Comments (2)
I believe the problem is more general than stdlibs, it looks like setting JULIA_CPU_TARGET
always results in compiling code only for the generic target, if we can trust the parsing done by Base.parse_image_targets
and Base.parse_cache_header
. Consider this script
# Cleanup Example precompile dir
example_dir = joinpath(first(Base.DEPOT_PATH), "compiled", "v$(Base.thisminor(Base.VERSION))"[begin:end-2], "Example")
rm(example_dir; force=true, recursive=true)
# Install Example
using Pkg
Pkg.activate(; temp=true, io=devnull)
Pkg.add("Example"; io=stdout)
# Find compile cache
pkg = Base.identify_package("Example")
cachefiles = Base.find_all_in_cache_path(pkg)
isempty(cachefiles) && error(pkg, " has not yet been precompiled for julia ", Base.VERSION, ". Reinstall the package with `Pkg.add(\"Example\"; io=stdout)` to see why")
pkgpath = Base.locate_package(pkg)
idx = findfirst(cachefiles) do cf
Base.stale_cachefile(pkgpath, cf) !== true
end
targets = Base.parse_image_targets(Base.parse_cache_header(cachefiles[idx])[7])
# Show target
@show targets
With Julia v1.10.3 I get
% julia example_targets.jl
targets = Base.ImageTarget[haswell; flags=0; features_en=(sse3, pclmul, ssse3, fma, cx16, sse4.1, sse4.2, movbe, popcnt, aes, xsave, avx, f16c, fsgsbase, bmi, avx2, bmi2, sahf, lzcnt)]
% JULIA_CPU_TARGET='generic;sandybridge,-xsaveopt,clone_all;haswell,-rdrnd,base(1);x86-64-v4,-rdrnd,base(1)' julia example_targets.jl
targets = Base.ImageTarget[generic; flags=0; features_en=(cx16)]
Moreover, shuffling the targets:
% JULIA_CPU_TARGET='sandybridge,-xsaveopt,clone_all;generic;haswell,-rdrnd,base(0);x86-64-v4,-rdrnd,base(0)' julia example_targets.jl
targets = Base.ImageTarget[sandybridge; flags=0; features_en=(sse3, pclmul, ssse3, cx16, sse4.1, sse4.2, popcnt, xsave, avx, sahf)]
So we always compile only for the first target of the list, whatever that is.
CC: @gbaraldi @vchuravy @timholy.
from julia.
That's not too surprising since stdlibs are compiled identically to normal packages.
from julia.
Related Issues (20)
- Performance regressions in linear algebra benchmarks with Hermitian and Triangular matrices
- Performance regressions in BaseBenchmarks due to #54647 (Cleanup `MemoryRef`) HOT 3
- observed failure of TestPkg thread test
- race condition in waitany test
- Regression in threads tests on FreeBSD
- Operations on `views` much slower when indices are `start:1:stop` HOT 7
- [1.11+] jl_array_t no longer contains elsz HOT 1
- Unreachable reached HOT 2
- `mkpath` does not stably return the original path
- Deserialization in a Module() HOT 2
- `last(::Tuple{})` throws `BoundsError` HOT 5
- document `FieldError`
- peek docstring has a disconnect HOT 2
- Precompiling and FunctionWrappers lead to extra runtime allocations HOT 4
- Matrix `exp` and `log` are not inverse of each other HOT 17
- recursive type parameter constraints HOT 3
- [CI] Intermittent failure in `Profile` on aarch64-linux-gnu HOT 1
- @time always shows reports compilation times while SnoopCompile does not HOT 6
- Problem with `similar` called for view-types such as `SubArray`, `ReshapedArray` or `ReinterpretArray` HOT 1
- 5% regression in some Inference benchmarks due to #51149 (Set temporary env whenever Julia is started with `--project=@temp`) HOT 6
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from julia.