Fix `kron` ambiguity for triangular/hermitian matrices #54413

dkarrasch · 2024-05-08T17:33:05Z

This resolves method ambiguities in SparseArrays.jl, that have been introduced in #53186. As usual, we would want the result to be sparse if any one Kronecker factor is sparse. In that case, however, we would need a specialized kernel to begin with. So, this is more like a quick fix.

This has not been released, so it's not a regression.

@araujoms Is this fine with you?

araujoms · 2024-05-08T18:00:57Z

There are some problems. First is that you removed the restriction to a subtype of Number. This reintroduces the bug that @jishnub had pointed out here: #53186 (comment) . For ease of reference, the problem is when we have a matrix of matrices:

m = UpperTriangular(reshape(fill(ones(2,2),4), 2, 2))
n = Symmetric(reshape(fill(ones(2,2),4), 2, 2))
kron(m,m)
kron(n,n)

The second is that you removed the parametrization of the functions. I don't understand why, we really want the compiler to specialize on conj and real.

The third is that now if we wrap Hermitian around another wrapper, like Diagonal, we won't have the nice code anymore, but the generic fallback. Of course it would be much more efficient to write something directly for Hermitian(Diagonal), but I was relying on the kronecker products staying conveniently Hermitian. I won't write code for every possible double wrapper, but I might do it for Diagonal.

dkarrasch · 2024-05-09T09:40:23Z

First is that you removed the restriction to a subtype of Number.

Hm, I see. Dispatching on type parameters is just not recommended (especially when we have so many existing methods already), since it's prone to introducing ambiguities and increases latency.

The second is that you removed the parametrization of the functions. I don't understand why, we really want the compiler to specialize on conj and real.

IIRC, then this is what the compiler does: it specializes on function arguments whenever they are called in the function body, and not merely passed on as an argument. I'll need to double-check.

The third is that now if we wrap Hermitian around another wrapper, like Diagonal, we won't have the nice code anymore, but the generic fallback.

Sure, but now we have stdlibs in an ambiguous state. So we can't kron two symmetric/triangular sparse matrices, not even with some generic fallback. The other option then would be to work out the analogue of #53186 for symmetric/hermitian/triangular sparse matrices, before you get to the Hermitian(Diagonal) case.

araujoms · 2024-05-09T10:42:05Z

Hm, I see. Dispatching on type parameters is just not recommended (especially when we have so many existing methods already), since it's prone to introducing ambiguities and increases latency.

It's better than introducing a bug, though. If you can fix the underlying bugs to make kron work with the recursive matrices, great, we can remove the specialization to <: Number. I can't.

IIRC, then this is what the compiler does: it specializes on function arguments whenever they are called in the function body, and not merely passed on as an argument. I'll need to double-check.

Well they are just passed on as an argument, no? I'm pretty sure it wasn't specializing without it.

Sure, but now we have stdlibs in an ambiguous state. So we can't kron two symmetric/triangular sparse matrices, not even with some generic fallback. The other option then would be to work out the analogue of #53186 for symmetric/hermitian/triangular sparse matrices, before you get to the Hermitian(Diagonal) case.

Sure, I was just complaining, we can't let a method ambiguity stay.

dkarrasch · 2024-05-10T09:17:30Z

Not to insist, but to learn something: I read

https://docs.julialang.org/en/v1/manual/performance-tips/#Be-aware-of-when-Julia-avoids-specializing

as it will specialize since in our case, the Function arguments are called within _hermkron!, not just passed as an argument to another function.

araujoms · 2024-05-10T10:36:35Z

Fair enough, it is specializing then. I did a quick test to confirm it:

f(x) = x^2
g(x) = abs2(x)
test(z::Real) = do_power(z,f)
test(z::Complex) = do_power(z,g)
do_power(z,h) = h(z)

It wasn't actually me who added this parametrization, but I can't find in the PR who did, so I could ask what they had in mind. I guess it doesn't really matter.

dkarrasch · 2024-05-10T11:49:44Z

Could well be me (who suggested it) at the time. I remember looking it up not so long ago.

dkarrasch · 2024-05-14T14:33:52Z

How about this now? The signature could be relaxed again once somebody writes sparse kron-kernels, but for now I think this is not too bad.

araujoms · 2024-05-14T15:20:17Z

I think it's fine now. I'd suggest adding the four lines I posted above to the tests, so that this bug doesn't get accidentally reintroduced.

araujoms · 2024-05-14T16:16:08Z

Thanks! I've opened an issue to track the underlying problem.

@dkarrasch

Using the recently introduced recursive `zero` I can remove the specialization to `<:Number` as @dkarrasch wanted to do in #54413. --------- Co-authored-by: Jishnu Bhattacharya <[email protected]>

* Improve type-stability in SymTridiagonal triu!/tril! (#55646) Changing the final `elseif` branch to an `else` makes it clear that the method definite returns a value, and the returned type is now a `Tridiagonal` instead of a `Union{Nothing, Tridiagonal}` * Reuse size-check function from `lacpy!` in `copytrito!` (#55664) Since there is a size-check function in `lacpy!` that does the same thing, we may reuse it instead of duplicating the check * Update calling-c-and-fortran-code.md: fix ccall parameters (not a tuple) (#55665) * Allow exact redefinition for types with recursive supertype reference (#55380) This PR allows redefining a type when the new type is exactly identical to the previous one (like #17618, #20592 and #21024), even if the type has a reference to itself in its supertype. That particular case used to error (issue #54757), whereas with this PR: ```julia julia> struct Rec <: AbstractVector{Rec} end julia> struct Rec <: AbstractVector{Rec} end # this used to error julia> ``` Fix #54757 by implementing the solution proposed there. Hence, this should also fix downstream Revise bug https://github.com/timholy/Revise.jl/issues/813. --------- Co-authored-by: N5N3 <[email protected]> * Reroute Symmetric/Hermitian + Diagonal through triangular (#55605) This should fix the `Diagonal`-related issue from https://github.com/JuliaLang/julia/issues/55590, although the `SymTridiagonal` one still remains. ```julia julia> using LinearAlgebra julia> a = Matrix{BigFloat}(undef, 2,2) 2×2 Matrix{BigFloat}: #undef #undef #undef #undef julia> a[1] = 1; a[3] = 1; a[4] = 1 1 julia> a = Hermitian(a) 2×2 Hermitian{BigFloat, Matrix{BigFloat}}: 1.0 1.0 1.0 1.0 julia> b = Symmetric(a) 2×2 Symmetric{BigFloat, Matrix{BigFloat}}: 1.0 1.0 1.0 1.0 julia> c = Diagonal([1,1]) 2×2 Diagonal{Int64, Vector{Int64}}: 1 ⋅ ⋅ 1 julia> a+c 2×2 Hermitian{BigFloat, Matrix{BigFloat}}: 2.0 1.0 1.0 2.0 julia> b+c 2×2 Symmetric{BigFloat, Matrix{BigFloat}}: 2.0 1.0 1.0 2.0 ``` * inference: check argtype compatibility in `abstract_call_opaque_closure` (#55672) * Forward istriu/istril for triangular to parent (#55663) * win: move stack_overflow_warning to the backtrace fiber (#55640) There is not enough stack space remaining after a stack overflow on Windows to allocate the 4k page used by `write` to call the WriteFile syscall. This causes it to hard-crash. But we can simply run this on the altstack implementation, where there is plenty of space. * Check if ct is not null before doing is_addr_on_stack in the macos signal handler. (#55603) Before the check we used to segfault while segfaulting and hang --------- Co-authored-by: Jameson Nash <[email protected]> * Profile.print: color Base/Core & packages. Make paths clickable (#55335) Updated ## This PR ![Screenshot 2024-09-02 at 1 47 23 PM](https://github.com/user-attachments/assets/1264e623-70b2-462a-a595-1db2985caf64) ## master ![Screenshot 2024-09-02 at 1 49 42 PM](https://github.com/user-attachments/assets/14d62fe1-c317-4df5-86e9-7c555f9ab6f1) Todo: - [ ] ~Maybe drop the `@` prefix when coloring it, given it's obviously special when colored~ If someone copy-pasted the profile into an issue this would make it confusing. - [ ] Figure out why `Profile.print(format=:flat)` is truncating before the terminal width is used up - [x] Make filepaths terminal links (even if they're truncated) * better signal handling (#55623) Instead of relying on creating a fake stack frame, and having no signals delivered, kernel bugs, accidentally gc_collect, or other issues occur during the delivery and execution of these calls, use the ability we added recently to emulate a longjmp into a unw_context to eliminate any time where there would exist any invalid states. Secondly, when calling jl_exit_thread0_cb, we used to end up completely smashing the unwind info (with CFI_NOUNWIND), but this makes core files from SIGQUIT much less helpful, so we now have a `fake_stack_pop` function with contains the necessary CFI directives such that a minimal unwind from the debugger will likely still succeed up into the frames that were removed. We cannot do this perfectly on AArch64 since that platform's DWARF spec lacks the ability to do so. On other platforms, this should be possible to implement exactly (subject to libunwind implementation quality). This is currently thus only fully implemented for x86_64 on Darwin Apple. * fix `exct` for mismatched opaque closure call * improve `exct` modeling for opaque closure calls * fix `nothrow` modeling for `invoke` calls * improve `exct` modeling for `invoke` calls * show a bit more detail when finished precompiling (#55660) * subtype: minor clean up for fast path for lhs union and rhs typevar (#55645) Follow up #55413. The error pattern mentioned in https://github.com/JuliaLang/julia/pull/55413#issuecomment-2288384468 care's `∃y`'s ub in env rather than its original ub. So it seems more robust to check the bounds in env directly. The equivalent typevar propagation is lifted from `subtype_var` for the same reason. * Adding `JL_DATA_TYPE` annotation to `_jl_globalref_t` (#55684) `_jl_globalref_t` seems to be allocated in the heap, and there is an object `jl_globalref_type` which indicates that it is in fact, a data type, thus it should be annotated with `JL_DATA_TYPE`?? * Make GEP when loading the PTLS an inbounds one. (#55682) Non inbounds GEPs should only be used when doing pointer arithmethic i.e Ptr or MemoryRef boundscheck. Found when auditing non inbounds GEPs for https://github.com/JuliaLang/julia/pull/55681 * codegen: make boundscheck GEP not be inbounds while the load GEP is inbounds (#55681) Avoids undefined behavior on the boundschecking arithmetic, which is correct only assuming overflow follows unsigned arithmetic wrap around rules. Also add names to the Memory related LLVM instructions to aid debugging Closes: https://github.com/JuliaLang/julia/pull/55674 * Make `rename` public (#55652) Fixes #41584. Follow up of #55503 I think `rename` is a very useful low-level file system operation. Many other programming languages have this function, so it is useful when porting IO code to Julia. One use case is to improve the Zarr.jl package to be more compatible with zarr-python. https://github.com/zarr-developers/zarr-python/blob/0b5483a7958e2ae5512a14eb424a84b2a75dd727/src/zarr/v2/storage.py#L994 uses the `os.replace` function. It would be nice to be able to directly use `Base.rename` as a replacement for `os.replace` to ensure compatibility. Another use case is writing a safe zip file extractor in pure Julia. https://github.com/madler/sunzip/blob/34107fa9e2a2e36e7e72725dc4c58c9ad6179898/sunzip.c#L365 uses the `rename` function to do this in C. Lastly in https://github.com/medyan-dev/MEDYANSimRunner.jl/blob/67d5b42cc599670486d5d640260a95e951091f7a/src/file-saving.jl#L83 I am using `ccall(:jl_fs_rename` to save files, because I have large numbers of Julia processes creating and reading these files at the same time on a distributed file system on a cluster, so I don't want data to become corrupted if one of the nodes crashes (which happens fairly regularly). However `jl_fs_rename` is not public, and might break in a future release. This PR also adds a note to `mv` comparing it to the `mv` command, similar to the note on the `cp` function. * contrib: include private libdir in `ldflags` on macOS (#55687) The private libdir is used on macOS, so it needs to be included in our `ldflags` * Profile.print: Shorten C paths too (#55683) * [LLVMLibUnwindJLL] Update llvmlibunwind to 14.0.6 (#48140) * Add `JL_DATA_TYPE` for `jl_line_info_node_t` and `jl_code_info_t` (#55698) * Canonicalize names of nested functions by keeping a more fine grained counter -- per (module, method name) pair (#53719) As mentioned in https://github.com/JuliaLang/julia/pull/53716, we've been noticing that `precompile` statements lists from one version of our codebase often don't apply cleanly in a slightly different version. That's because a lot of nested and anonymous function names have a global numeric suffix which is incremented every time a new name is generated, and these numeric suffixes are not very stable across codebase changes. To solve this, this PR makes the numeric suffixes a bit more fine grained: every pair of (module, top-level/outermost function name) will have its own counter, which should make nested function names a bit more stable across different versions. This PR applies @JeffBezanson's idea of making the symbol name changes directly in `current-julia-module-counter`. Here is an example: ```Julia julia> function foo(x) function bar(y) return x + y end end foo (generic function with 1 method) julia> f = foo(42) (::var"#bar#foo##0"{Int64}) (generic function with 1 method) ``` * Use `uv_available_parallelism` inside `jl_effective_threads` (#55592) * [LinearAlgebra] Initialise number of BLAS threads with `jl_effective_threads` (#55574) This is a safer estimate than `Sys.CPU_THREADS` to avoid oversubscribing the machine when running distributed applications, or when the Julia process is constrained by external controls (`taskset`, `cgroups`, etc.). Fix #55572 * Artifacts: Improve type-stability (#55707) This improves Artifacts.jl to make `artifact"..."` fully type-stable, so that it can be used with `--trim`. This is a requirement for JLL support w/ trimmed executables. Dependent on https://github.com/JuliaLang/julia/pull/55016 --------- Co-authored-by: Gabriel Baraldi <[email protected]> * Remove redundant conversion in structured matrix broadcasting (#55695) The additional construction is unnecessary, as we are already constructing a `Matrix`. Performance: ```julia julia> using LinearAlgebra julia> U = UpperTriangular(rand(1000,1000)); julia> L = LowerTriangular(rand(1000,1000)); julia> @btime $U .+ $L; 1.956 ms (6 allocations: 15.26 MiB) # nightly 1.421 ms (3 allocations: 7.63 MiB) # This PR ``` * [Profile] fix threading issue (#55704) I forgot about the existence of threads, so had hard-coded this to only support one thread. Clearly that is not sufficient though, so use the semaphore here as it is intended to be used. Fixes #55703 --------- Co-authored-by: Ian Butterworth <[email protected]> * delete flaky ranges/`TwicePrecision` test (#55712) Fixes #55710 * Avoid stack overflow in triangular eigvecs (#55497) This fixes a stack overflow in ```julia julia> using LinearAlgebra, StaticArrays julia> U = UpperTriangular(SMatrix{2,2}(1:4)) 2×2 UpperTriangular{Int64, SMatrix{2, 2, Int64, 4}} with indices SOneTo(2)×SOneTo(2): 1 3 ⋅ 4 julia> eigvecs(U) Warning: detected a stack overflow; program state may be corrupted, so further execution might be unreliable. ERROR: StackOverflowError: Stacktrace: [1] eigvecs(A::UpperTriangular{Float32, SMatrix{2, 2, Float32, 4}}) (repeats 79984 times) @ LinearAlgebra ~/.julia/juliaup/julia-nightly/share/julia/stdlib/v1.12/LinearAlgebra/src/triangular.jl:2749 ``` After this, ```julia julia> eigvecs(U) 2×2 Matrix{Float32}: 1.0 1.0 0.0 1.0 ``` * builtins: add `Core.throw_methoderror` (#55705) This allows us to simulate/mark calls that are known-to-fail. Required for https://github.com/JuliaLang/julia/pull/54972/ * Small missing tests for Irrationals (#55657) Looks like a bunch of methods for `Irrational`s are tested but not picked up by coverage... * Implement faster thread local rng for scheduler (#55501) Implement optimal uniform random number generator using the method proposed in https://github.com/swiftlang/swift/pull/39143 based on OpenSSL's implementation of it in https://github.com/openssl/openssl/blob/1d2cbd9b5a126189d5e9bc78a3bdb9709427d02b/crypto/rand/rand_uniform.c#L13-L99 This PR also fixes some bugs found while developing it. This is a replacement for https://github.com/JuliaLang/julia/pull/50203 and fixes the issues found by @IanButterworth with both rngs C rng <img width="1011" alt="image" src="https://github.com/user-attachments/assets/0dd9d5f2-17ef-4a70-b275-1d12692be060"> New scheduler rng <img width="985" alt="image" src="https://github.com/user-attachments/assets/4abd0a57-a1d9-46ec-99a5-535f366ecafa"> ~On my benchmarks the julia implementation seems to be almost 50% faster than the current implementation.~ With oscars suggestion of removing the debiasing this is now almost 5x faster than the original implementation. And almost fully branchless We might want to backport the two previous commits since they technically fix bugs. --------- Co-authored-by: Valentin Churavy <[email protected]> * Add precompile signatures to Markdown to reduce latency. (#55715) Fixes #55706 that is seemingly a 4472x regression, not just 16x (was my first guess, based on CondaPkg, also fixes or greatly mitigates https://github.com/JuliaPy/CondaPkg.jl/issues/145), and large part of 3x regression for PythonCall. --------- Co-authored-by: Kristoffer Carlsson <[email protected]> * Fix invalidations for FileIO (#55593) Fixes https://github.com/JuliaIO/FileIO.jl/issues/396 * Fix various issues with PGO+LTO makefile (#55581) This fixes various issues with the PGO+LTO makefile - `USECCACHE` doesn't work throwing an error at https://github.com/JuliaLang/julia/blob/eb5587dac02d1f6edf486a71b95149139cc5d9f7/Make.inc#L734 This is because setting `CC` and `CCX` by passing them as arguments to `make` prevents `Make.inc` from prepending these variables with `ccache` as `Make.inc` doesn't use override. To workaround this I instead set `USECLANG` and add the toolchain to the `PATH`. - To deal with similar issues for the other make flags, I pass them as environment variables which can be edited in `Make.inc`. - I add a way to build in one go by creating the `all` target, now you can just run `make` and a PGO+LTO build that profiles Julia's build will be generated. - I workaround `PROFRAW_FILES` not being reevaluated after `stage1` builds, this caused the generation of `PROFILE_FILE` to run an outdated command if `stage1` was built and affected the profraw files. This is important when building in one go. - I add a way to run rules like `binary-dist` which are not defined in this makefile with the correct toolchain which for example prevents `make binary-dist` from unnecessarily rebuilding `sys.ji`. - Include `-Wl,--undefined-version` till https://github.com/JuliaLang/julia/issues/54533 gets fixed. These changes need to be copied to the PGO+LTO+BOLT makefile and some to the BOLT makefile in a later pr. --------- Co-authored-by: Zentrik <[email protected]> * Fix `pkgdir` for extensions (#55720) Fixes https://github.com/JuliaLang/julia/issues/55719 --------- Co-authored-by: Max Horn <[email protected]> * Avoid materializing arrays in bidiag matmul (#55450) Currently, small `Bidiagonal`/`Tridiagonal` matrices are materialized in matrix multiplications, but this is wasteful and unnecessary. This PR changes this to use a naive matrix multiplication for small matrices, and fall back to the banded multiplication for larger ones. Multiplication by a `Bidiagonal` falls back to a banded matrix multiplication for all sizes in the current implementation, and iterates in a cache-friendly manner for the non-`Bidiagonal` matrix. In certain cases, the matrices were being materialized if the non-structured matrix was small, even if the structured matrix was large. This is changed as well in this PR. Some improvements in performance: ```julia julia> B = Bidiagonal(rand(3), rand(2), :U); A = rand(size(B)...); C = similar(A); julia> @btime mul!($C, $A, $B); 193.152 ns (6 allocations: 352 bytes) # nightly v"1.12.0-DEV.1034" 18.826 ns (0 allocations: 0 bytes) # This PR julia> T = Tridiagonal(rand(99), rand(100), rand(99)); A = rand(2, size(T,2)); C = similar(A); julia> @btime mul!($C, $A, $T); 9.398 μs (8 allocations: 79.94 KiB) # nightly 416.407 ns (0 allocations: 0 bytes) # This PR julia> B = Bidiagonal(rand(300), rand(299), :U); A = rand(20000, size(B,2)); C = similar(A); julia> @btime mul!($C, $A, $B); 33.395 ms (0 allocations: 0 bytes) # nightly 6.695 ms (0 allocations: 0 bytes) # This PR (cache-friendly) ``` Closes https://github.com/JuliaLang/julia/pull/55414 --------- Co-authored-by: Daniel Karrasch <[email protected]> * Fix `@time_imports` extension recognition (#55718) * drop typed GEP calls (#55708) Now that we use LLVM 18, and almost have LLVM 19 support, do cleanup to remove LLVM 15/16 type pointer support. LLVM now slightly prefers that we rewrite our complex GEP to use a simple emit_ptrgep call instead, which is also much simpler for julia to emit also. * minor fixup for JuliaLang/julia#55705 (#55726) * [REPL] prevent silent hang if precompile script async blocks fail (#55685) * Various fixes to byte / bytearray search (#54579) This was originally intended as a targeted fix to #54578, but I ran into a bunch of smaller issues with this code that also needed to be solved and it turned out to be difficult to fix them with small, trivial PRs. I would also like to refactor this whole file, but I want these correctness fixes to be merged first, because a larger refactoring has higher risk of getting stuck without getting reviewed and merged. ## Larger things that needs decisions * The internal union `Base.ByteArray` has been deleted. Instead, the unions `DenseInt8` and `DenseUInt8` have been added. These more comprehensively cover the types that was meant, e.g. `Memory{UInt8}` was incorrectly not covered by the former. As stated in the TODO, the concept of a "memory backed dense byte array" is needed throughout Julia, so this ideally needs to be implemented as a single type and used throughout Base. The fix here is a decent temporary solution. See #53178 #54581 * The `findall` docstring between two arrays was incorrectly not attached to the method - now it is. **Note that this change _changes_ the documentation** since it includes a docstring that was previously missed. Hence, it's an API addition. * Added a new minimal `testhelpers/OffsetDenseArrays.jl` which provide a `DenseVector` with offset axes for testing purposes. ## Trivial fixes * `findfirst(==(Int8(-1)), [0xff])` and similar findlast, findnext and findprev is no longer buggy, see #54578 * `findfirst([0x0ff], Int8[-1])` is similarly no longer buggy, see #54578 * `findnext(==('\xa6'), "æ", 1)` and `findprev(==('\xa6'), "æa", 2)` no longer incorrectly throws an error * The byte-oriented find* functions now work correctly with offset arrays * Fixed incorrect use of `GC.@preserve`, where the pointer was taken before the preserve block. * More of the optimised string methods now also apply to `SubString{String}` Closes #54578 Co-authored-by: Martin Holters <[email protected]> * codegen: deduplicate code for calling a specsig (#55728) I am tired of having 3 gratuitously different versions of this code to maintain. * Fix "Various fixes to byte / bytearray search" (#55734) Fixes the conflict between #54593 and #54579 `_search` returns `nothing` instead of zero as a sentinal in #54579 * Fix `make binary-dist` when using `USE_BINARYBUILDER_LLVM=0` (#55731) `make binary-dist` expects lld to be in usr/tools but it ends up in usr/bin so I copied it into usr/tools. Should fix the scheduled source tests which currently fail at linking. I think this is also broken with `USE_BINARYBUILDER_LLVM=0` and `BUILD_LLD=0`, maybe https://github.com/JuliaLang/julia/commit/ceaeb7b71bc76afaca2f3b80998164a47e30ce33 is the fix? --------- Co-authored-by: Zentrik <[email protected]> * Precompile the `@time_imports` printing so it doesn't confuse reports (#55729) Makes functions for the report printing that can be precompiled into the sysimage. * codegen: some cleanup of layout computations (#55730) Change Alloca to take an explicit alignment, rather than relying on LLVM to guess our intended alignment from the DataLayout. Eventually we should try to change this code to just get all layout data from julia queries (jl_field_offset, julia_alignment, etc.) instead of relying on creating an LLVM element type for memory and inspecting it (CountTrackedPointers, DataLayout, and so on). * Add some loading / LazyArtifacts precompiles to the sysimage (#55740) Fixes https://github.com/JuliaLang/julia/issues/55725 These help LazyArtifacts mainly but seem beneficial for the sysimage. * Update stable version number in readme to v1.10.5 (#55742) * Add `invokelatest` barrier to `string(...)` in `@assert` (#55739) This change protects `@assert` from invalidations to `Base.string(...)` by adding an `invokelatest` barrier. A common source of invalidations right now is `print(io, join(args...))`. The problem is: 1. Inference concludes that `join(::Any...)` returns `Union{String,AnnotatedString}` 2. The `print` call is union-split to `String` and `AnnotatedString` 3. This code is now invalidated when StyledStrings defines `print(io, ::AnnotatedString)` The invalidation chain for `@assert` is similar: ` @assert 1 == 1` calls into `string(::Expr)` which calls into `print(io, join(args::Any...))`. Unfortunately that leads to the invalidation of almost all `@assert`s without an explicit error message Similar to https://github.com/JuliaLang/julia/pull/55583#issuecomment-2308969806 * Don't show string concatenation error hint with zero arg `+` (#55749) Closes #55745 * Don't leave trailing whitespace when printing do-block expr (#55738) Before, when printing a `do`-block, we'd print a white-space after `do` even if no arguments follow. Now we don't print that space. --------- Co-authored-by: Lilith Orion Hafner <[email protected]> * Don't pass lSystem to the linker since macos always links it (#55722) This stops it complaing about duplicated libs. For libunwind there isn't much we can do because it's part of lsystem and we also need out own. * define `numerator` and `denominator` for `Complex` (#55694) Fixes #55693 * More testsets for SubString and a few missing tests (#55656) Co-authored-by: Simeon David Schaub <[email protected]> * Reorganize search tests into testsets (#55658) Some of these tests are nearly 10 years old! Organized some of them into testsets just in case one breaks in the future, should make it easier to find the problem. --------- Co-authored-by: Simeon David Schaub <[email protected]> * fix #45494, error in ssa conversion with complex type decl (#55744) We were missing a call to `renumber-assigned-ssavalues` in the case where the declared type is used to assert the type of a value taken from a closure box. * Revert "Avoid materializing arrays in bidiag matmul" (#55737) Reverts JuliaLang/julia#55450. @jishnub suggested reverting this PR to fix #55727. * Add a docs section about loading/precomp/ttfx time tuning (#55569) * Add compat entry for `Base.donotdelete` (#55773) * REPL: precompile in its own module because Main is closed. Add check for unexpected errors. (#55759) * Try to put back previously flakey addmul tests (#55775) Partial revert of #50071, inspired by conversation in https://github.com/JuliaLang/julia/issues/49966#issuecomment-2350935477 Ran the tests 100 times to make sure we're not putting back something that's still flaky. Closes #49966 * Print results of `runtests` with `printstyled` (#55780) This ensures escape characters are used only if `stdout` can accept them. * move null check in `unsafe_convert` of RefValue (#55766) LLVM can optimize out this check but our optimizer can't, so this leads to smaller IR in most cases. * Fix hang in tmerge_types_slow (#55757) Fixes https://github.com/JuliaLang/julia/issues/55751 Co-authored-by: Jameson Nash <[email protected]> * trace-compile: color recompilation yellow (#55763) Marks recompilation of a method that produced a `precompile` statement as yellow, or if color isn't supported adds a trailing comment: `# recompilation`. The coloring matches the `@time_imports` coloring. i.e. an excerpt of ``` % ./julia --start=no --trace-compile=stderr --trace-compile-timing -e "using InteractiveUtils; @time @time_imports using Plots" ``` ![Screenshot 2024-09-13 at 5 04 24 PM](https://github.com/user-attachments/assets/85bd99e0-586e-4070-994f-2d845be0d9e7) * Use PrecompileTools mechanics to compile REPL (#55782) Fixes https://github.com/JuliaLang/julia/issues/55778 Based on discussion here https://github.com/JuliaLang/julia/issues/55778#issuecomment-2352428043 With this `?reinterpret` feels instant, with only these precompiles at the start. ![Screenshot 2024-09-16 at 9 49 39 AM](https://github.com/user-attachments/assets/20dc016d-c6f7-4870-acd7-0e795dcf541b) * use `inferencebarrier` instead of `invokelatest` for 1-arg `@assert` (#55783) This version would be better as per this comment: <https://github.com/JuliaLang/julia/pull/55739#pullrequestreview-2304360447> I confirmed this still allows us to avoid invalidations reported at JuliaLang/julia#55583. * Inline statically known method errors. (#54972) This replaces the `Expr(:call, ...)` with a call of a new builtin `Core.throw_methoderror` This is useful because it makes very clear if something is a static method error or a plain dynamic dispatch that always errors. Tools such as AllocCheck or juliac can notice that this is not a genuine dynamic dispatch, and prevent it from becoming a false positive compile-time error. Dependent on https://github.com/JuliaLang/julia/pull/55705 --------- Co-authored-by: Cody Tapscott <[email protected]> * Fix shell `cd` error when working dir has been deleted (#41244) root cause: if current dir has been deleted, then pwd() will throw an IOError: pwd(): no such file or directory (ENOENT) --------- Co-authored-by: Ian Butterworth <[email protected]> * codegen: fix bits compare for UnionAll (#55770) Fixes #55768 in two parts: one is making the type computation in emit_bits_compare agree with the parent function and two is not using the optimized egal code for UnionAll kinds, which is different from how the egal code itself works for kinds. * use libuv to measure maxrss (#55806) Libuv has a wrapper around rusage on Unix (and its equivalent on Windows). We should probably use it. * REPL: use atreplinit to change the active module during precompilation (#55805) * 🤖 [master] Bump the Pkg stdlib from 299a35610 to 308f9d32f (#55808) * Improve codegen for `Core.throw_methoderror` and `Core.current_scope` (#55803) This slightly improves our (LLVM) codegen for `Core.throw_methoderror` and `Core.current_scope` ```julia julia> foo() = Core.current_scope() julia> bar() = Core.throw_methoderror(+, nothing) ``` Before: ```llvm ; Function Signature: foo() define nonnull ptr @julia_foo_2488() #0 { top: %0 = call ptr @jl_get_builtin_fptr(ptr nonnull @"+Core.#current_scope#2491.jit") %Builtin_ret = call nonnull ptr %0(ptr nonnull @"jl_global#2492.jit", ptr null, i32 0) ret ptr %Builtin_ret } ; Function Signature: bar() define void @julia_bar_589() #0 { top: %jlcallframe1 = alloca [2 x ptr], align 8 %0 = call ptr @jl_get_builtin_fptr(ptr nonnull @"+Core.#throw_methoderror#591.jit") %jl_nothing = load ptr, ptr @jl_nothing, align 8 store ptr @"jl_global#593.jit", ptr %jlcallframe1, align 8 %1 = getelementptr inbounds ptr, ptr %jlcallframe1, i64 1 store ptr %jl_nothing, ptr %1, align 8 %Builtin_ret = call nonnull ptr %0(ptr nonnull @"jl_global#592.jit", ptr nonnull %jlcallframe1, i32 2) call void @llvm.trap() unreachable } ``` After: ```llvm ; Function Signature: foo() define nonnull ptr @julia_foo_713() #0 { top: %thread_ptr = call ptr asm "movq %fs:0, $0", "=r"() #5 %tls_ppgcstack = getelementptr inbounds i8, ptr %thread_ptr, i64 -8 %tls_pgcstack = load ptr, ptr %tls_ppgcstack, align 8 %current_scope = getelementptr inbounds i8, ptr %tls_pgcstack, i64 -72 %0 = load ptr, ptr %current_scope, align 8 ret ptr %0 } ; Function Signature: bar() define void @julia_bar_1581() #0 { top: %jlcallframe1 = alloca [2 x ptr], align 8 %jl_nothing = load ptr, ptr @jl_nothing, align 8 store ptr @"jl_global#1583.jit", ptr %jlcallframe1, align 8 %0 = getelementptr inbounds ptr, ptr %jlcallframe1, i64 1 store ptr %jl_nothing, ptr %0, align 8 %jl_f_throw_methoderror_ret = call nonnull ptr @jl_f_throw_methoderror(ptr null, ptr nonnull %jlcallframe1, i32 2) call void @llvm.trap() unreachable } ``` * a minor improvement for EA-based `:effect_free`-ness refinement (#55796) * fix #52986, regression in `@doc` of macro without REPL loaded (#55795) fix #52986 * Assume that docstring code with no lang is julia (#55465) * Broadcast binary ops involving strided triangular (#55798) Currently, we evaluate expressions like `(A::UpperTriangular) + (B::UpperTriangular)` using broadcasting if both `A` and `B` have strided parents, and forward the summation to the parents otherwise. This PR changes this to use broadcasting if either of the two has a strided parent. This avoids accessing the parent corresponding to the structural zero elements, as the index might not be initialized. Fixes https://github.com/JuliaLang/julia/issues/55590 This isn't a general fix, as we still sum the parents if neither is strided. However, it will address common cases. This also improves performance, as we only need to loop over one half: ```julia julia> using LinearAlgebra julia> U = UpperTriangular(zeros(100,100)); julia> B = Bidiagonal(zeros(100), zeros(99), :U); julia> @btime $U + $B; 35.530 μs (4 allocations: 78.22 KiB) # nightly 13.441 μs (4 allocations: 78.22 KiB) # This PR ``` * Reland " Avoid materializing arrays in bidiag matmul #55450" (#55777) This relands #55450 and adds tests for the failing case noted in https://github.com/JuliaLang/julia/issues/55727. The `addmul` tests that were failing earlier pass with this change. The issue in the earlier PR was that we were not exiting quickly for `iszero(alpha)` in `_bibimul!` for small matrices, and were computing the result as `C .= A * B * alpha + C * beta`. The problem with this is that if `A * B` contains `NaN`s, this propagates to `C` even if `alpha === 0.0`. This is fixed now, and the result is only computed if `!iszero(alpha)`. * move the test case added in #50174 to test/core.jl (#55811) Also renames the name of the test function to avoid name collision. * [Random] Avoid conversion to `Float32` in `Float16` sampler (#55819) * simplify the fields of `UnionSplitInfo` (#55815) xref: <https://github.com/JuliaLang/julia/pull/54972#discussion_r1766187771> * Add errorhint for nonexisting fields and properties (#55165) I played a bit with error hints and crafted this: ```julia julia> (1+2im).real ERROR: FieldError: type Complex has no field real, available fields: `re`, `im` julia> nothing.xy ERROR: FieldError: type Nothing has no field xy; Nothing has no fields at all. julia> svd(rand(2,2)).VV ERROR: FieldError: type SVD has no field VV, available fields: `U`, `S`, `Vt` Available properties: `V` ``` --------- Co-authored-by: Lilith Orion Hafner <[email protected]> * Improve printing of several arguments (#55754) Following a discussion on [Discourse](https://discourse.julialang.org/t/string-optimisation-in-julia/119301/10?u=gdalle), this PR tries to improve `print` (and variants) for more than one argument. The idea is that `for` is type-unstable over the tuple `args`, while `foreach` unrolls. --------- Co-authored-by: Steven G. Johnson <[email protected]> * Markdown: support `parse(::AbstractString)` (#55747) `Markdown.parse` is documented to accept `AbstractString` but it was implemented by calling `IOBuffer` on the string argument. `IOBuffer`, however, is documented only for `String` arguments. This commit changes the current `parse(::AbstractString)` to `parse(::String)` and implements `parse(::AbstractString)` by converting the argument to `String`. Now, even `LazyString`s can be parsed to Markdown representation. Fixes #55732 * better error for esc outside of macro expansion (#55797) fixes #55788 --------- Co-authored-by: Jeff Bezanson <[email protected]> * allow kronecker product between recursive triangular matrices (#55527) Using the recently introduced recursive `zero` I can remove the specialization to `<:Number` as @dkarrasch wanted to do in #54413. --------- Co-authored-by: Jishnu Bhattacharya <[email protected]> * [Dates] Make test more robust against non-UTC timezones (#55829) `%M` is the format specifier for the minutes, not the month (which should be `%m`), and it was used twice. Also, on macOS `Libc.strptime` internally calls `mktime` which depends on the local timezone. We now temporarily set `TZ=UTC` to avoid depending on the local timezone. Fix #55827. * 🤖 [master] Bump the Pkg stdlib from 308f9d32f to ef9f76c17 (#55838) * lmul!/rmul! for banded matrices (#55823) This adds fast methods for `lmul!` and `rmul!` between banded matrices and numbers. Performance impact: ```julia julia> T = Tridiagonal(rand(999), rand(1000), rand(999)); julia> @btime rmul!($T, 0.2); 4.686 ms (0 allocations: 0 bytes) # nightly v"1.12.0-DEV.1225" 669.355 ns (0 allocations: 0 bytes) # this PR ``` * Specialize indexing triangular matrices with BandIndex (#55644) With this, certain indexing operations involving a `BandIndex` may be evaluated as constants. This isn't used directly presently, but might allow for more performant broadcasting in the future. With this, ```julia julia> n = 3; T = Tridiagonal(rand(n-1), rand(n), rand(n-1)); julia> @code_warntype ((T,j) -> UpperTriangular(T)[LinearAlgebra.BandIndex(2,j)])(T, 1) MethodInstance for (::var"#17#18")(::Tridiagonal{Float64, Vector{Float64}}, ::Int64) from (::var"#17#18")(T, j) @ Main REPL[12]:1 Arguments #self#::Core.Const(var"#17#18"()) T::Tridiagonal{Float64, Vector{Float64}} j::Int64 Body::Float64 1 ─ %1 = Main.UpperTriangular(T)::UpperTriangular{Float64, Tridiagonal{Float64, Vector{Float64}}} │ %2 = LinearAlgebra.BandIndex::Core.Const(LinearAlgebra.BandIndex) │ %3 = (%2)(2, j)::Core.PartialStruct(LinearAlgebra.BandIndex, Any[Core.Const(2), Int64]) │ %4 = Base.getindex(%1, %3)::Core.Const(0.0) └── return %4 ``` The indexing operation may be evaluated at compile-time, as the band index is constant-propagated. * Replace regex package module checks with actual code checks (#55824) Fixes https://github.com/JuliaLang/julia/issues/55792 Replaces https://github.com/JuliaLang/julia/pull/55822 Improves what https://github.com/JuliaLang/julia/pull/51635 was trying to do i.e. ``` ERROR: LoadError: `using/import Printf` outside of a Module detected. Importing a package outside of a module is not allowed during package precompilation. ``` * fall back to slower stat filesize if optimized filesize fails (#55641) * Use "index" instead of "subscript" to refer to indexing in performance tips (#55846) * privatize annotated string API, take two (#55845) https://github.com/JuliaLang/julia/pull/55453 is stuck on StyledStrings and Base documentation being entangled and there isn't a good way to have the documentation of Base types / methods live in an stdlib. This is a stop gap solution to finally be able to move forwards with 1.11. * 🤖 [master] Bump the Downloads stdlib from 1061ecc to 89d3c7d (#55854) Stdlib: Downloads URL: https://github.com/JuliaLang/Downloads.jl.git Stdlib branch: master Julia branch: master Old commit: 1061ecc New commit: 89d3c7d Julia version: 1.12.0-DEV Downloads version: 1.6.0(It's okay that it doesn't match) Bump invoked by: @KristofferC Powered by: [BumpStdlibs.jl](https://github.com/JuliaLang/BumpStdlibs.jl) Diff: https://github.com/JuliaLang/Downloads.jl/compare/1061ecc377a053fce0df94e1a19e5260f7c030f5...89d3c7dded535a77551e763a437a6d31e4d9bf84 ``` $ git log --oneline 1061ecc..89d3c7d 89d3c7d fix cancelling upload requests (#259) df33406 gracefully cancel a request (#256) ``` Co-authored-by: Dilum Aluthge <[email protected]> * docs: Small edits to noteworthy differences (#55852) - The first line edit changes it so that the Julia example goes first, not the Python example, keeping with the general flow of the lines above. - The second adds a "the" that is missing. * Add filesystem func to transform a path to a URI (#55454) In a few places across Base and the stdlib, we emit paths that we like people to be able to click on in their terminal and editor. Up to this point, we have relied on auto-filepath detection, but this does not allow for alternative link text, such as contracted paths. Doing so (via OSC 8 terminal links for example) requires filepath URI encoding. This functionality was previously part of a PR modifying stacktrace printing (#51816), but after that became held up for unrelated reasons and another PR appeared that would benefit from this utility (#55335), I've split out this functionality so it can be used before the stacktrace printing PR is resolved. * constrain the path argument of `include` functions to `AbstractString` (#55466) Each `Module` defined with `module` automatically gets an `include` function with two methods. Each of those two methods takes a file path as its last argument. Even though the path argument is unconstrained by dispatch, it's documented as constrained with `::AbstractString`: https://docs.julialang.org/en/v1.11-dev/base/base/#include Furthermore, I think that any invocation of `include` with a non-`AbstractString` path will necessarily throw a `MethodError` eventually. Thus this change should be harmless. Adding the type constraint to the path argument is an improvement because any possible exception would be thrown earlier than before. Apart from modules defined with `module`, the same issue is present with the anonymous modules created by `evalfile`, which is also addressed. Sidenote: `evalfile` seems to be completely untested apart from the test added here. Co-authored-by: Florian <[email protected]> * Mmap: fix grow! for non file IOs (#55849) Fixes https://github.com/JuliaLang/julia/issues/54203 Requires #55641 Based on https://github.com/JuliaLang/julia/pull/55641#issuecomment-2334162489 cc. @JakeZw @ronisbr --------- Co-authored-by: Jameson Nash <[email protected]> * codegen: split gc roots from other bits on stack (#55767) In order to help avoid memory provenance issues, and better utilize stack space (somewhat), and use FCA less, change the preferred representation of an immutable object to be a pair of `<packed-data,roots>` values. This packing requires some care at the boundaries and if the expected field alignment exceeds that of a pointer. The change is expected to eventually make codegen more flexible at representing unions of values with both bits and pointer regions. Eventually we can also have someone improve the late-gc-lowering pass to take advantage of this increased information accuracy, but currently it will not be any better than before at laying out the frame. * Refactoring to be considered before adding MMTk * Removing jl_gc_notify_image_load, since it's a new function and not part of the refactoring * Moving gc_enable code to gc-common.c * Addressing PR comments * Push resolution of merge conflict * Removing jl_gc_mark_queue_obj_explicit extern definition from scheduler.c * Don't need the getter function since it's possible to use jl_small_typeof directly * WIP: Adding support for MMTk/Immix * Refactoring to be considered before adding MMTk * Adding fastpath allocation * Fixing removed newlines * Refactoring to be considered before adding MMTk * Adding a few comments; Moving some functions to be closer together * Fixing merge conflicts * Applying changes from refactoring before adding MMTk * Update TaskLocalRNG docstring according to #49110 (#55863) Since #49110, which is included in 1.10 and 1.11, spawning a task no longer advances the parent task's RNG state, so this statement in the docs was incorrect. * Root globals in toplevel exprs (#54433) This fixes #54422, the code here assumes that top level exprs are always rooted, but I don't see that referenced anywhere else, or guaranteed, so conservatively always root objects that show up in code. * codegen: fix alignment typos (#55880) So easy to type jl_datatype_align to get the natural alignment instead of julia_alignment to get the actual alignment. This should fix the Revise workload. Change is visible with ``` julia> code_llvm(Random.XoshiroSimd.forkRand, (Random.TaskLocalRNG, Base.Val{8})) ``` * Fix some corner cases of `isapprox` with unsigned integers (#55828) * 🤖 [master] Bump the Pkg stdlib from ef9f76c17 to 51d4910c1 (#55896) * Profile: fix order of fields in heapsnapshot & improve formatting (#55890) * Profile: Improve generation of clickable terminal links (#55857) * inference: add missing `TypeVar` handling for `instanceof_tfunc` (#55884) I thought these sort of problems had been addressed by d60f92c, but it seems some were missed. Specifically, `t.a` and `t.b` from `t::Union` could be `TypeVar`, and if they are passed to a subroutine or recursed without being unwrapped or rewrapped, errors like JuliaLang/julia#55882 could occur. This commit resolves the issue by calling `unwraptv` in the `Union` handling within `instanceof_tfunc`. I also found a similar issue inside `nfields_tfunc`, so that has also been fixed, and test cases have been added. While I haven't been able to make up a test case specifically for the fix in `instanceof_tfunc`, I have confirmed that this commit certainly fixes the issue reported in JuliaLang/julia#55882. - fixes JuliaLang/julia#55882 * Install terminfo data under /usr/share/julia (#55881) Just like all other libraries, we don't want internal Julia files to mess with system files. Introduced by https://github.com/JuliaLang/julia/pull/55411. * expose metric to report reasons why full GCs were triggered (#55826) Additional GC observability tool. This will help us to diagnose why some of our servers are triggering so many full GCs in certain circumstances. * Revert "Improve printing of several arguments" (#55894) Reverts JuliaLang/julia#55754 as it overrode some performance heuristics which appeared to be giving a significant gain/loss in performance: Closes https://github.com/JuliaLang/julia/issues/55893 * Do not trigger deprecation warnings in `Test.detect_ambiguities` and `Test.detect_unbound_args` (#55869) #55868 * do not intentionally suppress errors in precompile script from being reported or failing the result (#55909) I was slightly annoying that the build was set up to succeed if this step failed, so I removed the error suppression and fixed up the script slightly * Remove eigvecs method for SymTridiagonal (#55903) The fallback method does the same, so this specialized method isn't necessary * add --trim option for generating smaller binaries (#55047) This adds a command line option `--trim` that builds images where code is only included if it is statically reachable from methods marked using the new function `entrypoint`. Compile-time errors are given for call sites that are too dynamic to allow trimming the call graph (however there is an `unsafe` option if you want to try building anyway to see what happens). The PR has two other components. One is changes to Base that generally allow more code to be compiled in this mode. These changes will either be merged in separate PRs or moved to a separate part of the workflow (where we will build a custom system image for this purpose). The branch is set up this way to make it easy to check out and try the functionality. The other component is everything in the `juliac/` directory, which implements a compiler driver script based on this new option, along with some examples and tests. This will eventually become a package "app" that depends on PackageCompiler and provides a CLI for all of this stuff, so it will not be merged here. To try an example: ``` julia contrib/juliac.jl --output-exe hello --trim test/trimming/hello.jl ``` When stripped the resulting executable is currently about 900kb on my machine. Also includes a lot of work by @topolarity --------- Co-authored-by: Gabriel Baraldi <[email protected]> Co-authored-by: Tim Holy <[email protected]> Co-authored-by: Cody Tapscott <[email protected]> * fix rawbigints OOB issues (#55917) Fixes issues introduced in #50691 and found in #55906: * use `@inbounds` and `@boundscheck` macros in rawbigints, for catching OOB with `--check-bounds=yes` * fix OOB in `truncate` * prevent loading other extensions when precompiling an extension (#55589) The current way of loading extensions when precompiling an extension very easily leads to cycles. For example, if you have more than one extension and you happen to transitively depend on the triggers of one of your extensions you will immediately hit a cycle where the extensions will try to load each other indefinitely. This is an issue because you cannot directly influence your transitive dependency graph so from this p.o.v the current system of loading extension is "unsound". The test added here checks this scenario and we can now precompile and load it without any warnings or issues. Would have made https://github.com/JuliaLang/julia/issues/55517 a non issue. Fixes https://github.com/JuliaLang/julia/issues/55557 --------- Co-authored-by: KristofferC <[email protected]> * TOML: Avoid type-pirating `Base.TOML.Parser` (#55892) Since stdlibs can be duplicated but Base never is, `Base.require_stdlib` makes type piracy even more complicated than it normally would be. To adapt, this changes `TOML.Parser` to be a type defined by the TOML stdlib, so that we can define methods on it without committing type-piracy and avoid problems like Pkg.jl#4017 Resolves https://github.com/JuliaLang/Pkg.jl/issues/4017#issuecomment-2377589989 * [FileWatching] fix PollingFileWatcher design and add workaround for a stat bug What started as an innocent fix for a stat bug on Apple (#48667) turned into a full blown investigation into the design problems with the libuv backend for PollingFileWatcher, and writing my own implementation of it instead which could avoid those singled-threaded concurrency bugs. * [FileWatching] fix FileMonitor similarly and improve pidfile reliability Previously pidfile used the same poll_interval as sleep to detect if this code made any concurrency mistakes, but we do not really need to do that once FileMonitor is fixed to be reliable in the presence of parallel concurrency (instead of using watch_file). * [FileWatching] reorganize file and add docs * Add `--trace-dispatch` (#55848) * relocation: account for trailing path separator in depot paths (#55355) Fixes #55340 * change compiler to be stackless (#55575) This change ensures the compiler uses very little stack, making it compatible with running on any arbitrary system stack size and depths much more reliably. It also could be further modified now to easily add various forms of pause-able/resumable inference, since there is no implicit state on the stack--everything is local and explicit now. Whereas before, less than 900 frames would crash in less than a second: ``` $ time ./julia -e 'f(::Val{N}) where {N} = N <= 0 ? 0 : f(Val(N - 1)); f(Val(1000))' Warning: detected a stack overflow; program state may be corrupted, so further execution might be unreliable. Internal error: during type inference of f(Base.Val{1000}) Encountered stack overflow. This might be caused by recursion over very long tuples or argument lists. [23763] signal 6: Abort trap: 6 in expression starting at none:1 __pthread_kill at /usr/lib/system/libsystem_kernel.dylib (unknown line) Allocations: 1 (Pool: 1; Big: 0); GC: 0 Abort trap: 6 real 0m0.233s user 0m0.165s sys 0m0.049s ```` Now: it is effectively unlimited, as long as you are willing to wait for it: ``` $ time ./julia -e 'f(::Val{N}) where {N} = N <= 0 ? 0 : f(Val(N - 1)); f(Val(50000))' info: inference of f(Base.Val{50000}) from f(Base.Val{N}) where {N} exceeding 2500 frames (may be slow). info: inference of f(Base.Val{50000}) from f(Base.Val{N}) where {N} exceeding 5000 frames (may be slow). info: inference of f(Base.Val{50000}) from f(Base.Val{N}) where {N} exceeding 10000 frames (may be slow). info: inference of f(Base.Val{50000}) from f(Base.Val{N}) where {N} exceeding 20000 frames (may be slow). info: inference of f(Base.Val{50000}) from f(Base.Val{N}) where {N} exceeding 40000 frames (may be slow). real 7m4.988s $ time ./julia -e 'f(::Val{N}) where {N} = N <= 0 ? 0 : f(Val(N - 1)); f(Val(1000))' real 0m0.214s user 0m0.164s sys 0m0.044s $ time ./julia -e '@noinline f(::Val{N}) where {N} = N <= 0 ? GC.safepoint() : f(Val(N - 1)); f(Val(5000))' info: inference of f(Base.Val{5000}) from f(Base.Val{N}) where {N} exceeding 2500 frames (may be slow). info: inference of f(Base.Val{5000}) from f(Base.Val{N}) where {N} exceeding 5000 frames (may be slow). real 0m8.609s user 0m8.358s sys 0m0.240s ``` * optimizer: simplify the finalizer inlining pass a bit (#55934) Minor adjustments have been made to the algorithm of the finalizer inlining pass. Previously, it required that the finalizer registration dominate all uses, but this is not always necessary as far as the finalizer inlining point dominates all the uses. So the check has been relaxed. Other minor fixes have been made as well, but their importance is low. * Limit `@inbounds` to indexing in the dual-iterator branch in `copyto_unaliased!` (#55919) This simplifies the `copyto_unalised!` implementation where the source and destination have different `IndexStyle`s, and limits the `@inbounds` to only the indexing operation. In particular, the iteration over `eachindex(dest)` is not marked as `@inbounds` anymore. This seems to help with performance when the destination uses Cartesian indexing. Reduced implementation of the branch: ```julia function copyto_proposed!(dest, src) axes(dest) == axes(src) || throw(ArgumentError("incompatible sizes")) iterdest, itersrc = eachindex(dest), eachindex(src) for (destind, srcind) in zip(iterdest, itersrc) @inbounds dest[destind] = src[srcind] end dest end function copyto_current!(dest, src) axes(dest) == axes(src) || throw(ArgumentError("incompatible sizes")) iterdest, itersrc = eachindex(dest), eachindex(src) ret = iterate(iterdest) @inbounds for a in src idx, state = ret::NTuple{2,Any} dest[idx] = a ret = iterate(iterdest, state) end dest end function copyto_current_limitinbounds!(dest, src) axes(dest) == axes(src) || throw(ArgumentError("incompatible sizes")) iterdest, itersrc = eachindex(dest), eachindex(src) ret = iterate(iterdest) for isrc in itersrc idx, state = ret::NTuple{2,Any} @inbounds dest[idx] = src[isrc] ret = iterate(iterdest, state) end dest end ``` ```julia julia> a = zeros(40000,4000); b = rand(size(a)...); julia> av = view(a, UnitRange.(axes(a))...); julia> @btime copyto_current!($av, $b); 617.704 ms (0 allocations: 0 bytes) julia> @btime copyto_current_limitinbounds!($av, $b); 304.146 ms (0 allocations: 0 bytes) julia> @btime copyto_proposed!($av, $b); 240.217 ms (0 allocations: 0 bytes) julia> versioninfo() Julia Version 1.12.0-DEV.1260 Commit 4a4ca9c8152 (2024-09-28 01:49 UTC) Build Info: Official https://julialang.org release Platform Info: OS: Linux (x86_64-linux-gnu) CPU: 8 × Intel(R) Core(TM) i5-10310U CPU @ 1.70GHz WORD_SIZE: 64 LLVM: libLLVM-18.1.7 (ORCJIT, skylake) Threads: 1 default, 0 interactive, 1 GC (on 8 virtual cores) Environment: JULIA_EDITOR = subl ``` I'm not quite certain why the proposed implementation here (`copyto_proposed!`) is even faster than `copyto_current_limitinbounds!`. In any case, `copyto_proposed!` is easier to read, so I'm not complaining. This fixes https://github.com/JuliaLang/julia/issues/53158 * Strong zero in Diagonal triple multiplication (#55927) Currently, triple multiplication with a `LinearAlgebra.BandedMatrix` sandwiched between two `Diagonal`s isn't associative, as this is implemented using broadcasting, which doesn't assume a strong zero, whereas the two-term matrix multiplication does. ```julia julia> D = Diagonal(StepRangeLen(NaN, 0, 3)); julia> B = Bidiagonal(1:3, 1:2, :U); julia> D * B * D 3×3 Matrix{Float64}: NaN NaN NaN NaN NaN NaN NaN NaN NaN julia> (D * B) * D 3×3 Bidiagonal{Float64, Vector{Float64}}: NaN NaN ⋅ ⋅ NaN NaN ⋅ ⋅ NaN julia> D * (B * D) 3×3 Bidiagonal{Float64, Vector{Float64}}: NaN NaN ⋅ ⋅ NaN NaN ⋅ ⋅ NaN ``` This PR ensures that the 3-term multiplication is evaluated as a sequence of two-term multiplications, which fixes this issue. This also improves performance, as only the bands need to be evaluated now. ```julia julia> D = Diagonal(1:1000); B = Bidiagonal(1:1000, 1:999, :U); julia> @btime $D * $B * $D; 656.364 μs (11 allocations: 7.63 MiB) # v"1.12.0-DEV.1262" 2.483 μs (12 allocations: 31.50 KiB) # This PR ``` * Fix dispatch on `alg` in Float16 Hermitian eigen (#55928) Currently, ```julia julia> using LinearAlgebra julia> A = Hermitian(reshape(Float16[1:16;], 4, 4)); julia> eigen(A).values |> typeof Vector{Float16} (alias for Array{Float16, 1}) julia> eigen(A, LinearAlgebra.QRIteration()).values |> typeof Vector{Float32} (alias for Array{Float32, 1}) ``` This PR moves the specialization on the `eltype` to an internal method, so that firstly all `alg`s dispatch to that method, and secondly, there are no ambiguities introduce by specializing the top-level `eigen`. The latter currently causes test failures in `StaticArrays` (https://github.com/JuliaArrays/StaticArrays.jl/actions/runs/11092206012/job/30816955210?pr=1279), and should be fixed by this PR. * Remove specialized `ishermitian` method for `Diagonal{<:Real}` (#55948) The fallback method for `Diagonal{<:Number}` handles this already by checking that the `diag` is real, so we don't need this additional specialization. * Fix logic in `?` docstring example (#55945) * fix `unwrap_macrocalls` (#55950) The implementation of `unwrap_macrocalls` has assumed that what `:macrocall` wraps is always an `Expr` object, but that is not necessarily correct: ```julia julia> Base.@assume_effects :nothrow @show 42 ERROR: LoadError: TypeError: in typeassert, expected Expr, got a value of type Int64 Stacktrace: [1] unwrap_macrocalls(ex::Expr) @ Base ./expr.jl:906 [2] var"@assume_effects"(__source__::LineNumberNode, __module__::Module, args::Vararg{Any}) @ Base ./expr.jl:756 in expression starting at REPL[1]:1 ``` This commit addresses this issue. * make faster BigFloats (#55906) We can coalesce the two required allocations for the MFPR BigFloat API design into one allocation, hopefully giving a easy performance boost. It would have been slightly easier and more efficient if MPFR BigFloat was already a VLA instead of containing a pointer here, but that does not prevent the optimization. * Add propagate_inbounds_meta to atomic genericmemory ops (#55902) `memoryref(mem, i)` will otherwise emit a boundscheck. ``` ; │ @ /home/vchuravy/WorkstealingQueues/src/CLL.jl:53 within `setindex_atomic!` @ genericmemory.jl:329 ; │┌ @ boot.jl:545 within `memoryref` %ptls_field = getelementptr inbounds i8, ptr %tls_pgcstack, i64 16 %ptls_load = load ptr, ptr %ptls_field, align 8 %"box::GenericMemoryRef" = call noalias nonnull align 8 dereferenceable(32) ptr @ijl_gc_small_alloc(ptr %ptls_load, i32 552, i32 32, i64 23456076646928) #9 %"box::GenericMemoryRef.tag_addr" = getelementptr inbounds i64, ptr %"box::GenericMemoryRef", i64 -1 store atomic i64 23456076646928, ptr %"box::GenericMemoryRef.tag_addr" unordered, align 8 store ptr %memoryref_data, ptr %"box::GenericMemoryRef", align 8 %.repack8 = getelementptr inbounds { ptr, ptr }, ptr %"box::GenericMemoryRef", i64 0, i32 1 store ptr %memoryref_mem, ptr %.repack8, align 8 call void @ijl_bounds_error_int(ptr nonnull %"box::GenericMemoryRef", i64 %7) unreachable ``` For the Julia code: ```julia function Base.setindex_atomic!(buf::WSBuffer{T}, order::Symbol, val::T, idx::Int64) where T @inbounds Base.setindex_atomic!(buf.buffer, order, val,((idx - 1) & buf.mask) + 1) end ``` from https://github.com/gbaraldi/WorkstealingQueues.jl/blob/0ebc57237cf0c90feedf99e4338577d04b67805b/src/CLL.jl#L41 * fix rounding mode in construction of `BigFloat` from pi (#55911) The default argument of the method was outdated, reading the global default rounding directly, bypassing the `ScopedValue` stuff. * fix `nonsetable_type_hint_handler` (#55962) The current implementation is wrong, causing it to display inappropriate hints like the following: ```julia julia> s = Some("foo"); julia> s[] = "bar" ERROR: MethodError: no method matching setindex!(::Some{String}, ::String) The function `setindex!` exists, but no method is defined for this combination of argument types. You attempted to index the type String, rather than an instance of the type. Make sure you create the type using its constructor: d = String([...]) rather than d = String Stacktrace: [1] top-level scope @ REPL[2]:1 ``` * REPL: make UndefVarError aware of imported modules (#55932) * fix test/staged.jl (#55967) In particular, the implementation of `overdub_generator54341` was dangerous. This fixes it up. * Explicitly store a module's location (#55963) Revise wants to know what file a module's `module` definition is in. Currently it does this by looking at the source location for the implicitly generated `eval` method. This is terrible for two reasons: 1. The method may not exist if the module is a baremodule (which is not particularly common, which is probably why we haven't seen it). 2. The fact that the implicitly generated `eval` method has this location information is an implementation detail that I'd like to get rid of (#55949). This PR adds explicit file/line info to `Module`, so that Revise doesn't have to use the hack anymore. * mergewith: add single argument example to docstring (#55964) I ran into this edge case. I though it should be documented. --------- Co-authored-by: Lilith Orion Hafner <[email protected]> * [build] avoid libedit linkage and align libccalllazy* SONAMEs (#55968) While building the 1.11.0-rc4 in Homebrew[^1] in preparation for 1.11.0 release (and to confirm Sequoia successfully builds) I noticed some odd linkage for our Linux builds, which included of: 1. LLVM libraries were linking to `libedit.so`, e.g. ``` Dynamic Section: NEEDED libedit.so.0 NEEDED libz.so.1 NEEDED libzstd.so.1 NEEDED libstdc++.so.6 NEEDED libm.so.6 NEEDED libgcc_s.so.1 NEEDED libc.so.6 NEEDED ld-linux-x86-64.so.2 SONAME libLLVM-16jl.so ``` CMakeCache.txt showed ``` //Use libedit if available. LLVM_ENABLE_LIBEDIT:BOOL=ON ``` Which might be overriding `HAVE_LIBEDIT` at https://github.com/JuliaLang/llvm-project/blob/julia-release/16.x/llvm/cmake/config-ix.cmake#L222-L225. So just added `LLVM_ENABLE_LIBEDIT` 2. Wasn't sure if there was a reason for this but `libccalllazy*` had mismatched SONAME: ```console ❯ objdump -p lib/julia/libccalllazy* | rg '\.so' lib/julia/libccalllazybar.so: file format elf64-x86-64 NEEDED ccalllazyfoo.so SONAME ccalllazybar.so lib/julia/libccalllazyfoo.so: file format elf64-x86-64 SONAME ccalllazyfoo.so ``` Modifying this, but can drop if intentional. --- [^1]: https://github.com/Homebrew/homebrew-core/pull/192116 * Add missing `copy!(::AbstractMatrix, ::UniformScaling)` method (#55970) Hi everyone! First PR to Julia here. It was noticed in a Slack thread yesterday that `copy!(A, I)` doesn't work, but `copyto!(A, I)` does. This PR adds the missing method for `copy!(::AbstractMatrix, ::UniformScaling)`, which simply defers to `copyto!`, and corresponding tests. I added a `compat` notice for Julia 1.12. --------- Co-authored-by: Lilith Orion Hafner <[email protected]> * Add forward progress update to NEWS.md (#54089) Closes #40009 which was left open because of the needs news tag. --------- Co-authored-by: Ian Butterworth <[email protected]> * Fix an intermittent test failure in `core` test (#55973) The test wants to assert that `Module` is not resolved in `Main`, but other tests do resolve this identifier, so the test can fail depending on test order (and I've been seeing such failures on CI recently). Fix that by running the test in a fresh subprocess. * fix comma logic in time_print (#55977) Minor formatting fix * optimizer: fix up the inlining algorithm to use correct `nargs`/`isva` (#55976) It appears that inlining.jl was not updated in JuliaLang/julia#54341. Specifically, using `nargs`/`isva` from `mi.def::Method` in `ir_prepare_inlining!` causes the following error to occur: ```julia function generate_lambda_ex(world::UInt, source::LineNumberNode, argnames, spnames, @nospecialize body) stub = Core.GeneratedFunctionStub(identity, Core.svec(argnames...), Core.svec(spnames...)) return stub(world, source, body) end function overdubbee54341(a, b) return a + b end const overdubee_codeinfo54341 = code_lowered(overdubbee54341, Tuple{Any, Any})[1] function overdub_generator54341(world::UInt, source::LineNumberNode, selftype, fargtypes) if length(fargtypes) != 2 return generate_lambda_ex(world, source, (:overdub54341, :args), (), :(error("Wrong number of arguments"))) else return copy(overdubee_codeinfo54341) end end @eval function overdub54341(args...) $(Expr(:meta, :generated, overdub_generator54341)) $(Expr(:meta, :generated_only)) end topfunc(x) = overdub54341(x, 2) ``` ```julia julia> topfunc(1) Internal error: during type inference of topfunc(Int64) Encountered unexpected error in runtime: BoundsError(a=Array{Any, 1}(dims=(2,), mem=Memory{Any}(8, 0x10632e780)[SSAValue(2), SSAValue(3), #<null>, #<null>, #<null>, #<null>, #<null>, #<null>]), i=(3,)) throw_boundserror at ./essentials.jl:14 getindex at ./essentials.jl:909 [inlined] ssa_substitute_op! at ./compiler/ssair/inlining.jl:1798 ssa_substitute_op! at ./compiler/ssair/inlining.jl:1852 ir_inline_item! at ./compiler/ssair/inlining.jl:386 ... ``` This commit updates the abstract interpretation and inlining algorithm to use the `nargs`/`isva` values held by `CodeInfo`. Similar modifications have also been made to EscapeAnalysis.jl. @nanosoldier `runbenchmarks("inference", vs=":master")` * Add `.zed` directory to `.gitignore` (#55974) Similar to the `vscode` config directory, we may ignore the `zed` directory as well. * typeintersect: reduce unneeded allocations from `merge_env` `merge_env` and `final_merge_env` could be skipped for emptiness test or if we know there's only 1 valid Union state. * typeintersect: trunc env before nested `intersect_all` if valid. This only covers the simplest cases. We might want a full dependence analysis and keep env length minimum in the future. * `@time` actually fix time report commas & add tests (#55982) https://github.com/JuliaLang/julia/pull/55977 looked simple but wasn't quite right because of a bad pattern in the lock conflicts report section. So fix and add tests. * adjust EA to JuliaLang/julia#52527 (#55986) `Ent…

Fir kron ambiguity for triangular/hermitian matrices

eefc093

dkarrasch added the linear algebra Linear algebra label May 8, 2024

put back Number restriction

fd44170

fix typos

0df3800

add matrix of matrix tests

6c6dc07

araujoms mentioned this pull request Nov 26, 2024

eltype of Symmetric or Hermitian matrix of matrices is AbstractMatrix JuliaLang/LinearAlgebra.jl#1071

Open

dkarrasch merged commit 9ea4536 into master May 15, 2024
7 checks passed

dkarrasch deleted the dk/kronambig branch May 15, 2024 18:41

lazarusA pushed a commit to lazarusA/julia that referenced this pull request Jul 12, 2024

Fix kron ambiguity for triangular/hermitian matrices (JuliaLang#54413)

0a7a7a9

araujoms mentioned this pull request Aug 19, 2024

allow kronecker product between recursive triangular matrices #55527

Merged

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Fix `kron` ambiguity for triangular/hermitian matrices #54413

Fix `kron` ambiguity for triangular/hermitian matrices #54413

dkarrasch commented May 8, 2024

araujoms commented May 8, 2024 •

edited

Loading

dkarrasch commented May 9, 2024

araujoms commented May 9, 2024

dkarrasch commented May 10, 2024

araujoms commented May 10, 2024

dkarrasch commented May 10, 2024

dkarrasch commented May 14, 2024

araujoms commented May 14, 2024

araujoms commented May 14, 2024

Fix kron ambiguity for triangular/hermitian matrices #54413

Fix kron ambiguity for triangular/hermitian matrices #54413

Conversation

dkarrasch commented May 8, 2024

araujoms commented May 8, 2024 • edited Loading

dkarrasch commented May 9, 2024

araujoms commented May 9, 2024

dkarrasch commented May 10, 2024

araujoms commented May 10, 2024

dkarrasch commented May 10, 2024

dkarrasch commented May 14, 2024

araujoms commented May 14, 2024

araujoms commented May 14, 2024

Fix `kron` ambiguity for triangular/hermitian matrices #54413

Fix `kron` ambiguity for triangular/hermitian matrices #54413

araujoms commented May 8, 2024 •

edited

Loading