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Fully mutating linear solver #48

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gdalle opened this issue May 24, 2023 · 4 comments
Open

Fully mutating linear solver #48

gdalle opened this issue May 24, 2023 · 4 comments
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performance Improve performance or stability

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@gdalle
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gdalle commented May 24, 2023 •
edited

At the moment, AbstractDifferentiation does not have a fully mutating API, and benchmarks show allocations are non-negligible when multiplying by A and B. Opening this to track JuliaDiff/AbstractDifferentiation.jl#14 and see what we can do
@gdalle gdalle added the feature New feature or request label May 24, 2023
@mohamed82008
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The problem is that most AD packages don't actually support mutation.

@gdalle
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gdalle commented May 24, 2023

Yeah I know, it would be useless for ChainRules, but not for ForwardDiff?

@gdalle gdalle mentioned this issue May 24, 2023
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@gdalle gdalle added performance Improve performance or stability and removed feature New feature or request labels Aug 8, 2023
@gdalle
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gdalle commented Feb 21, 2024

Trying to solve this with https://github.com/gdalle/DifferentiationInterface.jl

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gdalle commented Apr 10, 2024

This is now possible with DifferentiationInterface but

  • it won't work with every outer backend
  • it requires a mutating version of the conditions conditions!(c, x, y)

I hope to make it part of v0.7

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