Add code_ircode
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Co-authored-by: Shuhei Kadowaki <40514306+aviatesk@users.noreply.github.com>
To match `typeinf_ircode` with how typeinf lock is used ATM (i.e., optimizer is run inside the lock), we can manually lock it because the lock is re-entrant.
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KristofferC
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Aug 31, 2022
…Lang#45790) Currently the `@nospecialize`-d `push!(::Vector{Any}, ...)` can only take a single item and we will end up with runtime dispatch when we try to call it with multiple items: ```julia julia> code_typed(push!, (Vector{Any}, Any)) 1-element Vector{Any}: CodeInfo( 1 ─ $(Expr(:foreigncall, :(:jl_array_grow_end), Nothing, svec(Any, UInt64), 0, :(:ccall), Core.Argument(2), 0x0000000000000001, 0x0000000000000001))::Nothing │ %2 = Base.arraylen(a)::Int64 │ Base.arrayset(true, a, item, %2)::Vector{Any} └── return a ) => Vector{Any} julia> code_typed(push!, (Vector{Any}, Any, Any)) 1-element Vector{Any}: CodeInfo( 1 ─ %1 = Base.append!(a, iter)::Vector{Any} └── return %1 ) => Vector{Any} ``` This commit adds a new specialization that it can take arbitrary-length items. Our compiler should still be able to optimize the single-input case as before via the dispatch mechanism. ```julia julia> code_typed(push!, (Vector{Any}, Any)) 1-element Vector{Any}: CodeInfo( 1 ─ $(Expr(:foreigncall, :(:jl_array_grow_end), Nothing, svec(Any, UInt64), 0, :(:ccall), Core.Argument(2), 0x0000000000000001, 0x0000000000000001))::Nothing │ %2 = Base.arraylen(a)::Int64 │ Base.arrayset(true, a, item, %2)::Vector{Any} └── return a ) => Vector{Any} julia> code_typed(push!, (Vector{Any}, Any, Any)) 1-element Vector{Any}: CodeInfo( 1 ─ %1 = Base.arraylen(a)::Int64 │ $(Expr(:foreigncall, :(:jl_array_grow_end), Nothing, svec(Any, UInt64), 0, :(:ccall), Core.Argument(2), 0x0000000000000002, 0x0000000000000002))::Nothing └── goto JuliaLang#7 if not true 2 ┄ %4 = φ (#1 => 1, JuliaLang#6 => %14)::Int64 │ %5 = φ (#1 => 1, JuliaLang#6 => %15)::Int64 │ %6 = Base.getfield(x, %4, true)::Any │ %7 = Base.add_int(%1, %4)::Int64 │ Base.arrayset(true, a, %6, %7)::Vector{Any} │ %9 = (%5 === 2)::Bool └── goto #4 if not %9 3 ─ goto JuliaLang#5 4 ─ %12 = Base.add_int(%5, 1)::Int64 └── goto JuliaLang#5 5 ┄ %14 = φ (#4 => %12)::Int64 │ %15 = φ (#4 => %12)::Int64 │ %16 = φ (#3 => true, #4 => false)::Bool │ %17 = Base.not_int(%16)::Bool └── goto JuliaLang#7 if not %17 6 ─ goto #2 7 ┄ return a ) => Vector{Any} ``` This commit also adds the equivalent implementations for `pushfirst!`.
KristofferC
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Aug 31, 2022
When calling `jl_error()` or `jl_errorf()`, we must check to see if we
are so early in the bringup process that it is dangerous to attempt to
construct a backtrace because the data structures used to provide line
information are not properly setup.
This can be easily triggered by running:
```
julia -C invalid
```
On an `i686-linux-gnu` build, this will hit the "Invalid CPU Name"
branch in `jitlayers.cpp`, which calls `jl_errorf()`. This in turn
calls `jl_throw()`, which will eventually call `jl_DI_for_fptr` as part
of the backtrace printing process, which fails as the object maps are
not fully initialized. See the below `gdb` stacktrace for details:
```
$ gdb -batch -ex 'r' -ex 'bt' --args ./julia -C invalid
...
fatal: error thrown and no exception handler available.
ErrorException("Invalid CPU name "invalid".")
Thread 1 "julia" received signal SIGSEGV, Segmentation fault.
0xf75bd665 in std::_Rb_tree<unsigned int, std::pair<unsigned int const, JITDebugInfoRegistry::ObjectInfo>, std::_Select1st<std::pair<unsigned int const, JITDebugInfoRegistry::ObjectInfo> >, std::greater<unsigned int>, std::allocator<std::pair<unsigned int const, JITDebugInfoRegistry::ObjectInfo> > >::lower_bound (__k=<optimized out>, this=0x248) at /usr/local/i686-linux-gnu/include/c++/9.1.0/bits/stl_tree.h:1277
1277 /usr/local/i686-linux-gnu/include/c++/9.1.0/bits/stl_tree.h: No such file or directory.
#0 0xf75bd665 in std::_Rb_tree<unsigned int, std::pair<unsigned int const, JITDebugInfoRegistry::ObjectInfo>, std::_Select1st<std::pair<unsigned int const, JITDebugInfoRegistry::ObjectInfo> >, std::greater<unsigned int>, std::allocator<std::pair<unsigned int const, JITDebugInfoRegistry::ObjectInfo> > >::lower_bound (__k=<optimized out>, this=0x248) at /usr/local/i686-linux-gnu/include/c++/9.1.0/bits/stl_tree.h:1277
#1 std::map<unsigned int, JITDebugInfoRegistry::ObjectInfo, std::greater<unsigned int>, std::allocator<std::pair<unsigned int const, JITDebugInfoRegistry::ObjectInfo> > >::lower_bound (__x=<optimized out>, this=0x248) at /usr/local/i686-linux-gnu/include/c++/9.1.0/bits/stl_map.h:1258
#2 jl_DI_for_fptr (fptr=4155049385, symsize=symsize@entry=0xffffcfa8, slide=slide@entry=0xffffcfa0, Section=Section@entry=0xffffcfb8, context=context@entry=0xffffcf94) at /cache/build/default-amdci5-4/julialang/julia-master/src/debuginfo.cpp:1181
#3 0xf75c056a in jl_getFunctionInfo_impl (frames_out=0xffffd03c, pointer=4155049385, skipC=0, noInline=0) at /cache/build/default-amdci5-4/julialang/julia-master/src/debuginfo.cpp:1210
#4 0xf7a6ca98 in jl_print_native_codeloc (ip=4155049385) at /cache/build/default-amdci5-4/julialang/julia-master/src/stackwalk.c:636
JuliaLang#5 0xf7a6cd54 in jl_print_bt_entry_codeloc (bt_entry=0xf0798018) at /cache/build/default-amdci5-4/julialang/julia-master/src/stackwalk.c:657
JuliaLang#6 jlbacktrace () at /cache/build/default-amdci5-4/julialang/julia-master/src/stackwalk.c:1090
JuliaLang#7 0xf7a3cd2b in ijl_no_exc_handler (e=0xf0794010) at /cache/build/default-amdci5-4/julialang/julia-master/src/task.c:605
JuliaLang#8 0xf7a3d10a in throw_internal (ct=ct@entry=0xf070c010, exception=<optimized out>, exception@entry=0xf0794010) at /cache/build/default-amdci5-4/julialang/julia-master/src/task.c:638
JuliaLang#9 0xf7a3d330 in ijl_throw (e=0xf0794010) at /cache/build/default-amdci5-4/julialang/julia-master/src/task.c:654
JuliaLang#10 0xf7a905aa in ijl_errorf (fmt=fmt@entry=0xf7647cd4 "Invalid CPU name \"%s\".") at /cache/build/default-amdci5-4/julialang/julia-master/src/rtutils.c:77
JuliaLang#11 0xf75a4b22 in (anonymous namespace)::createTargetMachine () at /cache/build/default-amdci5-4/julialang/julia-master/src/jitlayers.cpp:823
JuliaLang#12 JuliaOJIT::JuliaOJIT (this=<optimized out>) at /cache/build/default-amdci5-4/julialang/julia-master/src/jitlayers.cpp:1044
JuliaLang#13 0xf7531793 in jl_init_llvm () at /cache/build/default-amdci5-4/julialang/julia-master/src/codegen.cpp:8585
JuliaLang#14 0xf75318a8 in jl_init_codegen_impl () at /cache/build/default-amdci5-4/julialang/julia-master/src/codegen.cpp:8648
JuliaLang#15 0xf7a51a52 in jl_restore_system_image_from_stream (f=<optimized out>) at /cache/build/default-amdci5-4/julialang/julia-master/src/staticdata.c:2131
JuliaLang#16 0xf7a55c03 in ijl_restore_system_image_data (buf=0xe859c1c0 <jl_system_image_data> "8'\031\003", len=125161105) at /cache/build/default-amdci5-4/julialang/julia-master/src/staticdata.c:2184
JuliaLang#17 0xf7a55cf9 in jl_load_sysimg_so () at /cache/build/default-amdci5-4/julialang/julia-master/src/staticdata.c:424
JuliaLang#18 ijl_restore_system_image (fname=0x80a0900 "/build/bk_download/julia-d78fdad601/lib/julia/sys.so") at /cache/build/default-amdci5-4/julialang/julia-master/src/staticdata.c:2157
JuliaLang#19 0xf7a3bdfc in _finish_julia_init (rel=rel@entry=JL_IMAGE_JULIA_HOME, ct=<optimized out>, ptls=<optimized out>) at /cache/build/default-amdci5-4/julialang/julia-master/src/init.c:741
JuliaLang#20 0xf7a3c8ac in julia_init (rel=<optimized out>) at /cache/build/default-amdci5-4/julialang/julia-master/src/init.c:728
JuliaLang#21 0xf7a7f61d in jl_repl_entrypoint (argc=<optimized out>, argv=0xffffddf4) at /cache/build/default-amdci5-4/julialang/julia-master/src/jlapi.c:705
JuliaLang#22 0x080490a7 in main (argc=3, argv=0xffffddf4) at /cache/build/default-amdci5-4/julialang/julia-master/cli/loader_exe.c:59
```
To prevent this, we simply avoid calling `jl_errorf` this early in the
process, punting the problem to a later PR that can update guard
conditions within `jl_error*`.
vtjnash
pushed a commit
that referenced
this pull request
Feb 10, 2023
…cts (JuliaLang#46712) Currently our inference isn't able to propagate `isa`-based type constraint for cases like `isa(Type{<:...}, DataType)` since `typeintersect` may return `Type` object itself when taking `Type` object and `iskindtype`-object. This case happens in the following kind of situation (motivated by the discussion at <JuliaLang#46553 (comment)>): ```julia julia> function isa_kindtype(T::Type{<:AbstractVector}) if isa(T, DataType) # `T` here should be inferred as `DataType` rather than `Type{<:AbstractVector}` return T.name.name # should be inferred as ::Symbol end return nothing end isa_kindtype (generic function with 1 method) julia> only(code_typed(isa_kindtype; optimize=false)) CodeInfo( 1 ─ %1 = (T isa Main.DataType)::Bool └── goto #3 if not %1 2 ─ %3 = Base.getproperty(T, :name)::Any │ %4 = Base.getproperty(%3, :name)::Any └── return %4 3 ─ return Main.nothing ) => Any ``` This commit improves the situation by adding a special casing for abstract interpretation, rather than changing the behavior of `typeintersect`.
vtjnash
pushed a commit
that referenced
this pull request
Sep 27, 2023
This commit improves SROA pass by extending the `unswitchtupleunion`
optimization to handle the general parametric types, e.g.:
```julia
julia> struct A{T}
x::T
end;
julia> function foo(a1, a2, c)
t = c ? A(a1) : A(a2)
return getfield(t, :x)
end;
julia> only(Base.code_ircode(foo, (Int,Float64,Bool); optimize_until="SROA"))
```
> Before
```
2 1 ─ goto #3 if not _4 │
2 ─ %2 = %new(A{Int64}, _2)::A{Int64} │╻ A
└── goto #4 │
3 ─ %4 = %new(A{Float64}, _3)::A{Float64} │╻ A
4 ┄ %5 = φ (#2 => %2, #3 => %4)::Union{A{Float64}, A{Int64}} │
3 │ %6 = Main.getfield(%5, :x)::Union{Float64, Int64} │
└── return %6 │
=> Union{Float64, Int64}
```
> After
```
julia> only(Base.code_ircode(foo, (Int,Float64,Bool); optimize_until="SROA"))
2 1 ─ goto #3 if not _4 │
2 ─ nothing::A{Int64} │╻ A
└── goto #4 │
3 ─ nothing::A{Float64} │╻ A
4 ┄ %8 = φ (#2 => _2, #3 => _3)::Union{Float64, Int64} │
│ nothing::Union{A{Float64}, A{Int64}}
3 │ %6 = %8::Union{Float64, Int64} │
└── return %6 │
=> Union{Float64, Int64}
```
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