Segfault using Julia 1.11-alpha2 on AMD EPYC 9554 #68

jonas-schulze · 2024-03-28T18:09:11Z

Running

using BFloat16s # v0.5

A = ones(BFloat16, 10)
A + A

sometimes leads to a segfault, sometimes a stack overflow, and sometimes one CPU sits at 100% until ^Ced.
Nothing breaks on my Intel Core i5-12600K that does not support avx512_bf16.

               _
   _       _ _(_)_     |  Documentation: https://docs.julialang.org
  (_)     | (_) (_)    |
   _ _   _| |_  __ _   |  Type "?" for help, "]?" for Pkg help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 1.11.0-alpha2 (2024-03-18)
 _/ |\__'_|_|_|\__'_|  |  Official https://julialang.org/ release
|__/                   |

julia> include("../mwe.jl")
ERROR: LoadError: StackOverflowError:
in expression starting at /home/jschulze/tmp/julia-bfloat16/mwe.jl:4

julia> include("../mwe.jl")
ERROR: LoadError: StackOverflowError:
in expression starting at /home/jschulze/tmp/julia-bfloat16/mwe.jl:4

julia> include("../mwe.jl")
ERROR: LoadError: StackOverflowError:
in expression starting at /home/jschulze/tmp/julia-bfloat16/mwe.jl:4

julia> 
jschulze@hostname:~/tmp/julia-bfloat16/v0.5.0$ julia +1.11 ../mwe.jl 
ERROR: LoadError: StackOverflowError:
in expression starting at /home/jschulze/tmp/julia-bfloat16/mwe.jl:4
jschulze@hostname:~/tmp/julia-bfloat16/v0.5.0$ julia +1.11 ../mwe.jl 
Segmentation fault (core dumped)
jschulze@hostname:~/tmp/julia-bfloat16/v0.5.0$ julia +1.11 ../mwe.jl 
^C
[207628] signal 2: Interrupt
in expression starting at none:0
_ZN4llvm8ExpectedINS_8ArrayRefINS_6object12Elf_Sym_ImplINS2_7ELFTypeILNS_7support10endiannessE1ELb1EEEEEEEED2Ev at /home/jschulze/.julia/juliaup/julia-1.11.0-alpha2+0.x64.linux.gnu/bin/../lib/julia/libLLVM-16jl.so (unknown line)
_ZNK4llvm6object13ELFObjectFileINS0_7ELFTypeILNS_7support10endiannessE1ELb1EEEE14getSymbolFlagsENS0_11DataRefImplE at /home/jschulze/.julia/juliaup/julia-1.11.0-alpha2+0.x64.linux.gnu/bin/../lib/julia/libLLVM-16jl.so (unknown line)
_ZNK4llvm6object10ObjectFile14getSymbolValueENS0_11DataRefImplE at /home/jschulze/.julia/juliaup/julia-1.11.0-alpha2+0.x64.linux.gnu/bin/../lib/julia/libLLVM-16jl.so (unknown line)
_ZNK4llvm6object13ELFObjectFileINS0_7ELFTypeILNS_7support10endiannessE1ELb1EEEE16getSymbolAddressENS0_11DataRefImplE at /home/jschulze/.julia/juliaup/julia-1.11.0-alpha2+0.x64.linux.gnu/bin/../lib/julia/libLLVM-16jl.so (unknown line)
getAddress at /cache/build/builder-amdci4-1/julialang/julia-release-1-dot-11/usr/include/llvm/Object/ObjectFile.h:408 [inlined]
get_function_name_and_base at /cache/build/builder-amdci4-1/julialang/julia-release-1-dot-11/src/debuginfo.cpp:746 [inlined]
jl_dylib_DI_for_fptr at /cache/build/builder-amdci4-1/julialang/julia-release-1-dot-11/src/debuginfo.cpp:1142
jl_getDylibFunctionInfo at /cache/build/builder-amdci4-1/julialang/julia-release-1-dot-11/src/debuginfo.cpp:1174 [inlined]
jl_getFunctionInfo_impl at /cache/build/builder-amdci4-1/julialang/julia-release-1-dot-11/src/debuginfo.cpp:1247
ijl_lookup_code_address at /cache/build/builder-amdci4-1/julialang/julia-release-1-dot-11/src/stackwalk.c:589
lookup at ./stacktraces.jl:108
stacktrace at ./stacktraces.jl:164
stacktrace at ./stacktraces.jl:162 [inlined]
scrub_repl_backtrace at ./client.jl:96
jfptr_scrub_repl_backtrace_70894.1 at /home/jschulze/.julia/juliaup/julia-1.11.0-alpha2+0.x64.linux.gnu/lib/julia/sys.so (unknown line)
scrub_repl_backtrace at ./client.jl:103
exec_options at ./client.jl:321
_start at ./client.jl:526
jfptr__start_71122.1 at /home/jschulze/.julia/juliaup/julia-1.11.0-alpha2+0.x64.linux.gnu/lib/julia/sys.so (unknown line)
jl_apply at /cache/build/builder-amdci4-1/julialang/julia-release-1-dot-11/src/julia.h:2154 [inlined]
true_main at /cache/build/builder-amdci4-1/julialang/julia-release-1-dot-11/src/jlapi.c:900
jl_repl_entrypoint at /cache/build/builder-amdci4-1/julialang/julia-release-1-dot-11/src/jlapi.c:1059
main at /cache/build/builder-amdci4-1/julialang/julia-release-1-dot-11/cli/loader_exe.c:58
unknown function (ip: 0x7f3a5a5dbd8f)
__libc_start_main at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
unknown function (ip: 0x4010b8)
unknown function (ip: (nil))
Allocations: 1 (Pool: 1; Big: 0); GC: 0

Manifest-v1.11.toml

# This file is machine-generated - editing it directly is not advised

julia_version = "1.11.0-alpha2"
manifest_format = "2.0"
project_hash = "911edae1ed7fd2de4577c3badb415b11dc83b1e4"

[[deps.Artifacts]]
uuid = "56f22d72-fd6d-98f1-02f0-08ddc0907c33"
version = "1.11.0"

[[deps.BFloat16s]]
deps = ["LinearAlgebra", "Printf", "Random", "Test"]
git-tree-sha1 = "2c7cc21e8678eff479978a0a2ef5ce2f51b63dff"
uuid = "ab4f0b2a-ad5b-11e8-123f-65d77653426b"
version = "0.5.0"

[[deps.Base64]]
uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
version = "1.11.0"

[[deps.CompilerSupportLibraries_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "e66e0078-7015-5450-92f7-15fbd957f2ae"
version = "1.1.1+0"

[[deps.InteractiveUtils]]
deps = ["Markdown"]
uuid = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
version = "1.11.0"

[[deps.Libdl]]
uuid = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
version = "1.11.0"

[[deps.LinearAlgebra]]
deps = ["Libdl", "OpenBLAS_jll", "libblastrampoline_jll"]
uuid = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
version = "1.11.0"

[[deps.Logging]]
deps = ["StyledStrings"]
uuid = "56ddb016-857b-54e1-b83d-db4d58db5568"
version = "1.11.0"

[[deps.Markdown]]
deps = ["Base64"]
uuid = "d6f4376e-aef5-505a-96c1-9c027394607a"
version = "1.11.0"

[[deps.OpenBLAS_jll]]
deps = ["Artifacts", "CompilerSupportLibraries_jll", "Libdl"]
uuid = "4536629a-c528-5b80-bd46-f80d51c5b363"
version = "0.3.26+2"

[[deps.Printf]]
deps = ["Unicode"]
uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"
version = "1.11.0"

[[deps.Random]]
deps = ["SHA"]
uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
version = "1.11.0"

[[deps.SHA]]
uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
version = "0.7.0"

[[deps.Serialization]]
uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
version = "1.11.0"

[[deps.StyledStrings]]
uuid = "f489334b-da3d-4c2e-b8f0-e476e12c162b"
version = "1.11.0"

[[deps.Test]]
deps = ["InteractiveUtils", "Logging", "Random", "Serialization"]
uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
version = "1.11.0"

[[deps.Unicode]]
uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
version = "1.11.0"

[[deps.libblastrampoline_jll]]
deps = ["Artifacts", "Libdl"]
uuid = "8e850b90-86db-534c-a0d3-1478176c7d93"
version = "5.8.0+1"

The text was updated successfully, but these errors were encountered:

milankl · 2024-03-28T18:21:03Z

Nothing breaks on my Intel Core i5-12600K that does not support avx512_bf16.

BFloat16 is for arithmetic operations converted to Float32 and then the result is truncated back down to BFloat16 (but I'm not sure when/how BFloat16 arithmetic is used if natively available). You can check this with

julia> a = one(BFloat16)
BFloat16(1.0)

julia> @code_lowered a+a
CodeInfo(
1 ─ %1 = BFloat16s.Float32(x)
│   %2 = BFloat16s.Float32(y)
│   %3 = %1 + %2
│   %4 = BFloat16s.BFloat16(%3)
└──      return %4
)

I also have an Intel i5 on my macbook and with Julia 1.10.2 I cannot reproduce your error, even if I execute this a million times

julia> using BFloat16s
julia> A = ones(BFloat16,10)
julia> for _ in 1:1000000
           A + A
       end

julia>

Are you sure that .../mwe.jl really only contains these lines of code that you copied in?

jonas-schulze · 2024-03-28T18:36:20Z

Are you sure that .../mwe.jl really only contains these lines of code that you copied in?

Yes, I am. I was also testing v0.4.2, hence the v0.5.0/ to separate the environments and the ../ to the common mwe.jl.

BFloat16 is for arithmetic operations converted to Float32 [...]

Starting with Julia 1.11 (JuliaLang/julia@5487046) and BFloat16s 0.5 (#51), native LLVM bfloat is used if available. On the AMD CPU, I see the following.

julia> BFloat16s.llvm_storage
true

julia> BFloat16s.llvm_arithmetic
true

julia> a = one(BFloat16)
BFloat16(1.0)

julia> @code_lowered a+a
CodeInfo(
1 ─ %1 = Base.add_float
│   %2 = (%1)(x, y)
└──      return %2
)

milankl · 2024-03-28T18:48:03Z

But what happens if you look at the LLVM code? Because for me the same conversion happens there (wtih 1.11) but you're hoping it would call fadd bfloat directly?

julia> @code_llvm a+a
; Function Signature: +(Core.BFloat16, Core.BFloat16)
;  @ /Users/milan/.julia/packages/BFloat16s/u3WQc/src/bfloat16.jl:225 within `+`
define bfloat @"julia_+_5925"(bfloat %"x::BFloat16", bfloat %"y::BFloat16") #0 {
top:
  %0 = fpext bfloat %"x::BFloat16" to float
  %1 = fpext bfloat %"y::BFloat16" to float
  %2 = fadd float %0, %1
  %3 = fptrunc float %2 to bfloat
  ret bfloat %3
}

jonas-schulze · 2024-04-02T09:21:24Z

Yes, I was hoping for fadd bfloat, but I see the same IR you posted ... 🤔
Do I need to compile julia with a custom LLVM that has BF16 enabled ... somehow?

Interestingly, I can't even generate the LLVM IR for A + A from the original MWE:

julia> A = ones(Core.BFloat16, 32);

julia> @code_llvm 2A
ERROR: StackOverflowError:

julia> @code_llvm A + A
ERROR: StackOverflowError:

julia> @code_llvm BFloat16(1) * A
ERROR: StackOverflowError:

Sometimes I even get one core sitting at 100% load just generating the LLVM IR. I am a bit clueless here.

jonas-schulze · 2024-05-30T12:37:47Z

The problem persists on the current nightly, Version 1.12.0-DEV.629 (2024-05-30).

jonas-schulze mentioned this issue Apr 10, 2024

Native BFloat16 support not working on AMD EPYC 9554 JuliaLang/julia#54025

Open

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Segfault using Julia 1.11-alpha2 on AMD EPYC 9554 #68

Segfault using Julia 1.11-alpha2 on AMD EPYC 9554 #68

jonas-schulze commented Mar 28, 2024

milankl commented Mar 28, 2024 •

edited

Loading

jonas-schulze commented Mar 28, 2024 •

edited

Loading

milankl commented Mar 28, 2024 •

edited

Loading

jonas-schulze commented Apr 2, 2024

jonas-schulze commented May 30, 2024

Segfault using Julia 1.11-alpha2 on AMD EPYC 9554 #68

Segfault using Julia 1.11-alpha2 on AMD EPYC 9554 #68

Comments

jonas-schulze commented Mar 28, 2024

milankl commented Mar 28, 2024 • edited Loading

jonas-schulze commented Mar 28, 2024 • edited Loading

milankl commented Mar 28, 2024 • edited Loading

jonas-schulze commented Apr 2, 2024

jonas-schulze commented May 30, 2024

milankl commented Mar 28, 2024 •

edited

Loading

jonas-schulze commented Mar 28, 2024 •

edited

Loading

milankl commented Mar 28, 2024 •

edited

Loading