level random number generation
differences?
Is there a recommended way to enforce bit-for-bit reproducibility of LDA
results across machines in R?
Would you recommend always saving fitted models with saveRDS() to ensure
reproducible outputs instead of re-fitting?
Thanks a lot for your guidance.
Best regards,
Jeanne Moreau
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