Repository: pytorch
Issue: Segmentation fault (core dumped) in `torch.autograd.profiler.profile`
Labels: triage review,oncall: profiler

### 🐛 Describe the bug

torch.autograd.profiler.profile triggered a crash when the gpu is available.
minimal example:

```
import threading
import torch
from torch.autograd.profiler import profile

def multi_threaded_profiler():
    with profile() as prof:
        torch.add(1, 1)
        torch.mul(1, 1)

def test_multithread_profiler_crash(self):
    threads = []

    for _ in range(10):
        t = threading.Thread(target=multi_threaded_profiler)
        threads.append(t)
        t.start()

    for t in threads:
        t.join()

test_multithread_profiler_crash(None)
```

outputs:
```
ERROR: External init callback must run in same thread as registerClient (1040168512 != -1250609344)
WARNING:2024-11-15 09:40:15 660751:660824 init.cpp:178] function cbapi->getCuptiStatus() failed with error CUPTI_ERROR_MULTIPLE_SUBSCRIBERS_NOT_SUPPORTED (39)
ERROR: External init callback must run in same thread as registerClient (1446118976 != -1250609344)
WARNING:2024-11-15 09:40:15 660751:660829 init.cpp:178] function cbapi->getCuptiStatus() failed with error CUPTI_ERROR_MULTIPLE_SUBSCRIBERS_NOT_SUPPORTED (39)WARNING:2024-11-15 09:40:15 660751:660826 init.cpp:178] function cbapi->getCuptiStatus() failed with error CUPTI_ERROR_MULTIPLE_SUBSCRIBERS_NOT_SUPPORTED (39)

WARNING:2024-11-15 09:40:15 660751:660827 init.cpp:178] function cbapi->getCuptiStatus() failed with error CUPTI_ERROR_MULTIPLE_SUBSCRIBERS_NOT_SUPPORTED (39)
Segmentation fault (core dumped)
```



### Versions

PyTorch version: 2.5.1+cu124                                                                                                                                                                        
Is debug build: False                                                                                                                                                                               
CUDA used to build PyTorch: 12.4                                                                                                                                                                    
ROCM used to build PyTorch: N/A                                                                                                                                                                     
                                                                                                                                                                                                    
OS: Ubuntu 22.04 LTS (x86_64)                                                                                                                                                                       
GCC version: (Ubuntu 11.2.0-19ubuntu1) 11.2.0                                                                                                                                                       
Clang version: Could not collect                                                                                                                                                                    
CMake version: version 3.22.1                                                                                                                                                                       
Libc version: glibc-2.35                                                                                                                                                                            
                                                                                                                                                                                                    
Python version: 3.9.13 (main, Oct 13 2022, 21:15:33)  [GCC 11.2.0] (64-bit runtime)                                                                                                                 
Python platform: Linux-5.15.0-119-generic-x86_64-with-glibc2.35                                                                                                                                     
Is CUDA available: True                                                                                                                                                                             
CUDA runtime version: Could not collect                                                                                                                                                             
CUDA_MODULE_LOADING set to: LAZY                                                                                                                                                                    
GPU models and configuration:                                                                                                                                                                       
GPU 0: NVIDIA GeForce RTX 4090                                                                                                                                                                      
GPU 1: NVIDIA GeForce RTX 4090                                                                                                                                                                      
                                                                                                                                                                                                    
Nvidia driver version: 535.183.01                                                                                                                                                                   
cuDNN version: Could not collect                                                                                                                                                                    
HIP runtime version: N/A                                                                                                                                                                            
MIOpen runtime version: N/A                                                                                                                                                                         
Is XNNPACK available: True                                                                                                                                                                          
                                                                                                                                                                                                    
CPU:                                                                                                                                                                                                
Architecture:                         x86_64                                                                                                                                                        
CPU op-mode(s):                       32-bit, 64-bit                                                                                                                                                
Address sizes:                        46 bits physical, 57 bits virtual                                                                                                                             
Byte Order:                           Little Endian                                                                                                                                                 
CPU(s):                               128                                                                                                                                                           
On-line CPU(s) list:                  0-127                                                                                                                                                         
Vendor ID:                            GenuineIntel                                                                                                                                                  
Model name:                           INTEL(R) XEON(R) GOLD 6530                                                                                                                                    
CPU family:                           6                                                                                                                                                             
Model:                                207                                                                                                                                                           
Thread(s) per core:                   2
Core(s) per socket:                   32
Socket(s):                            2
Stepping:                             2
CPU max MHz:                          4000.0000
CPU min MHz:                          800.0000
BogoMIPS:                             4200.00
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_
tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x
2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanc
ed tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni 
avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_ep
p hwp_pkg_req avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm m
d_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities                                                                                      
Virtualization:                       VT-x                                                                                                                                                          
L1d cache:                            3 MiB (64 instances)                                                                                                                                          
L1i cache:                            2 MiB (64 instances)                                                                                                                                          
L2 cache:                             128 MiB (64 instances)                                                                                                                                        
L3 cache:                             320 MiB (2 instances)                                                                                                                                         
NUMA node(s):                         4                                                                                                                                                             
NUMA node0 CPU(s):                    0-15,64-79                                                                                                                                                    
NUMA node1 CPU(s):                    16-31,80-95                                                                                                                                                   
NUMA node2 CPU(s):                    32-47,96-111                                                                                                                                                  
NUMA node3 CPU(s):                    48-63,112-127                                                                                                                                                 
Vulnerability Gather data sampling:   Not affected                                                                                                                                                  
Vulnerability Itlb multihit:          Not affected                                                                                                                                                  
Vulnerability L1tf:                   Not affected                                                                                                                                                  
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
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; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] numpy==2.0.2
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] torch==2.5.1
[pip3] torchaudio==2.5.1
[pip3] torchvision==0.20.1
[pip3] triton==3.1.0
[conda] numpy                     2.0.2                    pypi_0    pypi
[conda] nvidia-cublas-cu12        12.4.5.8                 pypi_0    pypi
[conda] nvidia-cuda-cupti-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-nvrtc-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-runtime-cu12  12.4.127                 pypi_0    pypi
[conda] nvidia-cudnn-cu12         9.1.0.70                 pypi_0    pypi
[conda] nvidia-cufft-cu12         11.2.1.3                 pypi_0    pypi
[conda] nvidia-curand-cu12        10.3.5.147               pypi_0    pypi
[conda] nvidia-cusolver-cu12      11.6.1.9                 pypi_0    pypi
[conda] nvidia-cusparse-cu12      12.3.1.170               pypi_0    pypi
[conda] nvidia-nccl-cu12          2.21.5                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.4.127                 pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.4.127                 pypi_0    pypi
[conda] torch                     2.5.1                    pypi_0    pypi
[conda] torchaudio                2.5.1                    pypi_0    pypi
[conda] torchvision               0.20.1                   pypi_0    pypi
[conda] triton                    3.1.0                    pypi_0    pypi

cc @robieta @chaekit @guotuofeng @guyang3532 @dzhulgakov @davidberard98 @briancoutinho @sraikund16 @sanrise