Troubleshooting

GPU not detected

Symptoms:

• CUDA tests fail to find a device.
• GPU demo reports gpu_available:false.

Checks:

docker compose run --rm dev nvidia-smi
docker compose run --rm dev bash -lc 'ls /dev/nvidia* 2>/dev/null || true'

Fixes:

• Install or enable nvidia-container-toolkit.
• Restart Docker after driver installation.
• Ensure the host driver supports CUDA 13.x.
• Confirm NVIDIA_VISIBLE_DEVICES=all is set for the container.

Driver mismatch

Symptoms:

• CUDA driver version is insufficient for CUDA runtime version.
• nvidia-smi fails inside the container.

Fixes:

• Update the host NVIDIA driver.
• Rebuild the dev image only if the Dockerfile CUDA tag changes.
• Do not install a host CUDA toolkit to fix container runtime issues.

Out of memory

Symptoms:

• cuBLAS or cuSOLVER allocation fails.
• GPU tests skip or fail on large matrices.

Fixes:

• Reduce numSamples, numHiddenNodes, or layer widths.
• Prefer the dual ridge path when hidden nodes greatly exceed samples.
• Run smaller benchmarks before scaling up.

Port conflicts

Symptoms:

• Demo server fails to bind to 0.0.0.0:8888.

Fixes:

docker run --rm -p 8080:8888 feature-elm-demo-cpu

Change the host port while keeping the container port at 8888.

Broken docs links

Run:

docker compose run --rm dev ./scripts/docs_check.sh

Fix Markdown links relative to the page that contains them. Use ../architecture.md from nested pages such as docs/upgrade/....

Numerical instability

Symptoms:

• Predictions explode after online updates.
• Batch solve returns poor accuracy.

Fixes:

• Increase ridgeAlpha.
• For online streams, set regularization > 0.
• For drift, use forgettingFactor < 1.
• Compare CPU and GPU results on small matrices before scaling.