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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Enable Jetson Thor 25G/10G/1G MGBE QSFP via kernel-DT overlay. Do NOT use for UPHY lane allocation or ODMDATA edits.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Thor T264 exposes mgbe0..mgbe3. On a custom carrier, the 25G QSFP cage
(or 10G / 1G fiber path) is wired to one of them through SerDes — with
or without an external MDIO PHY in front of the cage. This skill
renders the kernel-DT overlay that pairs the BPMP allocation with
kernel-side status="okay" + PHY plumbing on &mgbeN.
Out of scope:
/jetson-customize-uphy. Refuse if
the chosen uphy1-config-N doesn't allocate the target MGBE.mgbeN-speed-*, sub-node mgbeN_status=*) —
owned by /jetson-customize-uphy in its single atomic ODMDATA
commit. This skill MUST NOT touch ODMDATA=.Output is one commit to the composite custom overlay .dts in the
bsp_sources/ hardware repo. /jetson-build-source compiles the
composite to .dtbo and owns its Makefile + flash-conf registration.
ip link show mgbe<N> reports state DOWN
or NO-CARRIER on the configured controller, OR the controller
never appears at all.jetson-customize-uphy ran with uphy1-config-8 (or another config
allocating MGBE) and you now need to bring up the per-controller
side.Prerequisites:
reference_devkit: (Thor) +
custom_carrier: blocks.<source.root_path>/Linux_for_Tegra/.git exists
(/jetson-init-source)./jetson-derive-carrier has run — carrier flash-conf fork is in
the overlay tracker./jetson-customize-uphy chose a UPHY config that allocates the target
MGBE controller's lanes (uphy1-config-8 on Thor for MGBE0..3 25G).custom_carrier: is present, both
documents.custom_carrier_schematic AND
documents.custom_carrier_pinmux_xls are REQUIRED. Refuse the run
if either is missing — MGBE routing on a custom carrier cannot be
guessed. Reference-devkit-only profiles skip this check.dtc on PATH.See references/procedure.md for the full step-by-step procedure (Steps 1–8). Summary:
questions.json (controller, phy_mode, attach kind, I²C bus/addr, reset GPIO, compatible_list).pin_verifier.py for MDC/MDIO/RESET/INT; surface mismatches and route to /jetson-customize-pinmux./jetson-customize-uphy. Step 5 only records the BPMP DTB token-form inspection (sub-node vs top-level) in notes[] for audit..dts; obey the /* custom-bsp: mgbe:mgbe... */ marker contract; run the cpp/dtc/fdtoverlay pre-flight.<profile-stem>.jetson-customize-mgbe.json and emit the one-line + table summary, then drive the downstream chain via sequential AskUserQuestion prompts per references/procedure.md Step 8. Never substitute a printed "Next step: …" line for the prompts./mgbe/mgbe@N subtree — only
mgbe<N>-speed under /uphy. The mgbe<N>_status=disabled
sub-node token is silently rejected on these releases; the whole
ODMDATA line is then dropped at flash time. Always decompile BPMP
DTB (Step 3) before emitting; use the top-level dashed form
(mgbe<N>-speed-del to remove, mgbe<N>-speed-25G to set) when
the sub-node isn't there. Same wrong-form failure surface as
jetson-customize-uphy.mdio child needs both #address-cells = <1> AND
#size-cells = <0> when phy_attach_kind=="phy". Missing either
→ kernel rejects phy@<addr> reg property at probe; MGBE never
comes up.compatible must intersect live DT compatible.
UEFI plugin-manager filters by compatible match. A mismatched
overlay is silently skipped — flash succeeds, MGBE stays disabled,
no error in dmesg. Always sanity-check against
/proc/device-tree/compatible on a booted reference DUT.OVERLAY_DTB_FILE ordering is jetson-build-source's problem,
not this skill's. This skill never touches the carrier flash
conf. The composite custom overlay is registered (by
/jetson-build-source Step 5.0a) AFTER the platform
*-dynamic.dtbo, which is the correct ordering. If you find
yourself appending OVERLAY_DTB_FILE+= in this skill, you're
duplicating ownership — stop, and let the build skill do it.jetson-customize-uphy's job. If the chosen
uphy1-config-N doesn't allocate lanes for the target MGBE
controller, BL31 SError (fmon_update_config: detected fault 0x80) on cold boot. Always run /jetson-customize-uphy first; cite the
chosen uphy1-config-N in this skill's run-summary notes[].jetson-customize-uphy: mgbe<N>_status=disabled for a
controller that's already disabled in BPMP DTB is a no-op the
parser may treat as ambiguous → drops the rest of the ODMDATA
line. Disable via the kernel-DT overlay (status="disabled") only.<bsp_image.root_path>. All
edits land in the overlay tracker / bsp_sources mono-repo under
the pristine + customization commit pattern.jetson-customize-uphy: ODMDATA + overlay .dts + two git
commits are the device-facing outputs; the sidecar is for tooling
and idempotency only.questions.json — Q-1..Q-8 prompt schema
consumed by Step 2.../../scripts/pin_verifier.py
— shared HSIO pin verifier (Step 4).../../references/platform_template.yaml
— documents: block consumed by Step 1.../../context/bsp-customization-workflow.md
— overlay edit protocol (batched pristine + customization commit).../jetson-customize-uphy/SKILL.md — sibling
skill that owns UPHY lane allocation. Must run before this skill to
set uphy1-config-N for MGBE-allocated configurations.../jetson-customize-pinmux/SKILL.md —
sibling skill invoked by Step 4 (with operator confirmation) to
fix pin SFIO mismatches.../jetson-derive-carrier/SKILL.md
— must run first; produces the carrier flash-conf fork edited in
Step 5 and the carrier base overlay this skill orders after.../jetson-init-source/SKILL.md —
produces the overlay tracker + bsp_sources repo this skill commits
into.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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`.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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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