Can't build cuDNN on centos7.8

[kongdd]

Can't build cuDNN on centos7.8 with GLIBC_2.17.

julia> using CUDA

julia> using Flux
        Info Given cuDNN was explicitly requested, output will be shown live
ERROR: LoadError: InitError: could not load library "/share/home/kong/.julia/artifacts/8e7456794f147517aa9ba5a1147e4ecedffbbfa1/lib/libcudnn_cnn.so"
/lib64/libm.so.6: version `GLIBC_2.27' not found (required by /share/home/kong/.julia/artifacts/8e7456794f147517aa9ba5a1147e4ecedffbbfa1/lib/libcudnn_cnn.so)
Stacktrace:
  [1] dlopen(s::String, flags::UInt32; throw_error::Bool)
    @ Base.Libc.Libdl ./libdl.jl:117
  [2] dlopen(s::String, flags::UInt32)
    @ Base.Libc.Libdl ./libdl.jl:116
  [3] macro expansion
    @ ~/.julia/packages/JLLWrappers/inPJn/src/products/library_generators.jl:63 [inlined]
  [4] __init__()
    @ CUDNN_jll ~/.julia/packages/CUDNN_jll/8XeAL/src/wrappers/x86_64-linux-gnu-cuda+12.0.jl:28
  [5] run_module_init(mod::Module, i::Int64)
    @ Base ./loading.jl:1134
  [6] register_restored_modules(sv::Core.SimpleVector, pkg::Base.PkgId, path::String)
    @ Base ./loading.jl:1122
  [7] _include_from_serialized(pkg::Base.PkgId, path::String, ocachepath::String, depmods::Vector{Any})
    @ Base ./loading.jl:1067
  [8] _require_search_from_serialized(pkg::Base.PkgId, sourcepath::String, build_id::UInt128)
    @ Base ./loading.jl:1581
  [9] _require(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:1938
 [10] __require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:1812
 [11] #invoke_in_world#3
    @ ./essentials.jl:926 [inlined]
 [12] invoke_in_world
    @ ./essentials.jl:923 [inlined]
 [13] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:1803
 [14] macro expansion
    @ ./loading.jl:1790 [inlined]
 [15] macro expansion
    @ ./lock.jl:267 [inlined]
 [16] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:1753
 [17] #invoke_in_world#3
    @ ./essentials.jl:926 [inlined]
 [18] invoke_in_world
    @ ./essentials.jl:923 [inlined]
 [19] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:1746
 [20] top-level scope
    @ ~/.julia/packages/cuDNN/P9S4N/src/cuDNN.jl:20
 [21] include
    @ ./Base.jl:495 [inlined]
 [22] include_package_for_output(pkg::Base.PkgId, input::String, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:2222
 [23] top-level scope
    @ stdin:3
during initialization of module CUDNN_jll
in expression starting at /share/home/kong/.julia/packages/cuDNN/P9S4N/src/cuDNN.jl:1
in expression starting at stdin:3
  ✗ cuDNN
  0 dependencies successfully precompiled in 6 seconds. 93 already precompiled.

┌ Warning: Package cuDNN not found in current path.
│ - Run `import Pkg; Pkg.add("cuDNN")` to install the cuDNN package, then restart julia.
│ - If cuDNN is not installed, some Flux functionalities will not be available when running on the GPU.
└ @ FluxCUDAExt ~/.julia/packages/Flux/hiqg1/ext/FluxCUDAExt/FluxCUDAExt.jl:57

julia> versioninfo()
nJulia Version 1.10.5
Commit 6f3fdf7b362 (2024-08-27 14:19 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS:Linux (x86_64-linux-gnu)
  CPU: 64 × AMD EPYC 7452 32-Core Processor
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, znver2)
Threads: 1 default, 0 interactive, 1 GC (on 64 virtual cores)
Environment:
  LD_LIBRARY_PATH = 
  JULIA_SSL_NO_VERIFY_HOSTS = github.com
  JULIA_PKG_SERVER = https://mirrors.ustc.edu.cn/julia
  JULIA_SSL_CA_ROOTS_PATH = /share/opt/julias/julia-1.10/share/julia/cert.pem

julia> CUDA.versioninfo()
CUDA runtime 12.2, artifact installation
CUDA driver 12.6
NVIDIA driver 535.171.4

CUDA libraries: 
- CUBLAS: 12.2.5
- CURAND: 10.3.3
- CUFFT: 11.0.8
- CUSOLVER: 11.5.2
- CUSPARSE: 12.1.2
- CUPTI: 2023.2.2 (API 20.0.0)
- NVML: 12.0.0+535.171.4

Julia packages: 
- CUDA: 5.5.2
- CUDA_Driver_jll: 0.10.3+0
- CUDA_Runtime_jll: 0.15.3+0

Toolchain:
- Julia: 1.10.5
- LLVM: 15.0.7

Preferences:
- CUDA_Runtime_jll.version: 12.2

1 device:
  0: NVIDIA RTX A6000 (sm_86, 47.019 GiB / 47.988 GiB available)

[maleadt]

This ancient of a glibc version (CentOS 7.8 ships glibc 2.17 released in 2012) is not supported by NVIDIA; nothing we can do here, as CUDA.jl only supports the latest version of cuDNN. You can try using an older version of CUNN.jl.