Comments (4)
Thanks for pointing that out - I made the change.
I played around with syr2k
and found that it tended to be a tiny bit slower than just iterating over all the entries in the upper triangle.
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I find the performance of MLKernels.jl
very impressive and it is very flexible, great package!
syr2k
has a multithreaded implementation and it also depends if you use a build for a certain architecture.
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Should this issue be closed? It seems that removing the redundant copying operation has been pushed to master. Or is the performance of using syr2k
under question?
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For me the call to kernelmatrix!
is ~0.3s faster than the gauss
function in the above example and I think that the issue is resolved. I just gave the example to illustrate the speed increase if the extra copy was avoided (and because I stumbled over syrk2k
which is not documented), now I think this would make a great example to show how julia
can be faster than a specialized linear algebra library, while remaining super flexible.
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Related Issues (20)
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- DomainError in tests HOT 5
- threading support HOT 2
- Using Distances.jl and automatic differentiation
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- Remove HyperParameter? HOT 2
- Issue with new release HOT 2
- Wrong metric for Matern kernel HOT 1
- Error tagging new release
- Rename GammaRationalKernel to GammaRationalQuadraticKernel
- Remove PeriodicKernel
- Remove LinearKernel
- Remove integer parameter from PolynomialKernel
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- ForwardDiff.jl Compatibility
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- Using GPU to accelerate the eigen decomposition in the psuedo-inverse calculation in nystrom.jl HOT 1
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