Performance difference Windows/Ubuntu about bhtsne HOT 2 OPEN

I would suspect the linked libraries. For example, matrix multiplications (PCA) are more efficient with Intel MKL libraries which are probably integrated in Visual Studio. https://blog.revolutionanalytics.com/2014/10/revolution-r-open-mkl.html
https://simplystatistics.org/2016/01/21/parallel-blas-in-r/

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Thank you @SamGG for your response!

Profiling the binary with perf led to the conclusion that in particular computeNonEdgeForces (as also noticed here) is the most time-consuming.

Long story short: I couldn't dig the root cause for this, but I've applied the performance improvements mentioned in this pull request (Excellent writeup btw, kudos to tavianator!

Numbers of the mnist are now identical on windows/ubuntu, see below:

Computing input similarities...
Building tree...

• point 0 of 70000
• point 10000 of 70000
• point 20000 of 70000
• point 30000 of 70000
• point 40000 of 70000
• point 50000 of 70000
• point 60000 of 70000
  Input similarities computed in 700.94 seconds (sparsity = 0.002964)!
  Learning embedding...
  Iteration 1: error is 114.707556
  Iteration 50: error is 114.707555 (50 iterations in 36.25 seconds)
  Iteration 100: error is 114.707555 (50 iterations in 36.45 seconds)
  Iteration 150: error is 114.705697 (50 iterations in 38.57 seconds)
  Iteration 200: error is 107.418164 (50 iterations in 37.08 seconds)
  Iteration 250: error is 5.918315 (50 iterations in 36.25 seconds)
  Iteration 300: error is 4.685798 (50 iterations in 35.77 seconds)
  Iteration 350: error is 4.293142 (50 iterations in 33.82 seconds)
  Iteration 400: error is 4.059164 (50 iterations in 34.66 seconds)
  Iteration 450: error is 3.895986 (50 iterations in 35.09 seconds)
  Iteration 500: error is 3.770166 (50 iterations in 33.31 seconds)
  Iteration 550: error is 3.669497 (50 iterations in 34.37 seconds)
  Iteration 600: error is 3.586112 (50 iterations in 33.95 seconds)
  Iteration 650: error is 3.514839 (50 iterations in 34.67 seconds)
  Iteration 700: error is 3.453197 (50 iterations in 34.06 seconds)
  Iteration 750: error is 3.398859 (50 iterations in 32.85 seconds)
  Iteration 800: error is 3.350613 (50 iterations in 33.65 seconds)
  Iteration 850: error is 3.307334 (50 iterations in 34.55 seconds)
  Iteration 900: error is 3.268252 (50 iterations in 33.63 seconds)
  Iteration 950: error is 3.232840 (50 iterations in 33.08 seconds)
  Iteration 1000: error is 3.200317 (50 iterations in 33.95 seconds)
  Fitting performed in 696.02 seconds.

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