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Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Cannot build libtorch from source with NVHPC compilers - "Could NOT find Threads" #135437

Open stenczelt opened 1 month ago

stenczelt commented 1 month ago

🐛 Describe the bug

Tried to build libtorch from source with NVHPC compilers, and ran into problems with the cmake settings:

CMAKE_Fortran_COMPILER=/opt/nvidia/hpc_sdk/Linux_x86_64/24.5/comm_libs/mpi/bin/mpif90 CMAKE_C_COMPILER=/opt/nvidia/hpc_sdk/Linux_x86_64/24.5/comm_libs/mpi/bin/mpicc CMAKE_CXX_COMPILER=/opt/nvidia/hpc_sdk/Linux_x86_64/24.5/comm_libs/mpi/bin/mpic++ CMAKE_PREFIX_PATH="/opt/nvidia/hpc_sdk/Linux_x86_64/24.5/cuda/12.4" USE_CUDA=1 python tools/build_libtorch.py --cmake-only --rerun-cmake

results in logs-issue.txt

[... see full output attached ...]
CMake Error at /opt/cmake/share/cmake-3.30/Modules/FindPackageHandleStandardArgs.cmake:233 (message):
  Could NOT find Threads (missing: Threads_FOUND)
Call Stack (most recent call first):
  /opt/cmake/share/cmake-3.30/Modules/FindPackageHandleStandardArgs.cmake:603 (_FPHSA_FAILURE_MESSAGE)
  /opt/cmake/share/cmake-3.30/Modules/FindThreads.cmake:226 (FIND_PACKAGE_HANDLE_STANDARD_ARGS)
  cmake/Modules/FindCUDAToolkit.cmake:947 (find_package)
  cmake/public/cuda.cmake:59 (find_package)
  cmake/Dependencies.cmake:44 (include)
  CMakeLists.txt:863 (include)

I can't find anything in associated compiler docs about threads.

I've tried installing libpthread with sudo apt-get install libpthread-stubs0-dev as well, and adding /usr/lib/x86_64-linux-gnu/ to the CMAKE_PREFIX_PATH above, but that did not solve the problem either.

Are the settings incorrect, or is some library missing here?

The compiler versions used:

/opt/nvidia/hpc_sdk/Linux_x86_64/24.5/comm_libs/mpi/bin/mpic++ --version

nvc++ 24.5-1 64-bit target on x86-64 Linux -tp cascadelake 
NVIDIA Compilers and Tools
Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES.  All rights reserved.

and nvhpc-24-5 was installed using apt-get.

Versions

Collecting environment information...
PyTorch version: N/A
Is debug build: N/A
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: version 3.30.3
Libc version: glibc-2.31

Python version: 3.9.5 (default, Nov 23 2021, 15:27:38)  [GCC 9.3.0] (64-bit runtime)
Python platform: Linux-5.15.0-88-generic-x86_64-with-glibc2.31
Is CUDA available: N/A
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: 
GPU 0: NVIDIA A100 80GB PCIe
  MIG 3g.40gb     Device  0:

Nvidia driver version: 550.54.15
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: N/A

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Byte Order:                         Little Endian
Address sizes:                      46 bits physical, 48 bits virtual
CPU(s):                             32
On-line CPU(s) list:                0-31
Thread(s) per core:                 1
Core(s) per socket:                 32
Socket(s):                          1
NUMA node(s):                       1
Vendor ID:                          GenuineIntel
CPU family:                         6
Model:                              85
Model name:                         Intel Xeon Processor (Cascadelake)
Stepping:                           5
CPU MHz:                            2593.906
BogoMIPS:                           5187.81
Virtualization:                     VT-x
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          1 MiB
L1i cache:                          1 MiB
L2 cache:                           128 MiB
NUMA node0 CPU(s):                  0-31
Vulnerability Gather data sampling: Unknown: Dependent on hypervisor status
Vulnerability Itlb multihit:        KVM: Mitigation: VMX disabled
Vulnerability L1tf:                 Mitigation; PTE Inversion; VMX conditional cache flushes, SMT disabled
Vulnerability Mds:                  Mitigation; Clear CPU buffers; SMT Host state unknown
Vulnerability Meltdown:             Mitigation; PTI
Vulnerability Mmio stale data:      Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Retbleed:             Mitigation; IBRS
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; IBRS, IBPB conditional, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Mitigation; Clear CPU buffers; SMT Host state unknown
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq vmx ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 arat avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq md_clear arch_capabilities

Versions of relevant libraries:
[pip3] numpy==2.0.2
[conda] Could not collect

cc @malfet @seemethere @ptrblck @msaroufim

stenczelt commented 1 month ago

This relates to https://github.com/pytorch/pytorch/issues/82627#issuecomment-2336693228