Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
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Install Holoscan SDK natively on Ubuntu via apt. Use for C++ installs on Ubuntu; pair with /holoscan-install-wheel for Python.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Install the Holoscan SDK C++ runtime + headers on Ubuntu using NVIDIA's apt repo, selecting the right holoscan-cuda-* package for the host's CUDA driver and verifying with the bundled C++ examples.
nvidia-smi).sudo and network access to developer.download.nvidia.com and docs.nvidia.com.cuda-keyring package (Step 2 installs it if missing)./holoscan-install-wheel if the user needs Python.holoscan-cuda-12 vs holoscan-cuda-13); wrong variant → "CUDA driver version is insufficient".Fetch the Debian/apt section of https://docs.nvidia.com/holoscan/sdk-user-guide/sdk_installation.html before installing. Extract:
holoscan-cuda-12, holoscan-cuda-13, holoscan)If the doc disagrees with anything below, the doc wins.
Determine OS version and CUDA variant if not already known — run in parallel:
lsb_release -a 2>/dev/null || cat /etc/os-release
nvidia-smi 2>&1 | head -5
CUDA variant rule — pick the apt package:
| nvidia-smi CUDA Version | Package |
|---|---|
| 13.x+ | holoscan-cuda-13 |
| 12.x (on IGX) | holoscan |
| 12.x (not on IGX) | holoscan-cuda-12 |
| 12.x (nvgpu) | holoscan-cuda-12 |
dpkg -l | grep cuda-keyring
dpkg -l | grep -E "holoscan-cuda-(12|13)|^ii holoscan "
apt-cache show holoscan-cuda-13 holoscan-cuda-12 2>/dev/null | grep -E "^(Package|Version)"
Decision rules based on what Step 1 found:
cuda-keyring is already installed.apt-get update if the repo is already configured and the package is visible in apt-cache show.holoscan-cuda-12 when targeting cu12).Skip this step if the package is already installed (detected in Step 1) or if user is on IGX platform.
# If cuda-keyring missing (adjust ubuntu2204/ubuntu2404 as needed) and not on IGX platform:
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb && sudo apt-get update
sudo apt-get install -y holoscan-cuda-12 # or holoscan-cuda-13
Set the env once for the rest of this step, then run the three C++ checks:
HS=/opt/nvidia/holoscan
export LD_LIBRARY_PATH=$HS/lib
export HOLOSCAN_INPUT_PATH=$HS/data
ulimit -s 32768
ls $HS/examples/{hello_world,tensor_interop,video_replayer}/
# hello_world — expected: "Hello World!"
$HS/examples/hello_world/cpp/hello_world
# tensor_interop — expected: tensors doubling each pass, "Graph execution finished."
# If "CUDA driver version is insufficient": swap package variant:
# sudo apt-get remove -y holoscan-cuda-13 && sudo apt-get install -y holoscan-cuda-12
$HS/examples/tensor_interop/cpp/tensor_interop
# video_replayer (10 frames, headless) — expected: Vulkan selects NVIDIA GPU, "Graph execution finished."
# Always run headless: works with or without a display, avoids GUI failure modes over SSH.
ls $HS/data/racerx 2>/dev/null || sudo $HS/examples/download_example_data
python3 -c "
c=open('$HS/examples/video_replayer/cpp/video_replayer.yaml').read()
c=c.replace('count: 0','count: 10').replace('repeat: true','repeat: false').replace('realtime: true','realtime: false')
c=c.replace(' width: 854',' headless: true\n width: 854')
open('/tmp/vr.yaml','w').write(c)"
$HS/examples/video_replayer/cpp/video_replayer --config /tmp/vr.yaml
Once verified, share this snippet with user and suggest adding it to their shell startup file (e.g., ~/.bashrc) if they want it to persist across sessions:
export LD_LIBRARY_PATH=/opt/nvidia/holoscan/lib:${LD_LIBRARY_PATH}
export HOLOSCAN_INPUT_PATH=/opt/nvidia/holoscan/data
ulimit -s 32768
Then offer next steps:
/holoscan-install-wheells /opt/nvidia/holoscan/examples//explain-examplepython3 -c "import holoscan" fails after apt install. Expected — the Debian package has been C++ only since v3.0.0. Run /holoscan-install-wheel to add Python bindings.nvidia-smi CUDA Version and swap variants: sudo apt-get remove -y holoscan-cuda-13 && sudo apt-get install -y holoscan-cuda-12 (or vice versa).E: Unable to locate package holoscan-cuda-12. cuda-keyring not installed or repo not yet pulled. Run the keyring + apt-get update block in Step 2 (adjust ubuntu2204/ubuntu2404 to match the host).ulimit -s 32768 not set in the current shell. Prepend it to the command (Step 3 pattern).error while loading shared libraries: libholoscan_core.so. LD_LIBRARY_PATH is unset. Use the env snippet from Step 4 — export LD_LIBRARY_PATH=/opt/nvidia/holoscan/lib.video_replayer can't find data. Set HOLOSCAN_INPUT_PATH=/opt/nvidia/holoscan/data, or run sudo /opt/nvidia/holoscan/examples/download_example_data to fetch the racerx dataset.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
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Customize NVIDIA Nemotron Voice Agent's Generic Pipecat example for healthcare appointment, five-field patient intake, or custom tool-calling workflows without a separate backend.
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Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.
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Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
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Calibrates pre-recorded `cam_*.mp4` datasets through the AutoMagicCalib REST API. Use for user-supplied local MP4s; route live RTSP streams to `amc-run-rtsp-calibration`.
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Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.
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