[pull] master from JuliaLang:master #2151
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Red Hat-based distros don't include the static version of libstdc++ in
their g++ packages, so document this dependency, as well as the
`USE_RT_STATIC_LIBSTDCXX=0` workaround if it isn't available. I also
looked for missing dependencies by compiling Julia in the base
`fedora:42` and `debian:12` images:
```dockerfile
FROM debian:12 AS build
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential libatomic1 python3 gfortran perl wget m4 cmake pkg-config \
curl git ca-certificates
WORKDIR /build
RUN git clone --depth=1 https://github.com/JuliaLang/julia.git
RUN cd julia && make -j binary-dist VERBOSE=1
```
```dockerfile
FROM fedora:42 AS build
RUN dnf install -y --nodocs --setopt=install_weak_deps=False \
gcc gcc-c++ gcc-gfortran python3 perl wget m4 cmake pkgconfig curl git \
which diffutils libatomic libstdc++-static
WORKDIR /build
RUN git clone --depth=1 https://github.com/JuliaLang/julia.git
RUN cd julia && make -j binary-dist VERBOSE=1
```
Reported by
#60248 (comment).
This seems to be an issue at least as far back as 1.10: ```julia $ rm -rf ~/.julia/compiled/*/SuiteSparse/ $ julia +1.10 -q julia> using SuiteSparse [ Info: Precompiling SuiteSparse [4607b0f0-06f3-5cda-b6b1-a6196a1729e9] ```
To get things going with #56521 I've made a minimal implementation that mirrors one from numpy (https://github.com/numpy/numpy/blob/7c0e2e4224c6feb04a2ac4aa851f49a2c2f6189f/numpy/_core/src/multiarray/alloc.c#L113). What this does: changes `jl_gc_managed_malloc(size_t sz)` to check whether requested allocation is big enough to benefit from huge pages. And if so, we ensure the allocation is page aligned and then appropriate `madvise` is called on the memory pointer. For a simple "fill memory" test I see around 2x timing improvement. ```julia function f(N) mem = Memory{Int}(undef, N) mem .= 0 mem[end] end f(1) @time f(1_000_000) ``` ``` 0.001464 seconds (2 allocations: 7.633 MiB) # this branch 0.003431 seconds (2 allocations: 7.633 MiB) # master ``` I would appreciate help with this PR as I have no experience writing C code and little knowledge of julia internals. In particular I think it would make sense to have a startup option controlling minimal eligible allocation size which should default to system's hugepage size - for this initial implementation the same constant as in numpy is hardcoded. --------- Co-authored-by: Artem Solod <>
The `kw` form isn't produced in `SyntaxNode`/`SyntaxTree` like it is in Expr, which simplifies the parser, but causes problems once we start start caring about the semantics of these trees. Parsing `"f(a=1)"` will always produce an `Expr(:call, :f, Expr(:kw, :a, 1))`, but the equivalent SyntaxNode representation `(call f (= a 1))` makes `Expr(:call, :f, Expr(:(=), :a, 1))` unrepresentable, even though that's valid syntax a macro could produce. To fix this, we need to convert `=` to `kw` within certain forms before macro expansion.
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