Host OOM Killed
Host OOM (out of memory) kills training processes when system RAM is exhausted, often silently.
Host OOM (out of memory) kills training processes when system RAM is exhausted, often silently.
What this failure is
Host OOM Killed is a Memory failure seen during ML training runs. Host OOM (out of memory) kills training processes when system RAM is exhausted, often silently. Common tags: Host","Oom","Memory","System","Kill, Ram.
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Why it happens (the mechanism)
System RAM exhausted by CPU-side tensor operations. Dataloader workers use too much shared memory. CPU offloaded optimizer states exhaust system memory. Taken together, these mechanisms explain why the failure is reproducible, why it tends to surface on specific workloads or scales, and why generic mitigation attempts often fall short without addressing the underlying cause.
What you'll observe
- Training process is killed with no error
- dmesg shows OOM killer messages
- Process killed with signal 9 (SIGKILL)
Common symptoms and what they mean
| Symptom | Why it happens |
|---|---|
| Killed process in dmesg: Out of memory: Killed process | System RAM exhausted by CPU-side tensor operations |
| Memory cgroup limit reached | Dataloader workers use too much shared memory |
| System swap usage at 100% before kill | CPU offloaded optimizer states exhaust system memory |
Which systems are affected
- Training with many dataloader workers
- CPU model offloading for large models
- Data preprocessing pipelines in same process
How to confirm this is the problem
Use this checklist to test the hypothesis against a small reproduction. No single line proves the root cause, so preserve the preceding events and compare one variable at a time.
- ✓Reproduce the failure from a clean checkpoint/seed: the symptom must appear without warm-up state from a previous run.
- ✓Verified signal present: Killed process in dmesg: Out of memory: Killed process
- ✓Verified signal present: Memory cgroup limit reached
- ✓Verified signal present: System swap usage at 100% before kill
- ✓A targeted fix from the "How to fix it" section eliminates or substantially reduces the symptom within one validation pass.
The fix and the prevention pattern
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Diagnose this failure in VS Code
Select the traceback or open the failed terminal, then run Denpex locally to see the initiating rank, collateral failures, exact fix, and verification command without uploading the log.
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Root cause
- System RAM exhausted by CPU-side tensor operations
- Dataloader workers use too much shared memory
- CPU offloaded optimizer states exhaust system memory
The fix and how to prevent it
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