Problem description：
I compile the pytorch source code in arm machine.And I want to use DDP interface for
distributed training.However, I found that pytorch could only find one physical CPU, which means that my CPU usage cannot exceed 50%.(The machine has two sockets)
My machine contains two physical Cpus, each with 64 cores.
I use OpenBLAS as the BLAS and I compile it with openmp.In the script, I set the environment variable
export OMP_NUM_THREADS=128
export GOMP_CPU_AFFINITY=0-127
export OMP_DISPLAY_ENV=true

Then when I execute my script
python3 -m torch.distributed.launch \
--nproc_per_node=$NPROC_PER_NODE \
script.py 2>&1

Then I found out that all the threads were running on the same CPU core and it ouput:
OPENMP DISPLAY ENVIRONMENT BEGIN
  _OPENMP = '201511'
  OMP_DYNAMIC = 'FALSE'
  OMP_NESTED = 'FALSE'
  OMP_NUM_THREADS = '64'
  OMP_SCHEDULE = 'DYNAMIC'
  OMP_PROC_BIND = 'TRUE'
  OMP_PLACES = '{0},{1},{2},{3},{4},{5},{6},{7},{8},{9},{10},{11},{12},{13},{14},{15},{16},{17},{18},{19},{20},{21},{22},{23},{24},{25},{26},{27},{28},{29},{30},{31},{32},{33},{34},{35},{36},{37},{38},{39},{40},{41},{42},{43},{44},{45},{46},{47},{48},{49},{50},{51},{52},{53},{54},{55},{56},{57},{58},{59},{60},{61},{62},{63},{64},{65},{66},{67},{68},{69},{70},{71},{72},{73},{74},{75},{76},{77},{78},{79},{80},{81},{82},{83},{84},{85},{86},{87},{88},{89},{90},{91},{92},{93},{94},{95},{96},{97},{98},{99},{100},{101},{102},{103},{104},{105},{106},{107},{108},{109},{110},{111},{112},{113},{114},{115},{116},{117},{118},{119},{120},{121},{122},{123},{124},{125},{126},{127}'
  OMP_STACKSIZE = '0'
  OMP_WAIT_POLICY = 'PASSIVE'
  OMP_THREAD_LIMIT = '4294967295'
  OMP_MAX_ACTIVE_LEVELS = '2147483647'
  OMP_CANCELLATION = 'FALSE'
  OMP_DEFAULT_DEVICE = '0'
  OMP_MAX_TASK_PRIORITY = '0'
  OMP_DISPLAY_AFFINITY = 'FALSE'
  OMP_AFFINITY_FORMAT = 'level %L thread %i affinity %A'
OPENMP DISPLAY ENVIRONMENT END

OPENMP DISPLAY ENVIRONMENT BEGIN
  _OPENMP = '201511'
  OMP_DYNAMIC = 'FALSE'
  OMP_NESTED = 'FALSE'
  OMP_NUM_THREADS = '64'
  OMP_SCHEDULE = 'DYNAMIC'
  OMP_PROC_BIND = 'TRUE'
  OMP_PLACES = '{0},{1},{2},{3},{4},{5},{6},{7},{8},{9},{10},{11},{12},{13},{14},{15},{16},{17},{18},{19},{20},{21},{22},{23},{24},{25},{26},{27},{28},{29},{30},{31},{32},{33},{34},{35},{36},{37},{38},{39},{40},{41},{42},{43},{44},{45},{46},{47},{48},{49},{50},{51},{52},{53},{54},{55},{56},{57},{58},{59},{60},{61},{62},{63}'
  OMP_STACKSIZE = '0'
  OMP_WAIT_POLICY = 'PASSIVE'
  OMP_THREAD_LIMIT = '4294967295'
  OMP_MAX_ACTIVE_LEVELS = '2147483647'
  OMP_CANCELLATION = 'FALSE'
  OMP_DEFAULT_DEVICE = '0'
  OMP_MAX_TASK_PRIORITY = '0'
  OMP_DISPLAY_AFFINITY = 'FALSE'
  OMP_AFFINITY_FORMAT = 'level %L thread %i affinity %A'
OPENMP DISPLAY ENVIRONMENT END

Could someone tell me what is the reason? Thanks!
environment
Collecting environment information...
PyTorch version: 1.6.0a0+b31f58d
Is debug build: No
CUDA used to build PyTorch: None

OS: CentOS Linux release 7.6.1810 (AltArch)
GCC version: (GCC) 9.2.0
CMake version: version 3.16.5

Python version: 3.7
Is CUDA available: No
CUDA runtime version: No CUDA
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA

Versions of relevant libraries:
[pip3] numpy==1.19.1
[pip3] torch==1.6.0a0+b31f58d
[conda] Could not collect