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CUDA Illegal Instruction

CUDA illegal instruction errors crash training when the GPU encounters unsupported instructions, often from binary mismatches.

Quick answer

CUDA illegal instruction errors crash training when the GPU encounters unsupported instructions, often from binary mismatches.

Hardware#cuda#illegal-instruction#gpu#hardware#compute-capability#nvidia

What this failure is

CUDA Illegal Instruction is a Hardware failure seen during ML training runs. CUDA illegal instruction errors crash training when the GPU encounters unsupported instructions, often from binary mismatches. Common tags: Cuda, Illegal Instruction, Gpu, Hardware.

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Why it happens (the mechanism)

CUDA binary compiled for newer compute capability than GPU supports. GPU driver incompatibility with CUDA toolkit. PyTorch compiled for different SM version than GPU. Custom CUDA kernels compiled without proper arch flags. 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 crashes with CUDA illegal instruction
  • Error points to specific CUDA instruction
  • GPU supports older compute capability than required

Common symptoms and what they mean

SymptomWhy it happens
CUDA error: an illegal instruction was encounteredCUDA binary compiled for newer compute capability than GPU supports
RuntimeError: CUDA error: illegal instructionGPU driver incompatibility with CUDA toolkit
GPU compute capability mismatchPyTorch compiled for different SM version than GPU

Which systems are affected

  • Training on older GPUs with newer CUDA toolkit
  • Compiled binaries for newer GPU architectures
  • Mixed compute capabilities in cluster

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: CUDA error: an illegal instruction was encountered
  • ✓Verified signal present: RuntimeError: CUDA error: illegal instruction
  • ✓Verified signal present: GPU compute capability mismatch
  • ✓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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CUDA errors in context

CUDA reports errors asynchronously, so the traceback usually points at whatever line synchronised next rather than the one at fault. The hub covers every common CUDA error and how to make it report honestly.

Compare every cuda error side by side

Related failures to investigate next

Gpu Memory Clock Throttle often co-occurs with this failure because both share underlying assumptions about hardware; if you fix this entry but still see drift, validate the related primary cause next. gpu memory clock throttle →
Gpu Clock Throttle often co-occurs with this failure because both share underlying assumptions about hardware; if you fix this entry but still see drift, validate the related neighboring cause next. gpu clock throttle →
Gsp Rpc Timeout Xid119 often co-occurs with this failure because both share underlying assumptions about hardware; if you fix this entry but still see drift, validate the related neighboring cause next. gsp rpc timeout xid119 →

Root cause

  • CUDA binary compiled for newer compute capability than GPU supports
  • GPU driver incompatibility with CUDA toolkit
  • PyTorch compiled for different SM version than GPU
  • Custom CUDA kernels compiled without proper arch flags

The fix and how to prevent it

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References

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Related Hardware errors

GPU Memory Clock Throttle

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NVLink Error

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GPU Thermal Throttling

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GPU Power Cap Reached

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