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.
Use this skill when the user is doing hands-on DOCA SHA programming — offloading SHA-1, SHA-256, or SHA-512 hashing onto a BlueField DPU or ConnectX accelerator, picking between one-shot `doca_sha_task_hash` and incremental `doca_sha_task_partial_hash`, querying `doca_sha_cap_*` for algorithm support and min destination / max source buffer sizes, setting source / destination `doca_mmap` permissions, or decoding DOCA_ERROR_* returns from the SHA API. Trigger even when the user does not explicitly mention "DOCA SHA" or "doca_sha_task" — typical implicit phrasings include "hash a multi-GiB file on the DPU", "offload SHA-256 to the BlueField", "streaming hash over chunks", "partial hash returns BAD_STATE", "destination buffer too small for digest", or "is SHA-512 available on this card". Refuse and route elsewhere for general cryptographic-hash theory (collision resistance, SHA-3 selection), other DOCA crypto libraries (AES-GCM, Compress, DMA), or DOCA install / BFB bring-up — those belong to other skills.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
doca_sha_cap_* before picking SHA-1 /
SHA-256 / SHA-512.doca_sha_task_partial_hash lifecycle; do not switch to a CPU
hash library mid-stream.Follow Loading order below. Open the tasks companion for configure / build / run. Open the capabilities companion for one-shot vs partial hash and algorithm support. Do not open every companion file.
Where to start: This skill assumes DOCA is already installed and
the user is doing hands-on SHA-acceleration work on a BlueField
/ ConnectX / host with DOCA. Open the tasks companion if the user
wants to do something (configure / build / modify / run / test /
debug); open the capabilities companion when the question
is what can DOCA SHA express on this version. If the user has not
installed DOCA yet, route to
doca-setup first. If the user is
asking "should I even use the accelerator for this hash?", the
path-selection rule in
is the first stop.
How to use this skill. Read this file, then search the companion file
for the ## <name> heading the question needs and read that whole section.
Answer completely from it, quoting only its symbols and commands. Do not
browse docs; use the entry points in doca-public-knowledge-map. Give
environment checks as commands for the user's DOCA host. For out-of-scope
requests, name the skill that owns them and stop.
The CLASSES of DOCA SHA questions this skill is built to answer, each with one worked example. The agent should treat the class as the load-bearing piece — the worked example is a single instance.
doca_sha_cap_task_hash_get_supported(devinfo, algorithm)
for the one-shot path; _task_partial_hash_get_supported(devinfo, algorithm)
for the partial-hash path; doca_sha_cap_get_min_dst_buf_size,
doca_sha_cap_get_max_src_buf_size) in
doca_sha_task_hash returns
DOCA_ERROR_NOT_PERMITTED". Answered by the permission matrix
in ## Safety policy
doca_sha_task_partial_hash in the DOCA
I have installed?". Answered by the version-compatibility
overlay in
doca-version and adds the
SHA-specific "discover, do not assume" bullets.DOCA_ERROR_* from a SHA call mean and which
layer caused it?" — worked example: "DOCA_ERROR_INVALID_VALUE
on doca_sha_task_hash_alloc_init". Answered by the SHA overlay
on the cross-library taxonomy in
doca-debug.This skill serves external developers building applications that
consume the DOCA SHA library — i.e., users whose code calls
doca_sha_* (directly in C/C++, or through FFI/bindings from
another language) to offload SHA hashing onto a BlueField DPU or
ConnectX accelerator. It is not for NVIDIA developers contributing
to DOCA SHA itself.
Language scope. DOCA SHA ships as a C library with pkg-config
module name doca-sha. The shipped samples are written in C. C and
C++ consumers are the canonical case and the worked examples in
the tasks companion assume that path. Other-language consumers (Rust, Go,
Python, …) consume the same *.so through FFI or language-specific
bindings; the skill's contribution in that case is to keep the
lifecycle, capability-discovery, permission, error-taxonomy, and
one-shot-vs-partial guidance language-neutral, and to route the
agent to the public C ABI as the authoritative surface that any
wrapper will eventually call.
Load this skill when the user is doing hands-on DOCA SHA work, in any language. Concretely:
doca_sha context on a doca_dev and configuring
at least one task type (doca_sha_task_hash and/or
doca_sha_task_partial_hash) before doca_ctx_start().doca_sha_task_hash —
input fits in a single source buffer, output digest lands in a
single destination buffer) and the partial / incremental task
(doca_sha_task_partial_hash — input streamed in chunks, finalized
separately) for the user's data shape.doca_mmap correctly for the source buffer
(DOCA_ACCESS_FLAG_LOCAL_READ_ONLY at minimum) and the destination
buffer (DOCA_ACCESS_FLAG_LOCAL_READ_WRITE).doca_sha_cap_get_min_dst_buf_size(devinfo, algorithm) and
the source buffer against
doca_sha_cap_get_max_src_buf_size(devinfo).DOCA_SHA_ALGORITHM_SHA1, DOCA_SHA_ALGORITHM_SHA256,
DOCA_SHA_ALGORITHM_SHA512) the active device's accelerator
advertises, via
doca_sha_cap_task_hash_get_supported(devinfo, algorithm) and
doca_sha_cap_task_partial_hash_get_supported(devinfo, algorithm) —
both fold task-support and algorithm-support into one call.DOCA_ERROR_* returned from a SHA call (lifecycle vs.
buffer-sizing vs. permission vs. unsupported-algorithm) and the
task-completion event on the progress engine.Do not load this skill for general DOCA orientation, install of
DOCA itself, non-SHA hashing libraries on CPU (use OpenSSL or
similar), or other DOCA libraries. For those, use
doca-public-knowledge-map.
This is a thin loader. The body keeps only the orientation needed to pick the right next file. The substantive SHA-specific material lives in two companion files:
doca_sha_cap_* for algorithm support and buffer sizing), the
SHA error taxonomy (mapped onto the cross-library DOCA_ERROR_*
set), the observability surface (per-task completion events on
the progress engine), the safety policy that gates source /
destination mmap permission decisions, and the path-selection
rule (when to use doca-sha versus a CPU hash or a different
DOCA crypto library).configure, build, modify, run, test, debug.
Plus a Deferred task verbs block that points out-of-scope
questions at the right next skill.The skill assumes a host or BlueField where DOCA is already
installed at the standard location and the user has the privileges
their public install profile expects. It does not cover installing
DOCA — that path goes through
doca-setup.
This skill is agent guidance, not a samples or templates bundle. To keep the boundary clean, it deliberately does not contain — and pull requests should not add:
/opt/mellanox/doca/samples/doca_sha/, plus the File Integrity
reference application linked from the public DOCA SHA guide. The
agent's job is to route the user to those files and prescribe a
minimum-diff modification on them via the universal
modify-a-sample workflow in
doca-programming-guide,
layered with the SHA-specific overrides in
a input) as the known-vector smoke; it does not ship a
vector bank of its own.meson.build, CMakeLists.txt,
Cargo.toml, …) parked inside the skill. The agent constructs
the build manifest in the user's project directory against the
user's installed DOCA, where pkg-config --modversion doca-sha
is the source of truth.samples/, bindings/, or reference/ subtree of any
kind. A mock or incomplete artifact in this skill's tree, even
one labeled "reference", is misleading: users will read it as
buildable.Both companion files cross-link to each other,
doca-version for the canonical
version-handling rules, and
doca-public-knowledge-map
whenever the right answer is "look it up in the public docs or the
installed package layout" rather than "SHA-specific guidance".
doca-public-knowledge-map —
the routing table for every public DOCA documentation source and
the on-disk layout of an installed DOCA package. The DOCA SHA
page lives at docs.nvidia.com/doca/sdk/DOCA-SHA/; the File
Integrity reference application is the canonical worked example.doca-setup — env preparation,
install verification, and the I have no install yet path with
the public NGC DOCA container. This skill assumes its
preconditions are satisfied.doca-version — canonical DOCA
version-handling rules. This skill's
## Version compatibility
cross-links the four-way match rule and adds only the SHA-specific
"discover algorithms + buffer sizes via cap query" overlay.doca-structured-tools-contract —
the bundle's structured-tools precedence rule (detect / prefer
/ fall back / report). The Command appendix in
the tasks companion honors this contract.doca-programming-guide —
general DOCA programming patterns shared by every library: the
canonical pkg-config + meson build pattern, the universal
modify-a-shipped-sample first-app workflow, the universal
lifecycle, the cross-library DOCA_ERROR_* taxonomy, and the
program-side debug order. This skill layers SHA specifics on
top.doca-debug — the cross-cutting
debug ladder (install / version / build / link / runtime /
program / driver). SHA-specific debug (algorithm-not-supported,
destination-buffer-too-small, partial-hash-out-of-order) overlays
on top of that ladder.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.