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ziggurat performance comparison (julia vs. C) #1211

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ViralBShah opened this issue Aug 25, 2012 · 2 comments
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ziggurat performance comparison (julia vs. C) #1211

ViralBShah opened this issue Aug 25, 2012 · 2 comments
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performance Must go faster

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@ViralBShah
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The julia implementation of the ziggurat implementation is 2x slower than the C implementation for generating 1 million normally distributed random numbers.

julia, randn_zig,30.411958694458008
c,randn_zig,16.033888
@ViralBShah ViralBShah mentioned this issue Oct 8, 2012
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JeffBezanson added a commit that referenced this issue Nov 16, 2012
@JeffBezanson
specialize function signatures
9a68a05 
this is an optimization and also makes it easier to get callback pointers.
closes #938. sparse on Range 3x faster
helps #1211 (ziggurat), about 25% faster
helps #1169 (game of go), about 25% faster
helps #939 (sortperm), about 25% faster
helps #1163 (graph centrality) a bit, about 10% faster
@ViralBShah
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The difference is considerably reduced now.

c,randn_zig,18.842936
julia,randn_zig,23.12302589416504

Note that I get 14ms if I use clang -O4, but that uses LTO and is probably not a fair comparison.

@StefanKarpinski
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Very nice. I'm sure we'll gradually close the gap with C on many of these sorts of things, which will be lovely for now, we're getting close enough and language features and API stability are a higher priority.

KristofferC added a commit that referenced this issue Feb 25, 2025
@DilumAluthgeBot @KristofferC
🤖 [master] Bump the LinearAlgebra stdlib from e7da19f to f781708 (#57522
9f7cdfd 
)

Stdlib: LinearAlgebra
URL: https://github.com/JuliaLang/LinearAlgebra.jl.git
Stdlib branch: master
Julia branch: master
Old commit: e7da19f
New commit: f781708
Julia version: 1.13.0-DEV
LinearAlgebra version: 1.12.0(Does not match)
Bump invoked by: @KristofferC
Powered by:
[BumpStdlibs.jl](https://github.com/JuliaLang/BumpStdlibs.jl)

Diff:
JuliaLang/LinearAlgebra.jl@e7da19f...f781708

```
$ git log --oneline e7da19f..f781708
f781708 use the custom sysimage when running documentation (and doctests) as well (#1226)
8fdbfd5 Add `getindex` for `SymTridiagonal` using a `BandIndex` (#1223)
91b8845 Use `BandIndex` directly in `diagzero` call in `getindex` (#1222)
ef7ef3a Restrict triangular type aliases to `AbstractMatrix`es (#1220)
af7a9ac Use `BandIndex` directly in `diagzero` call in `getindex` for banded matrices
579b5f7 Specialize Diagonal * Adjoint (#1207)
5cf41c4 Indirection in matrix multiplication to avoid ambiguities (#1210)
0a9c164 Remove specialized `issymmetric`/`ishermitian` for `Diagonal{<:Number}` (#1213)
ff5648a Make unitary matrices in `svd`/`eigen` of `Diagonal` be unitless (#1155)
e096a03 Don't mutate arrays in symmetric trig functions (#1206)
c234bed Loop over `diagind` in `diag` for banded matrices (#1211)
57785c7 More resizing for truncating return values from LAPACK (#1190)
b464203 Materialize adjoint in mul with `HermOrSym` (#1191)
16d9d61 Restrict Diagonal sqrt branch to positive diag (#1203)
baa48b7 Verbose `showerror` for `SingularException` (#1204)
e0b59a7 Remove `LinearAlgebra` qualifications in `cholesky.jl` (#1209)
95d009b Remove `LinearAlgebra` qualifications in `cholesky.jl`
c550974 change to pivot
ed35a37 Add fast path in generic matmul (#1202)
8c7fe68 Detailed `showerror` for `SingularException`
2a1696a Explicitly declare type constructor imports (#1196)
101f766 Added note to BLAS.[g|s]et_num_threads about Apple Accelerate not supporting it  (#1195)
5aca26f Simplify `getproperty` for `Cholesky*` (#1197)
924dda4 remove copy-allocation on accessing `cholesky` factors (`.L`, `.U`) (#1186)
6f02532 Use `BLAS.trsm!` instead of `LAPACK.trtrs!` in left-triangular solves (#1194)
```

Co-authored-by: KristofferC <[email protected]>
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@StefanKarpinski @ViralBShah