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CUDA programming in Julia.
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Julia keeps allocations alive in presence of try/catch #2197

Open IanButterworth opened 11 months ago

IanButterworth commented 11 months ago

Describe the bug

I have a case where the inclusion of a try-catch in a for loop is causing CUDA OOM.

Rather nastily the try-catch was actually introduced by a @info "epoch $epoch_num" log, which wraps the evaluation of the log message in a try-catch because of the interpolation. The issue doesn't happen for @info "epoch"

https://github.com/IanButterworth/julia/blob/61a36549f961eacd74d431f5e987f3e7f789c643/base/logging.jl#L344-L380

To reproduce

The Minimal Working Example (MWE) for this bug:

Instantiate https://github.com/IanButterworth/EfficientNet-Training/tree/main

This is with CUDA.jl dev-ed and logging added as suggested by @maleadt 

julia> include("effnet_train.jl")

julia> @time train(limit=3, gpu_gc=false, gpu_stats=true)
[ Info: loading CIFAR-10 dataset
[ Info: loading EfficientNetv2 model
[ Info: starting training
Effective GPU memory usage: 99.55% (11.688 GiB/11.741 GiB)
Memory pool usage: 8.505 GiB (10.406 GiB reserved)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 8.292 GiB)
Effective GPU memory usage: 99.55% (11.688 GiB/11.741 GiB)
Memory pool usage: 8.492 GiB (10.406 GiB reserved)
training epoch 1/45   4%|███▊                                                                                           |  ETA: 0:00:09WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 8.279 GiB)
Effective GPU memory usage: 99.55% (11.688 GiB/11.741 GiB)
Memory pool usage: 8.492 GiB (10.406 GiB reserved)
training epoch 1/45   6%|█████▊                                                                                         |  ETA: 0:00:09WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 8.279 GiB)
Effective GPU memory usage: 99.54% (11.687 GiB/11.741 GiB)
Memory pool usage: 8.492 GiB (10.406 GiB reserved)
training epoch 1/45 100%|███████████████████████████████████████████████████████████████████████████████████████████████| Time: 0:00:00
[ Info: epoch 1 complete. Testing...
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 9.974 GiB)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 9.917 GiB)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 9.818 GiB)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 9.834 GiB)
[ Info: (train_loss = 2.303f0, train_acc = 0.1, test_loss = 2.303f0, test_acc = 0.099)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 5.953 GiB)
Effective GPU memory usage: 99.54% (11.687 GiB/11.741 GiB)
Memory pool usage: 6.301 GiB (10.406 GiB reserved)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 5.875 GiB)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 3.002 GiB)
Effective GPU memory usage: 99.54% (11.687 GiB/11.741 GiB)
Memory pool usage: 5.703 GiB (10.406 GiB reserved)
training epoch 2/45   4%|███▊                                                                                           |  ETA: 0:00:09WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 5.240 GiB)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 1.578 GiB)
WARNING: CUDA memory allocation failed; attempting to free up memory...
... waiting for pending frees (freed 0 bytes)
... waiting for all pending frees (freed 0 bytes)
... running a quick GC (freed 167.542 MiB)
... running a full GC (freed 11.719 MiB)
... releasing reserved memory (freed 0 bytes)

┌ Error: Out of GPU memory trying to allocate 128.000 MiB
│ Effective GPU memory usage: 99.54% (11.687 GiB/11.741 GiB)
│ Memory pool usage: 4.157 GiB (10.406 GiB reserved)
└ @ Main ~/Documents/GitHub/EfficientNet-Training/effnet_train.jl:104
  3.465019 seconds (2.09 M allocations: 1.532 GiB, 27.75% gc time)

The inner loop can be simplified to this reproducer

for epoch in 1:epochs
    for (x, y) in train_loader
        x = x |> device; y = y |> device
        gs, _ = gradient(model, x) do m, _x
            logitcrossentropy(m(_x), y)
        end
        # state, model = Optimisers.update(state, model, gs)
        model = Flux.Functors.fmap(copy, model; exclude = Optimisers.maywrite)
        state = Flux.Functors.fmap(copy, state; exclude = Optimisers.maywrite)
        @show CUDA.MemoryInfo().pool_used_bytes
    end
    try
        true
    catch
    end
end

Commenting out the try-catch (or the 2 loop @info logs in the original code), or will avoid the OOM entirely.

Manifest.toml

``` # This file is machine-generated - editing it directly is not advised julia_version = "1.9.4" manifest_format = "2.0" project_hash = "4bc608d3c54e7666344bf4c7441aba4973b01068" [[deps.AbstractFFTs]] deps = ["LinearAlgebra"] git-tree-sha1 = "d92ad398961a3ed262d8bf04a1a2b8340f915fef" uuid = "621f4979-c628-5d54-868e-fcf4e3e8185c" version = "1.5.0" weakdeps = ["ChainRulesCore", "Test"] [deps.AbstractFFTs.extensions] AbstractFFTsChainRulesCoreExt = "ChainRulesCore" AbstractFFTsTestExt = "Test" [[deps.Adapt]] deps = ["LinearAlgebra", "Requires"] git-tree-sha1 = "02f731463748db57cc2ebfbd9fbc9ce8280d3433" uuid = "79e6a3ab-5dfb-504d-930d-738a2a938a0e" version = "3.7.1" weakdeps = ["StaticArrays"] [deps.Adapt.extensions] AdaptStaticArraysExt = "StaticArrays" [[deps.ArgCheck]] git-tree-sha1 = "a3a402a35a2f7e0b87828ccabbd5ebfbebe356b4" uuid = "dce04be8-c92d-5529-be00-80e4d2c0e197" version = "2.3.0" [[deps.ArgTools]] uuid = "0dad84c5-d112-42e6-8d28-ef12dabb789f" version = "1.1.1" [[deps.Artifacts]] uuid = "56f22d72-fd6d-98f1-02f0-08ddc0907c33" [[deps.Atomix]] deps = ["UnsafeAtomics"] git-tree-sha1 = "c06a868224ecba914baa6942988e2f2aade419be" uuid = "a9b6321e-bd34-4604-b9c9-b65b8de01458" version = "0.1.0" [[deps.AtomsBase]] deps = ["LinearAlgebra", "PeriodicTable", "Printf", "Requires", "StaticArrays", "Unitful", "UnitfulAtomic"] git-tree-sha1 = "995c2b6b17840cd87b722ce9c6cdd72f47bab545" uuid = "a963bdd2-2df7-4f54-a1ee-49d51e6be12a" version = "0.3.5" [[deps.BFloat16s]] deps = ["LinearAlgebra", "Printf", "Random", "Test"] git-tree-sha1 = "dbf84058d0a8cbbadee18d25cf606934b22d7c66" uuid = "ab4f0b2a-ad5b-11e8-123f-65d77653426b" version = "0.4.2" [[deps.BSON]] git-tree-sha1 = "2208958832d6e1b59e49f53697483a84ca8d664e" uuid = "fbb218c0-5317-5bc6-957e-2ee96dd4b1f0" version = "0.3.7" [[deps.BangBang]] deps = ["Compat", "ConstructionBase", "InitialValues", "LinearAlgebra", "Requires", "Setfield", "Tables"] git-tree-sha1 = "e28912ce94077686443433c2800104b061a827ed" uuid = "198e06fe-97b7-11e9-32a5-e1d131e6ad66" version = "0.3.39" [deps.BangBang.extensions] BangBangChainRulesCoreExt = "ChainRulesCore" BangBangDataFramesExt = "DataFrames" BangBangStaticArraysExt = "StaticArrays" BangBangStructArraysExt = "StructArrays" BangBangTypedTablesExt = "TypedTables" [deps.BangBang.weakdeps] ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4" DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" StaticArrays = "90137ffa-7385-5640-81b9-e52037218182" StructArrays = "09ab397b-f2b6-538f-b94a-2f83cf4a842a" TypedTables = "9d95f2ec-7b3d-5a63-8d20-e2491e220bb9" [[deps.Base64]] uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f" [[deps.Baselet]] git-tree-sha1 = "aebf55e6d7795e02ca500a689d326ac979aaf89e" uuid = "9718e550-a3fa-408a-8086-8db961cd8217" version = "0.1.1" [[deps.BitFlags]] git-tree-sha1 = "2dc09997850d68179b69dafb58ae806167a32b1b" uuid = "d1d4a3ce-64b1-5f1a-9ba4-7e7e69966f35" version = "0.1.8" [[deps.BufferedStreams]] git-tree-sha1 = "4ae47f9a4b1dc19897d3743ff13685925c5202ec" uuid = "e1450e63-4bb3-523b-b2a4-4ffa8c0fd77d" version = "1.2.1" [[deps.CEnum]] git-tree-sha1 = "eb4cb44a499229b3b8426dcfb5dd85333951ff90" uuid = "fa961155-64e5-5f13-b03f-caf6b980ea82" version = "0.4.2" [[deps.CSV]] deps = ["CodecZlib", "Dates", "FilePathsBase", "InlineStrings", "Mmap", "Parsers", "PooledArrays", "PrecompileTools", "SentinelArrays", "Tables", "Unicode", "WeakRefStrings", "WorkerUtilities"] git-tree-sha1 = "44dbf560808d49041989b8a96cae4cffbeb7966a" uuid = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b" version = "0.10.11" [[deps.CUDA]] deps = ["AbstractFFTs", "Adapt", "BFloat16s", "CEnum", "CUDA_Driver_jll", "CUDA_Runtime_Discovery", "CUDA_Runtime_jll", "Crayons", "DataFrames", "ExprTools", "GPUArrays", "GPUCompiler", "KernelAbstractions", "LLVM", "LLVMLoopInfo", "LazyArtifacts", "Libdl", "LinearAlgebra", "Logging", "NVTX", "Preferences", "PrettyTables", "Printf", "Random", "Random123", "RandomNumbers", "Reexport", "Requires", "SparseArrays", "Statistics", "UnsafeAtomicsLLVM"] git-tree-sha1 = "76582ae19006b1186e87dadd781747f76cead72c" uuid = "052768ef-5323-5732-b1bb-66c8b64840ba" version = "5.1.1" weakdeps = ["ChainRulesCore", "SpecialFunctions"] [deps.CUDA.extensions] ChainRulesCoreExt = "ChainRulesCore" SpecialFunctionsExt = "SpecialFunctions" [[deps.CUDA_Driver_jll]] deps = ["Artifacts", "JLLWrappers", "LazyArtifacts", "Libdl", "Pkg"] git-tree-sha1 = "1e42ef1bdb45487ff28de16182c0df4920181dc3" uuid = "4ee394cb-3365-5eb0-8335-949819d2adfc" version = "0.7.0+0" [[deps.CUDA_Runtime_Discovery]] deps = ["Libdl"] git-tree-sha1 = "bcc4a23cbbd99c8535a5318455dcf0f2546ec536" uuid = "1af6417a-86b4-443c-805f-a4643ffb695f" version = "0.2.2" [[deps.CUDA_Runtime_jll]] deps = ["Artifacts", "CUDA_Driver_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "TOML"] git-tree-sha1 = "9704e50c9158cf8896c2776b8dbc5edd136caf80" uuid = "76a88914-d11a-5bdc-97e0-2f5a05c973a2" version = "0.10.1+0" [[deps.CUDNN_jll]] deps = ["Artifacts", "CUDA_Runtime_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "TOML"] git-tree-sha1 = "75923dce4275ead3799b238e10178a68c07dbd3b" uuid = "62b44479-cb7b-5706-934f-f13b2eb2e645" version = "8.9.4+0" [[deps.ChainRules]] deps = ["Adapt", "ChainRulesCore", "Compat", "Distributed", "GPUArraysCore", "IrrationalConstants", "LinearAlgebra", "Random", "RealDot", "SparseArrays", "SparseInverseSubset", "Statistics", "StructArrays", "SuiteSparse"] git-tree-sha1 = "006cc7170be3e0fa02ccac6d4164a1eee1fc8c27" uuid = "082447d4-558c-5d27-93f4-14fc19e9eca2" version = "1.58.0" [[deps.ChainRulesCore]] deps = ["Compat", "LinearAlgebra"] git-tree-sha1 = "e0af648f0692ec1691b5d094b8724ba1346281cf" uuid = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4" version = "1.18.0" weakdeps = ["SparseArrays"] [deps.ChainRulesCore.extensions] ChainRulesCoreSparseArraysExt = "SparseArrays" [[deps.Chemfiles]] deps = ["AtomsBase", "Chemfiles_jll", "DocStringExtensions", "PeriodicTable", "Unitful", "UnitfulAtomic"] git-tree-sha1 = "82fe5e341c793cb51149d993307da9543824b206" uuid = "46823bd8-5fb3-5f92-9aa0-96921f3dd015" version = "0.10.41" [[deps.Chemfiles_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] git-tree-sha1 = "f3743181e30d87c23d9c8ebd493b77f43d8f1890" uuid = "78a364fa-1a3c-552a-b4bb-8fa0f9c1fcca" version = "0.10.4+0" [[deps.CodecZlib]] deps = ["TranscodingStreams", "Zlib_jll"] git-tree-sha1 = "cd67fc487743b2f0fd4380d4cbd3a24660d0eec8" uuid = "944b1d66-785c-5afd-91f1-9de20f533193" version = "0.7.3" [[deps.ColorSchemes]] deps = ["ColorTypes", "ColorVectorSpace", "Colors", "FixedPointNumbers", "PrecompileTools", "Random"] git-tree-sha1 = "67c1f244b991cad9b0aa4b7540fb758c2488b129" uuid = "35d6a980-a343-548e-a6ea-1d62b119f2f4" version = "3.24.0" [[deps.ColorTypes]] deps = ["FixedPointNumbers", "Random"] git-tree-sha1 = "eb7f0f8307f71fac7c606984ea5fb2817275d6e4" uuid = "3da002f7-5984-5a60-b8a6-cbb66c0b333f" version = "0.11.4" [[deps.ColorVectorSpace]] deps = ["ColorTypes", "FixedPointNumbers", "LinearAlgebra", "Requires", "Statistics", "TensorCore"] git-tree-sha1 = "a1f44953f2382ebb937d60dafbe2deea4bd23249" uuid = "c3611d14-8923-5661-9e6a-0046d554d3a4" version = "0.10.0" weakdeps = ["SpecialFunctions"] [deps.ColorVectorSpace.extensions] SpecialFunctionsExt = "SpecialFunctions" [[deps.Colors]] deps = ["ColorTypes", "FixedPointNumbers", "Reexport"] git-tree-sha1 = "fc08e5930ee9a4e03f84bfb5211cb54e7769758a" uuid = "5ae59095-9a9b-59fe-a467-6f913c188581" version = "0.12.10" [[deps.CommonSubexpressions]] deps = ["MacroTools", "Test"] git-tree-sha1 = "7b8a93dba8af7e3b42fecabf646260105ac373f7" uuid = "bbf7d656-a473-5ed7-a52c-81e309532950" version = "0.3.0" [[deps.Compat]] deps = ["UUIDs"] git-tree-sha1 = "886826d76ea9e72b35fcd000e535588f7b60f21d" uuid = "34da2185-b29b-5c13-b0c7-acf172513d20" version = "4.10.1" weakdeps = ["Dates", "LinearAlgebra"] [deps.Compat.extensions] CompatLinearAlgebraExt = "LinearAlgebra" [[deps.CompilerSupportLibraries_jll]] deps = ["Artifacts", "Libdl"] uuid = "e66e0078-7015-5450-92f7-15fbd957f2ae" version = "1.0.5+0" [[deps.CompositionsBase]] git-tree-sha1 = "802bb88cd69dfd1509f6670416bd4434015693ad" uuid = "a33af91c-f02d-484b-be07-31d278c5ca2b" version = "0.1.2" [deps.CompositionsBase.extensions] CompositionsBaseInverseFunctionsExt = "InverseFunctions" [deps.CompositionsBase.weakdeps] InverseFunctions = "3587e190-3f89-42d0-90ee-14403ec27112" [[deps.ConcurrentUtilities]] deps = ["Serialization", "Sockets"] git-tree-sha1 = "8cfa272e8bdedfa88b6aefbbca7c19f1befac519" uuid = "f0e56b4a-5159-44fe-b623-3e5288b988bb" version = "2.3.0" [[deps.ConstructionBase]] deps = ["LinearAlgebra"] git-tree-sha1 = "c53fc348ca4d40d7b371e71fd52251839080cbc9" uuid = "187b0558-2788-49d3-abe0-74a17ed4e7c9" version = "1.5.4" [deps.ConstructionBase.extensions] ConstructionBaseIntervalSetsExt = "IntervalSets" ConstructionBaseStaticArraysExt = "StaticArrays" [deps.ConstructionBase.weakdeps] IntervalSets = "8197267c-284f-5f27-9208-e0e47529a953" StaticArrays = "90137ffa-7385-5640-81b9-e52037218182" [[deps.ContextVariablesX]] deps = ["Compat", "Logging", "UUIDs"] git-tree-sha1 = "25cc3803f1030ab855e383129dcd3dc294e322cc" uuid = "6add18c4-b38d-439d-96f6-d6bc489c04c5" version = "0.1.3" [[deps.Contour]] git-tree-sha1 = "d05d9e7b7aedff4e5b51a029dced05cfb6125781" uuid = "d38c429a-6771-53c6-b99e-75d170b6e991" version = "0.6.2" [[deps.Crayons]] git-tree-sha1 = "249fe38abf76d48563e2f4556bebd215aa317e15" uuid = "a8cc5b0e-0ffa-5ad4-8c14-923d3ee1735f" version = "4.1.1" [[deps.DataAPI]] git-tree-sha1 = "8da84edb865b0b5b0100c0666a9bc9a0b71c553c" uuid = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a" version = "1.15.0" [[deps.DataDeps]] deps = ["HTTP", "Libdl", "Reexport", "SHA", "p7zip_jll"] git-tree-sha1 = "6e8d74545d34528c30ccd3fa0f3c00f8ed49584c" uuid = "124859b0-ceae-595e-8997-d05f6a7a8dfe" version = "0.7.11" [[deps.DataFrames]] deps = ["Compat", "DataAPI", "DataStructures", "Future", "InlineStrings", "InvertedIndices", "IteratorInterfaceExtensions", 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FreeType = "b38be410-82b0-50bf-ab77-7b57e271db43" ImageInTerminal = "d8c32880-2388-543b-8c61-d9f865259254" IntervalSets = "8197267c-284f-5f27-9208-e0e47529a953" Term = "22787eb5-b846-44ae-b979-8e399b8463ab" Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d" [[deps.Unitful]] deps = ["Dates", "LinearAlgebra", "Random"] git-tree-sha1 = "3c793be6df9dd77a0cf49d80984ef9ff996948fa" uuid = "1986cc42-f94f-5a68-af5c-568840ba703d" version = "1.19.0" [deps.Unitful.extensions] ConstructionBaseUnitfulExt = "ConstructionBase" InverseFunctionsUnitfulExt = "InverseFunctions" [deps.Unitful.weakdeps] ConstructionBase = "187b0558-2788-49d3-abe0-74a17ed4e7c9" InverseFunctions = "3587e190-3f89-42d0-90ee-14403ec27112" [[deps.UnitfulAtomic]] deps = ["Unitful"] git-tree-sha1 = "903be579194534af1c4b4778d1ace676ca042238" uuid = "a7773ee8-282e-5fa2-be4e-bd808c38a91a" version = "1.0.0" [[deps.UnsafeAtomics]] git-tree-sha1 = "6331ac3440856ea1988316b46045303bef658278" uuid = "013be700-e6cd-48c3-b4a1-df204f14c38f" version = "0.2.1" [[deps.UnsafeAtomicsLLVM]] deps = ["LLVM", "UnsafeAtomics"] git-tree-sha1 = "323e3d0acf5e78a56dfae7bd8928c989b4f3083e" uuid = "d80eeb9a-aca5-4d75-85e5-170c8b632249" version = "0.1.3" [[deps.WeakRefStrings]] deps = ["DataAPI", "InlineStrings", "Parsers"] git-tree-sha1 = "b1be2855ed9ed8eac54e5caff2afcdb442d52c23" uuid = "ea10d353-3f73-51f8-a26c-33c1cb351aa5" version = "1.4.2" [[deps.WorkerUtilities]] git-tree-sha1 = "cd1659ba0d57b71a464a29e64dbc67cfe83d54e7" uuid = "76eceee3-57b5-4d4a-8e66-0e911cebbf60" version = "1.6.1" [[deps.ZipFile]] deps = ["Libdl", "Printf", "Zlib_jll"] git-tree-sha1 = "f492b7fe1698e623024e873244f10d89c95c340a" uuid = "a5390f91-8eb1-5f08-bee0-b1d1ffed6cea" version = "0.10.1" [[deps.Zlib_jll]] deps = ["Libdl"] uuid = "83775a58-1f1d-513f-b197-d71354ab007a" version = "1.2.13+0" [[deps.Zygote]] deps = ["AbstractFFTs", "ChainRules", "ChainRulesCore", "DiffRules", "Distributed", "FillArrays", "ForwardDiff", "GPUArrays", "GPUArraysCore", "IRTools", "InteractiveUtils", "LinearAlgebra", "LogExpFunctions", "MacroTools", "NaNMath", "PrecompileTools", "Random", "Requires", "SparseArrays", "SpecialFunctions", "Statistics", "ZygoteRules"] git-tree-sha1 = "5ded212acd815612df112bb895ef3910c5a03f57" uuid = "e88e6eb3-aa80-5325-afca-941959d7151f" version = "0.6.67" [deps.Zygote.extensions] ZygoteColorsExt = "Colors" ZygoteDistancesExt = "Distances" ZygoteTrackerExt = "Tracker" [deps.Zygote.weakdeps] Colors = "5ae59095-9a9b-59fe-a467-6f913c188581" Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7" Tracker = "9f7883ad-71c0-57eb-9f7f-b5c9e6d3789c" [[deps.ZygoteRules]] deps = ["ChainRulesCore", "MacroTools"] git-tree-sha1 = "9d749cd449fb448aeca4feee9a2f4186dbb5d184" uuid = "700de1a5-db45-46bc-99cf-38207098b444" version = "0.2.4" [[deps.cuDNN]] deps = ["CEnum", "CUDA", "CUDA_Runtime_Discovery", "CUDNN_jll"] git-tree-sha1 = "c092c26591a851083ed3358890d0d916c58dde62" uuid = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd" version = "1.2.1" [[deps.libaec_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] git-tree-sha1 = "eddd19a8dea6b139ea97bdc8a0e2667d4b661720" uuid = "477f73a3-ac25-53e9-8cc3-50b2fa2566f0" version = "1.0.6+1" [[deps.libblastrampoline_jll]] deps = ["Artifacts", "Libdl"] uuid = "8e850b90-86db-534c-a0d3-1478176c7d93" version = "5.8.0+0" [[deps.libevent_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "OpenSSL_jll"] git-tree-sha1 = "f04ec6d9a186115fb38f858f05c0c4e1b7fc9dcb" uuid = "1080aeaf-3a6a-583e-a51c-c537b09f60ec" version = "2.1.13+1" [[deps.nghttp2_jll]] deps = ["Artifacts", "Libdl"] uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d" version = "1.52.0+1" [[deps.p7zip_jll]] deps = ["Artifacts", "Libdl"] uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0" version = "17.4.0+0" [[deps.prrte_jll]] deps = ["Artifacts", "Hwloc_jll", "JLLWrappers", "Libdl", "PMIx_jll", "libevent_jll"] git-tree-sha1 = "5adb2d7a18a30280feb66cad6f1a1dfdca2dc7b0" uuid = "eb928a42-fffd-568d-ab9c-3f5d54fc65b9" version = "3.0.2+0" ```

Expected behavior

A clear and concise description of what you expected to happen.

No OOM, which is the case if you GC.gc() each loop (turn that on via train(limit=3, gpu_gc=true, gpu_stats=true)

Version info

Details on Julia:

julia> versioninfo()
Julia Version 1.9.4
Commit 8e5136fa297 (2023-11-14 08:46 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 32 × AMD Ryzen 9 5950X 16-Core Processor
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-14.0.6 (ORCJIT, znver3)
  Threads: 5 on 32 virtual cores

Details on CUDA:

CUDA runtime 12.3, artifact installation
CUDA driver 12.0
NVIDIA driver 525.147.5

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+525.147.5

Julia packages: 
- CUDA: 5.1.1
- CUDA_Driver_jll: 0.7.0+0
- CUDA_Runtime_jll: 0.10.1+0

Toolchain:
- Julia: 1.9.4
- LLVM: 14.0.6

1 device:
  0: NVIDIA GeForce RTX 3080 (sm_86, 10.301 GiB / 12.000 GiB available)

Additional context

Add any other context about the problem here.

CUDA.jl debug prints added

diff --git a/src/pool.jl b/src/pool.jl
index 9d476d591..4a134e6c5 100644
--- a/src/pool.jl
+++ b/src/pool.jl
@@ -363,25 +363,35 @@ function retry_reclaim(f, isfailed)
     state = active_state()
     is_stream_ordered = stream_ordered(state.device)

+    println(Core.stdout, "WARNING: CUDA memory allocation failed; attempting to free up memory...")
+
     phase = 1
     while true
+      before_memory = used_memory()
       if is_stream_ordered
         if phase == 1
+          print(Core.stdout, "... waiting for pending frees")
           synchronize(state.stream)
         elseif phase == 2
+          print(Core.stdout, "... waiting for all pending frees")
           device_synchronize()
         elseif phase == 3
+          print(Core.stdout, "... running a quick GC")
           GC.gc(false)
           device_synchronize()
         elseif phase == 4
+          print(Core.stdout, "... running a full GC")
           GC.gc(true)
           device_synchronize()
         elseif phase == 5
           # in case we had a release threshold configured
+          print(Core.stdout, "... releasing reserved memory")
           trim(memory_pool(state.device))
         else
           break
         end
+        after_memory = used_memory()
+        println(Core.stdout, " (freed $(Base.format_bytes(before_memory - after_memory)))")
       else
         if phase == 1
           GC.gc(false)
IanButterworth commented 11 months ago

@maleadt reported that in julia 1.10 on their setup the OOM happens sooner

❯ JULIA_CUDA_HARD_MEMORY_LIMIT=12GB jl --project effnet_train.jl
[ Info: loading CIFAR-10 dataset
[ Info: loading EfficientNetv2 model
[ Info: starting training

┌ Error: Out of GPU memory trying to allocate 4.578 GiB
│ Effective GPU memory usage: 24.97% (11.808 GiB/47.296 GiB)
│ Memory pool usage: 4.017 GiB (11.188 GiB reserved)
│ Memory limit: hard = 11.176 GiB
└ @ Main ~/Julia/tmp/EfficientNet-Training/effnet_train.jl:104
IanButterworth commented 11 months ago

I have been trying to look for differences in GC collections with GC logging on. On the left here is with the try-catch, on the right is without. The GC operations seem to happen in the same sequence. You can see pool_used_bytes jumps up on the left, and doesn't on the right, but on the right there's no big GC collect, which I was expecting to see

image

maleadt commented 11 months ago

On Slack, we determined that this is likely due to objects being kept alive in upsilon nodes due to the try/catch. Unclear why calling GC.gc helps for that, but this does look like a Julia bug...