perf: exploration of better matmul algorithms

[steven-murray]

This adds a notebook that explores different ways to do the V = Z.dot(Z.T.conj()) calculation.

Ideas that I haven't yet explored:

• Using MAGMA (see eg. https://github.com/PSims/BayesEoR)
• Using PyTorch
• Proper NVIDIA profiling of all the functions

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All modified and coverable lines are covered by tests ✅

Comparison is base (d45e9bc) 100.00% compared to head (af6f273) 65.07%.
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@@             Coverage Diff              @@
##              main      #69       +/-   ##
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- Coverage   100.00%   65.07%   -34.93%     
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  Files            8        8               
  Lines          567      567               
  Branches        88       88               
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- Hits           567      369      -198     
- Misses           0      193      +193     
- Partials         0        5        +5     

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unittests	64.72% <ø> (-34.57%)	⬇️

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[mkolopanis]

If you're going through all the efforts of writing a cublas implementation, might investigated compiled extensions like cython or a rust extension. Both have interop with numpy which is pretty straightforward