Extended benchmark #68
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This week I saw some peculiar behaviour that makes me doubt the JAX benchmarks: it is slower when parameters update, which suggests some form of caching. I haven't noticed this before and IPython's My first guess was that JAX v0.3.x introduced some new behaviour, but I don't see any specific new caching features in their changelog. At any rate, has to be investigated. A first step may be to separate the 'benchmarks' into a separate notebook, so that no intensities are computed prior to the |
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As a side note, I noticed that sympy does not simplify expressions like sp.sin(sp.acos((x+y)/z)) or at least certain combined expressions. This would also have to be investigated. |
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yes, I worked around that by replacing the sin and cos separately. |
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thoughts to come back after the sensitivity project!
The difference in the speed between SymPy+JIT and Julia still bothers me.
I have a guess that the most of it comes from taking the summation over the helicity indices analytically.
I would be interested to follow the polarization asymmetry project with this investigation.
Particularly, we would like to do an extended benchmark.
There is a great interest in faster amplitude fitter in LHCb. The toys we do not for Lb decays will take a month on 10 GPU. A factor of 100, or even 10 would matter a lot.
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