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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11To diagnose a Linux multiprocessing hang, first identify the parent, child processes, and threads that have stopped making progress. Then compare repeated process snapshots, inspect kernel wait locations, trace system calls across workers, and collect native or Python stack traces. A blocked process or thread is evidence of waiting—not, by itself, proof of a deadlock. To establish a deadlock, find the dependency cycle or missing event that prevents progress.
1. Establish which processes and threads have stopped progressing
Start by recording the command, start time, parent PID, child PIDs, thread counts, CPU use, and whether logs or output are still changing. Take at least two observations a short interval apart: one snapshot shows a state, but cannot show whether that state is persistent.
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On systems with the relevant procps columns, this command gives a useful process-tree snapshot:
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ps -eo pid,ppid,tid,stat,wchan:24,etime,pcpu,comm --forestColumn availability can vary by procps version. For an individual process, Linux exposes a numbered /proc/PID directory; its task directory contains one subdirectory per thread, named by thread ID (TID):
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ls /proc/PID/taskReplace PID with the process ID you are investigating. Keep the parent-child relationships and thread IDs alongside your snapshots so you can match later trace and stack output to the right worker.
2. Check where each task is waiting
Read /proc/PID/wchan for a process and, where needed, /proc/PID/task/TID/wchan for a particular thread. The value is a symbolic kernel location where that task is sleeping. It can help distinguish a sleeping task from one consuming CPU, but it does not identify the application-level lock, queue, or condition responsible for the wait.
Access to wchan is subject to a ptrace access check. A permission error or missing information may reflect the current user, ptrace settings, or container policy rather than the absence of a wait.
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3. Trace system calls across the parent and workers
When process state and wait channels do not explain the stall, attach strace to the parent and follow its descendants:
strace -ff -tt -T -p PID -o /tmp/traceUse the PID of the process under investigation. The -f option follows processes created by fork, vfork, and clone; for a multithreaded target, it attaches to the threads as well. With -ff, output is split into files for individual processes. Match those files to PIDs and application logs rather than treating a trace file as a complete explanation on its own.
Look for an unfinished system call or repeated waits that fit the observed stall: for example, a blocked read, pipe operation, futex wait, or wait for a child. The trace records system calls, arguments, return values, and signals; this can reveal where a process is waiting or what event it has not received. It does not necessarily show why the application-level event is missing. Tracing can alter timing and affect performance, so use it deliberately on performance-sensitive production workloads.
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4. Collect native stacks when syscall traces are not enough
Attach GDB to a running process and request a backtrace with bt. Inspect the relevant threads, then compare stacks from the parent and worker processes. A stack shows current call paths and may reveal a thread stopped in a synchronization routine or blocked in I/O.
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5. Capture Python thread tracebacks for intermittent stalls
For Python programs, faulthandler.dump_traceback_later(timeout) can schedule a traceback dump after a timeout and can repeat it. Configure it before a failure if the hang is intermittent or difficult to reproduce interactively:
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import faulthandler
faulthandler.dump_traceback_later(60, repeat=True)Keep the output file open until the dump is written or the scheduled dump is canceled, and cancel the watchdog when it is no longer needed. These tracebacks show Python frames; if a thread is stuck in a native wait, syscall tracing or GDB may be needed as well. The Python 3.14 documentation notes a special case for free-threaded operation with the GIL disabled: to avoid data races, the dump includes only the current thread.
6. Check Python multiprocessing joins, queues, and worker state
Check whether a join is actually complete
For each process, inspect is_alive() and exitcode, and use a timeout where appropriate. In Python, join(timeout) returns None both when the process has ended and when the timeout expires. Check exitcode or is_alive() afterward; the return value alone does not tell you whether the child finished.
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Look for queue-and-join ordering problems
The Python multiprocessing documentation describes a deadlock pattern in which a child puts a large payload on a queue and the parent joins that child before reading the queued data. The child can be unable to finish flushing the item while the parent waits for it to exit. In that documented example, draining the queue before joining—or removing the premature join—resolves the ordering problem.
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Do not treat termination as a harmless reset
Terminating a process while it owns a lock or semaphore can leave other processes deadlocked. Termination can also corrupt a pipe or queue that is in use. Before killing a worker, capture the state and check what shared resources it may hold.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.7. Decide whether the evidence supports calling it a deadlock
A hang means expected progress has stopped. A deadlock is a stronger causal diagnosis: participants are waiting on conditions that cannot be satisfied because of their dependencies. Other explanations include slow work, a blocked external service, exhausted file descriptors, a lost queue consumer, a crashed child that the parent is waiting for, or a worker waiting for a resource held by a task that is still progressing.
Build the diagnosis from a stable pattern across observations. Use traces and stacks to locate waits, then use application-level ownership or event logs to connect them: which participant holds a needed resource, which participant is waiting for it, and what event would allow either one to continue? A single wait-channel value, blocked syscall, or stack frame does not automatically answer those questions, and none of these tools detects every deadlock by itself.
How the diagnostic methods compare
| Method | Evidence | Useful for | Limits |
|---|---|---|---|
/proc/PID/task/TID and wchan |
Thread inventory and symbolic kernel sleep location | A fast host-side snapshot of per-thread state | Access can be restricted; the wait location is not the application-level cause. Linux procfs documentation. |
strace -f |
System-call and signal history across child processes and threads | Finding kernel waits, missing reads or writes, and process wait patterns | Tracing can affect timing and performance. The strace manual. |
| GDB backtrace | Native call stacks in a running process | Seeing where threads are blocked in application or library code | Attachment permissions and symbols matter; a stack is a snapshot, not a causal graph. GDB documentation. |
Python faulthandler |
Python thread tracebacks after a timeout | Capturing intermittent Python-level stalls | Native waits may need other tools; free-threaded behavior differs. Python 3.14 documentation. |
Choose the least intrusive method that can answer the next specific question. A process inventory can narrow the target; a syscall trace can expose a kernel-level wait; stacks can show the code path; and application-level state can establish the dependency that makes a wait causal.
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