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StackOverflowError trying to throw OutOfGPUMemoryError, subsequent errors #2292

Closed
BioTurboNick opened this issue Mar 16, 2024 · 8 comments · Fixed by #2299
Closed

StackOverflowError trying to throw OutOfGPUMemoryError, subsequent errors #2292

BioTurboNick opened this issue Mar 16, 2024 · 8 comments · Fixed by #2299
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bug Something isn't working

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@BioTurboNick
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BioTurboNick commented Mar 16, 2024

Describe the bug

My neural network was training smoothly, but then I got a StackOverflowError. The stack trace suggests this was caused by OutOfGPUMemoryError being thrown.

I can't show the original stack trace, because when I went to check the CUDA version via Pkg, the screen started being flooded with more StackOverflowErrors unendingly with "Error while freeing DeviceBuffer(_____)", where the details of the buffer are different each time. The REPL is broken.

The subsequent errors have this form:

WARNING: Error while freeing DeviceBuffer(2.000 MiB at 0x0000000564c93e00):      
StackOverflowError()

Stacktrace:
     [1] prepare_cuda_state()
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\state.jl:94  
     [2] initialize_context()
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\libcuda.jl:18
     [3] macro expansion
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\libcuda.jl:167 [inlined]
     [4] (::CUDA.var"#7#8"{Base.RefValue{UInt64}, Base.RefValue{UInt64}})()      
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\utils\call.jl:27     
     [5] check(f::CUDA.var"#7#8"{Base.RefValue{UInt64}, Base.RefValue{UInt64}})  
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\libcuda.jl:32
     [6] cuMemGetInfo_v2(free::Base.RefValue{UInt64}, total::Base.RefValue{UInt64})
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\utils\call.jl:26     
     [7] info()
       @ CUDA.Mem C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\memory.jl:763
     [8] CUDA.MemoryInfo()
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:264
     [9] CUDA.OutOfGPUMemoryError(sz::Int64)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:338
    [10] CUDA.OutOfGPUMemoryError()
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:333
    [11] throw_api_error(res::CUDA.cudaError_enum)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\libcuda.jl:25
    [12] check(f::CUDA.var"#7#8"{Base.RefValue{UInt64}, Base.RefValue{UInt64}})  
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\libcuda.jl:34
--- the last 7 lines are repeated 3836 more times ---
 [26865] cuMemGetInfo_v2(free::Base.RefValue{UInt64}, total::Base.RefValue{UInt64})
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\utils\call.jl:26     
 [26866] info()
       @ CUDA.Mem C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\memory.jl:763
 [26867] CUDA.MemoryInfo()
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:264
 [26868] CUDA.OutOfGPUMemoryError(sz::Int64)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:338
 [26869] CUDA.OutOfGPUMemoryError()
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:333
 [26870] throw_api_error(res::CUDA.cudaError_enum)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\libcuda.jl:25
 [26871] check
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\libcuda.jl:34 [inlined]
 [26872] cuMemFreeAsync
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\utils\call.jl:26 [inlined]
 [26873] #free#2
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\memory.jl:97 [inlined]
 [26874] free
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\memory.jl:92 [inlined]
 [26875] #actual_free#998
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:78 [inlined]      
 [26876] actual_free
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:75 [inlined]      
 [26877] #_free#1023
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:516 [inlined]     
 [26878] _free
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:503 [inlined]     
 [26879] macro expansion
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:488 [inlined]     
 [26880] macro expansion
       @ .\timing.jl:395 [inlined]
 [26881] #free#1022
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:487 [inlined]     
 [26882] free
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:476 [inlined]     
 [26883] (::CUDA.var"#1029#1030"{CUDA.Mem.DeviceBuffer, Bool})()
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\array.jl:101
 [26884] #context!#912
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\state.jl:170 [inlined]
 [26885] context!
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\state.jl:165 [inlined]
 [26886] _free_buffer(buf::CUDA.Mem.DeviceBuffer, early::Bool)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\array.jl:89
 [26887] release(rc::GPUArrays.RefCounted{CUDA.Mem.DeviceBuffer}, args::Bool)    
       @ GPUArrays C:\Users\nicho\.julia\packages\GPUArrays\Hd5Sk\src\host\abstractarray.jl:42
 [26888] unsafe_free!
       @ C:\Users\nicho\.julia\packages\GPUArrays\Hd5Sk\src\host\abstractarray.jl:91 [inlined]
 [26889] unsafe_finalize!(xs::CUDA.CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})   
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\array.jl:113
 [26890] status(pkgs::Vector{Pkg.Types.PackageSpec})
       @ Pkg.API C:\Users\nicho\.julia\juliaup\julia-1.10.2+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Pkg\src\API.jl:148
 [26891] do_cmd!(command::Pkg.REPLMode.Command, repl::REPL.LineEditREPL)
       @ Pkg.REPLMode C:\Users\nicho\.julia\juliaup\julia-1.10.2+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Pkg\src\REPLMode\REPLMode.jl:412
 [26892] do_cmd(repl::REPL.LineEditREPL, input::String; do_rethrow::Bool)        
       @ Pkg.REPLMode C:\Users\nicho\.julia\juliaup\julia-1.10.2+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Pkg\src\REPLMode\REPLMode.jl:390
 [26893] do_cmd
       @ C:\Users\nicho\.julia\juliaup\julia-1.10.2+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Pkg\src\REPLMode\REPLMode.jl:380 [inlined]
 [26894] (::Pkg.REPLMode.var"#24#27"{REPL.LineEditREPL, REPL.LineEdit.Prompt})(s::REPL.LineEdit.MIState, buf::IOBuffer, ok::Bool)
       @ Pkg.REPLMode C:\Users\nicho\.julia\juliaup\julia-1.10.2+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Pkg\src\REPLMode\REPLMode.jl:557
 [26895] #invokelatest#2
       @ .\essentials.jl:892 [inlined]
 [26896] invokelatest
       @ .\essentials.jl:889 [inlined]
 [26897] run_interface(terminal::REPL.Terminals.TextTerminal, m::REPL.LineEdit.ModalInterface, s::REPL.LineEdit.MIState)
       @ REPL.LineEdit C:\Users\nicho\.julia\juliaup\julia-1.10.2+0.x64.w64.mingw32\share\julia\stdlib\v1.10\REPL\src\LineEdit.jl:2656
 [26898] run_frontend(repl::REPL.LineEditREPL, backend::REPL.REPLBackendRef)     
       @ REPL C:\Users\nicho\.julia\juliaup\julia-1.10.2+0.x64.w64.mingw32\share\julia\stdlib\v1.10\REPL\src\REPL.jl:1312

To reproduce

Not available.

Manifest.toml

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

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    AdaptStaticArraysExt = "StaticArrays"

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    [deps.BangBang.extensions]
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    BangBangDataFramesExt = "DataFrames"
    BangBangStaticArraysExt = "StaticArrays"
    BangBangStructArraysExt = "StructArrays"
    BangBangTypedTablesExt = "TypedTables"

    [deps.BangBang.weakdeps]
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[[deps.CUDA]]
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    [deps.CUDA.extensions]
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[[deps.CUDA_Driver_jll]]
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[[deps.ConstructionBase]]
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[[deps.DiffRules]]
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[[deps.Distances]]
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weakdeps = ["ChainRulesCore", "SparseArrays"]

    [deps.Distances.extensions]
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    DistancesSparseArraysExt = "SparseArrays"

[[deps.Distributed]]
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[[deps.DocStringExtensions]]
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Expected behavior

These errors should not be causing StackOverflowErrors, and the REPL should be usable.

Version info

Details on Julia:

Julia Version 1.10.2
Commit bd47eca2c8 (2024-03-01 10:14 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 32 × 13th Gen Intel(R) Core(TM) i9-13900KF
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, goldmont)
Threads: 1 default, 0 interactive, 1 GC (on 32 virtual cores)

Details on CUDA:

CUDA runtime 12.3, artifact installation
CUDA driver 12.3
NVIDIA driver 546.33.0

CUDA libraries:
- CUBLAS: 12.3.4
- CURAND: 10.3.4
- CUFFT: 11.0.12
- CUSOLVER: 11.5.4
- CUSPARSE: 12.2.0
- CUPTI: 21.0.0
- NVML: 12.0.0+546.33

Julia packages:
- CUDA: 5.2.0
- CUDA_Driver_jll: 0.7.0+1
- CUDA_Runtime_jll: 0.11.1+0

Toolchain:
- Julia: 1.10.2
- LLVM: 15.0.7

1 device:
  0: NVIDIA GeForce RTX 4080 (sm_89, 163.711 MiB / 15.992 GiB available)

Additional context

none

@BioTurboNick BioTurboNick added the bug Something isn't working label Mar 16, 2024
@BioTurboNick
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BioTurboNick commented Mar 16, 2024

Update: it was not unending, it just took a very, very long time to clear the buffer of all the errors. Then the REPL was fine.

Except a new StackOverflowError randomly appeared while the prompt was just sitting there.

Task Manager shows the GPU memory is full.

Unhandled Task ERROR: StackOverflowError:
Stacktrace:
     [1] throw_api_error(res::CUDA.cudaError_enum)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\libcuda.jl:25
     [2] check(f::CUDA.var"#7#8"{Base.RefValue{UInt64}, Base.RefValue{UInt64}})  
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\libcuda.jl:34
     [3] cuMemGetInfo_v2(free::Base.RefValue{UInt64}, total::Base.RefValue{UInt64})
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\utils\call.jl:26     
     [4] info()
       @ CUDA.Mem C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\memory.jl:763
     [5] CUDA.MemoryInfo()
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:264
     [6] CUDA.OutOfGPUMemoryError(sz::Int64)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:338
     [7] CUDA.OutOfGPUMemoryError()
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:333
--- the last 7 lines are repeated 3840 more times ---
 [26888] throw_api_error(res::CUDA.cudaError_enum)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\libcuda.jl:25
 [26889] isdone
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\stream.jl:111 [inlined]
 [26890] spinning_synchronization(f::typeof(CUDA.isdone), obj::CUDA.CuStream)    
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\synchronization.jl:79
 [26891] device_synchronize(; blocking::Bool, spin::Bool)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\synchronization.jl:171
 [26892] device_synchronize
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\synchronization.jl:169 [inlined]
 [26893] reclaim(sz::Int64)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:534
 [26894] reclaim
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:532 [inlined]     
 [26895] #1011
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:245 [inlined]     
 [26896] context!(f::CUDA.var"#1011#1012", ctx::CUDA.CuContext; skip_destroyed::Bool)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\state.jl:170 
 [26897] context!
       @ C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\state.jl:165 [inlined]
 [26898] device!(f::Function, dev::CUDA.CuDevice)
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\lib\cudadrv\state.jl:302 
 [26899] pool_cleanup()
       @ CUDA C:\Users\nicho\.julia\packages\CUDA\htRwP\src\pool.jl:244

@BioTurboNick BioTurboNick changed the title StackOverflowError trying to throw OutOfGPUMemoryError, REPL broken StackOverflowError trying to throw OutOfGPUMemoryError, subsequent errors Mar 16, 2024
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Related: Deliberately calling unsafe_free! on GPU arrays allocated during the training loop allowed me to avoid OOM. The GC for the GPU arrays doesn't seem to work right.

@maleadt
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maleadt commented Mar 19, 2024

The GC for the GPU arrays doesn't seem to work right.

The problem is just that the OOM handling itself triggers an OOM, I don't see how that would imply that the entire GPU GC handling is broken.

@BioTurboNick
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The GC for the GPU arrays doesn't seem to work right.

The problem is just that the OOM handling itself triggers an OOM, I don't see how that would imply that the entire GPU GC handling is broken.

The fact that I have to manually free GPU arrays to avoid OOM errors at all does, though. Separate issue, to be sure.

@maleadt
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maleadt commented Mar 19, 2024

The fact that I have to manually free GPU arrays to avoid OOM errors at all does, though.

Not necessarily; when encountering an OOM, we trigger GC to free up memory. If we first encounter a stack overflow, that doesn't happen.

@BioTurboNick
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Ohhh, okay, I understand. Thank you.

Is MemoryInfo() not supposed to allocate on the GPU and that changed, or is there usually just enough space for a small object in most OOM conditions?

@maleadt
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maleadt commented Mar 20, 2024

I didn't expect that the cuMemGetInfo during MemoryInfo actually breaks because of the OOM, which is annoying as it means we can't generate a useful report.

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maleadt commented Mar 21, 2024

Please test #2299

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