Doca Sha Offload Engine
NVIDIAOfficialCreated by NVIDIA
- Skill
- Tool integration
- Software development
- Apache-2.0
- Medium risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The DOCA SHA Offload Engine is an OpenSSL ENGINE that enables hardware-accelerated SHA hashing for existing OpenSSL-based applications without requiring source code modifications. It specifically targets one-shot SHA-1, SHA-256, and SHA-512 operations via the EVP_Digest interface. This skill provides guidance on loading the engine, configuring the PCIe address, verifying that offload is active, and determining when hardware acceleration provides a performance benefit over CPU-based hashing.
What it does
- Provides mechanics for loading the engine into OpenSSL pipelines.
- Explains how to configure the engine using the set_pci_addr control command.
- Outlines verification patterns to confirm offload is active versus software fallback.
- Defines the supported SHA algorithms and the engine's behavior for unsupported types.
- Offers guidance on comparing performance between the engine and standard CPU SHA.
- Details the engine-vs-library selection criteria for new versus existing pipelines.
When to use it
- When you need to accelerate SHA hashing in an existing OpenSSL-based application.
- When you want to avoid rewriting code to use the native doca-sha library.
- When you need to verify if your current OpenSSL pipeline is successfully using the DPU hardware.
- When you are evaluating if the message-size of your workload benefits from hardware offload.
- When you need to troubleshoot engine loading or performance issues on a BlueField-2 DPU.
Advantages
- Enables hardware acceleration without modifying existing application source code.
- Integrates seamlessly with standard OpenSSL EVP_Digest workflows.
- Provides clear verification tests to ensure offload is actually occurring.
- Allows for performance optimization by identifying the optimal message-size window.
- Maintains compatibility with standard OpenSSL engine loading mechanisms.
Usage examples
- “How can I offload SHA-256 in my existing OpenSSL application without rewriting it?”
- The agent will guide you through loading the libdoca_sha_offload_engine.so shared object into your OpenSSL pipeline using the engine dynamic interface.
- “How do I verify that my OpenSSL command is actually using the DOCA SHA engine?”
- The agent will instruct you to perform a negative test using an unsupported digest like SHA-224 to ensure the engine does not silently fall back to software.
- “Is the DOCA SHA engine faster than CPU SHA for my 4KB data blocks?”
- The agent will provide the openssl speed comparison pattern to help you measure the performance impact on your specific hardware and workload.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/nvidia/doca-sha-offload-engine/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip doca-sha-offload-engine.zip -d .agents/skills
Documentation by NVIDIA
DOCA SHA Offload Engine
Examples
“Can I offload SHA in an existing OpenSSL pipeline without rewriting?” — this is in scope. Load the engine; do not start a new
doca-shapipeline here.“How do I prove OpenSSL used DOCA SHA, not CPU SHA?” — use the SHA-224 negative test; do not treat a successful digest as proof of offload.
Quick answer (answer from this file)
Device gate first. The DOCA SHA engine exists only on BlueField-2; BlueField-3 has no SHA acceleration engine (public DOCA SHA guide), so there is nothing to offload there: say so and stop.
Load probe:
openssl engine dynamic -pre NO_VCHECK:1 -pre SO_PATH:<engine .so> -pre LOAD -vvv -t -c.Positive test:
openssl dgst -sha256 -engine <engine .so> -engine_impl <file>reports the engine was set.Negative test: an unsupported digest (
-sha224) must fail with the engine selected; it must not silently fall back.Performance: compare
openssl speed -evp sha256with and without the engine (add-async_jobsfor parallelism). Report measured numbers only; never quote numbers from memory.
Instructions
Follow Loading order below. Open the tasks companion for configure / run. Open the capabilities companion for when offload wins and how to verify it. Do not open every companion file.
Where to start: This is a tool skill for the OpenSSL
ENGINE installed by the doca-sha-offload-engine package
under ${DOCA_DIR}/tools/doca_sha_offload_engine/ as
libdoca_sha_offload_engine.so, next to its
engine_readme.md. It is not a CLI —
it is a shared object loaded by an OpenSSL-based
application or by openssl itself, that re-routes SHA-1 /
SHA-256 / SHA-512 (one-shot only, via the EVP_Digest
interface) onto the DOCA SHA hardware path. Open
the tasks companion and start at
## configure for the PCIe-address
configuration and the OpenSSL prerequisites; jump to
## run for the “load the engine and
prove it actually runs” flow. Open
the capabilities companion when the question is
what the engine actually offloads vs falls back to,
when the engine is a perf win vs not, or how to verify
offload actually engaged. If DOCA is not installed yet,
route to doca-setup/SKILL.md first.
If the user is building a new SHA pipeline from scratch
(not wrapping an existing OpenSSL-based one), this skill
is the wrong surface — route to
../../libs/doca-sha/SKILL.md (doca-sha/SKILL.md)
instead.
Example questions this skill answers well
The CLASSES of doca-sha-offload-engine questions this
skill is built to answer, each with one worked example.
The class is the load-bearing piece; the worked example
is one instance.
“I have an existing OpenSSL-based pipeline doing SHA; can I offload the SHA to DOCA without rewriting the app?” — worked example: “the app uses
EVP_DigestInit_ex/EVP_DigestUpdate/EVP_DigestFinal_exagainstEVP_sha256(); can I drop in DOCA-SHA offload via an engine load?”. Answered by the “when this engine is the right surface” rule in the capabilities companionthe engine-load mechanics in the tasks companion.
“Did the engine actually load? Or did OpenSSL just fall back to software SHA?” — worked example: “my
openssl dgstinvocation completed; how do I know DOCA SHA actually did the work and OpenSSL did not silently use the software path?”. Answered by the “prove the engine actually ran” pattern in the capabilities companion (the SHA-224 negative test and the-engine_implflag) + the verification flow in the tasks companion.“For what message-size range is the engine offload a win vs CPU SHA?” — worked example: “my pipeline hashes 4 KB blocks at a time; is the engine a win there, or does the round-trip to DOCA SHA cost more than the CPU hash itself?”. Answered by the message-size-window rule in the capabilities companion
the
openssl speedperf-comparison pattern in the tasks companion.
“What SHA algorithms does the engine actually support — and what happens for the ones it does not?” — worked example: “my pipeline mixes SHA-1, SHA-256, SHA-512, and SHA-224 — what does the engine do for each?”. Answered by the algorithm-coverage matrix in the capabilities companion.
“Should I use this engine, or call doca-sha directly?” — worked example: “I am writing a new service from scratch; does the engine save me work or does it add complexity I do not need?”. Answered by the “engine vs library” selection table in the capabilities companion.
“What OpenSSL versions does the engine require, and what about OpenSSL 3.x's deprecation of the ENGINE API?” — worked example: “my host has OpenSSL 3.0; will the engine still load?”. Answered by the version overlay in the capabilities companion (verified surface: the engine is documented for OpenSSL 1.1.1f on Ubuntu 20.04 and OpenSSL 3.0.2 on Ubuntu 22.04 per the shipped
engine_readme.md).
When to load this skill
Load this skill when the user is — or the agent needs to — deploy the DOCA SHA Offload Engine into an OpenSSL-based pipeline on a host with DOCA installed and a SHA-capable device. Concretely:
Wiring the engine into an existing OpenSSL-based application or
opensslCLI invocation, with the intent of no source-level code changes (or only the minimumENGINE_load_dynamic/ENGINE_by_idblock shown in the shippedengine_readme.md).Verifying the engine actually engaged for the hot-path digests (the “is offload real or did OpenSSL fall back to software” question).
Characterizing the message-size range over which the engine is a perf win vs the CPU
sha1/sha256/sha512paths.Deciding between “adopt the engine” (existing pipeline, minimal change) and “rewrite to doca-sha” (new pipeline, fine-grained control needed).
Do not load this skill for users building a new
SHA-pipeline from scratch — route to
../../libs/doca-sha/SKILL.md (doca-sha/SKILL.md).
Do not load this skill for users wanting algorithms the
engine does not implement (MD5, SHA-3, SHA-224, HMAC-SHA,
streaming/incremental SHA via EVP_DigestUpdate chains
that the engine treats as one-shot only).
What this skill provides
This is a thin loader. Substantive material lives in two companion files:
the capabilities companion — what the engine offloads (verified: one-shot SHA-1, SHA-256, SHA-512 via the OpenSSL
EVP_Digesthigh-level interface), what it does NOT offload (anything else — including SHA-224, MD5, SHA-3, HMAC-SHA, and any chainedEVP_DigestInit_ex/EVP_DigestUpdate/EVP_DigestFinal_expattern that the engine implements by buffering and then calling DOCA SHA in one shot atFinal), the engine-vs-library selection rule, the message-size-window rule for when offload is a perf win, the verified ctrl-cmd surface (set_pci_addr), the version overlay (OpenSSL ≥ 1.1.1; the shippedengine_readme.mddocuments testing on OpenSSL 1.1.1f and 3.0.2; OpenSSL 3.x deprecates the ENGINE API but still supports it via the legacy code path), the layered error taxonomy, the observability surface (the “prove offload engaged” pattern using the SHA-224 negative test and-engine_impl), and the safety overlay.the tasks companion — step-by-step workflows for the in-scope task verbs:
install,configure(PCIe address selection — the engine defaults to03:00.0and exposes theset_pci_addrctrl-cmd),build(none: the package ships the engine pre-built),modify(refuses engine patching; modify the load-time invocation and the PCIe address instead),run(load the engine viaopenssl engine dynamic; the verification pattern; the OpenSSL programmaticENGINE_load_dynamicblock),test(the “prove the engine ran” SHA-224 negative test; theopenssl speedperf comparison; the message-size window characterization),debug(walk the error taxonomy layer by layer),use(the engine-vs-library decision for the user's specific pipeline), plus aDeferred task verbsblock.
The skill assumes a host where DOCA is already installed,
OpenSSL ≥ 1.1.1 is present (libssl-dev or equivalent),
and the deploying user can access the selected DOCA SHA PCIe device. Verify
device visibility and run the engine-load smoke as that same user before
integration; if either fails with a permission error, stop and route to
doca-setup rather than guessing a group, ACL, or sudo policy.
What this skill deliberately does not ship
This skill is agent guidance, not a samples or scripts bundle. It deliberately does not contain — and pull requests should not add:
Pre-written OpenSSL ENGINE application source code beyond the verbatim block in the shipped
engine_readme.md(theENGINE_load_dynamic/ENGINE_by_id/ENGINE_ctrl_cmd_string/ENGINE_init/ENGINE_set_default_digestssequence, cross-referenced into the tasks companion). The shipped readme is the worked example.A
samples/,bindings/, orreference/subtree. This is a thin loader for a shipped shared-object; substantive material lives in the shippedengine_readme.mdand the doca-sha library docs.Performance numbers from agent memory. The message-size-window where the engine wins is device-, firmware-, OpenSSL-version-, and workload-specific. The
openssl speedcomparison pattern in the tasks companion is the way to capture it on the user's actual hardware; quoting a number from memory is the cross-platform failure mode this skill exists to prevent.Wrappers, parsers, or scripts in any language that consume the engine's stdout or the
openssl speedoutput format.
Loading order
Read this skill first to confirm the user's question is in scope (the user actually has an existing OpenSSL-based pipeline and wants to offload to DOCA SHA without code changes; if the user is building from scratch, route to
../../libs/doca-sha/(doca-sha/SKILL.md)).For what the engine offloads vs falls back, the engine-vs-library selection rule, the message-size- window rule, the version overlay, the error taxonomy, the observability surface (and the prove-offload- actually-engaged pattern), and the safety overlay, see the capabilities companion.
For step-by-step workflows —
install,configure,build,modify,run,test,debug,use— see the tasks companion.
Related skills
../../libs/doca-sha/SKILL.md(doca-sha/SKILL.md) — the underlying DOCA SHA library. The engine is a thin OpenSSL-ENGINE wrapper around doca-sha; when the user needs fine-grained control over the SHA task surface (partial-hash, custom buffer permissions, cap-query for unusual message sizes), the library is the right answer. The engine wraps the one-shot task; the library exposes both one-shot and partial- hash perdoca-sha/SKILL.md.doca-version/SKILL.md— the canonical version-detection chain. The engine has a TWO-axis version overlay (DOCA-side and OpenSSL-side); the version skill carries the four-way match rule this skill layers on top of.doca-debug/SKILL.md— the cross-cutting debug ladder. The engine surfaces its own error taxonomy; when the cause is below DOCA (driver, firmware), the taxonomy hands off here.doca-setup/SKILL.md— env preparation, install verification, thelibssl-devinstall path, and the NGC DOCA container path.doca-public-knowledge-map/SKILL.md— routing to the public DOCA SHA documentation set ondocs.nvidia.com/doca/sdk/and to the OpenSSL ENGINE /openssl-engineupstream documentation onopenssl.org.doca-hardware-safety/SKILL.md— the bundle-wide hardware-safety meta-policy. The engine binds to a specific PCIe device; theset_pci_addrctrl is the artifact-specific overlay, but any host-side change underneath (firmware burn, BFB reflash) runs through the meta-policy.
Files
- ATTRIBUTION.mdAdded by AutoGineer927 B
- BENCHMARK.md10.0 KiB
- CAPABILITIES.md21.5 KiB
- LICENSELicence file added by AutoGineer11.2 KiB
- SKILL.md13.7 KiB
- SKILLCARD.yaml2.7 KiB
- TASKS.md18.7 KiB
- evals/evals.json2.6 KiB
- skill-card.md4.7 KiB
- skill.oms.sig5.1 KiB
skill-card.md
Description: <br>
Guides wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1, SHA-256, or SHA-512 (EVP_Digest) onto BlueField-2 DOCA SHA hardware without rewriting against doca-sha, covering engine load mechanics, the SHA-224 negative test that proves offload engaged, the message-size window where offload beats CPU SHA, and engine-vs-library selection. <br>
This skill is ready for commercial/non-commercial use. <br>
Owner
NVIDIA <br>
License/Terms of Use: <br>
Apache 2.0 <br>
Use Case: <br>
Developers and engineers use this skill to offload SHA hashing in existing OpenSSL-based applications or openssl CLI invocations onto DOCA SHA hardware on BlueField-2, verify that offload actually engaged rather than falling back to software, measure where offload outperforms CPU SHA, and decide between the engine and the doca-sha library. <br>
Deployment Geography for Use: <br>
Global <br>
Requirements / Dependencies: <br>
Requires API Key or External Credential: [Not Specified] <br> Credential Type(s): [None identified] <br>
Do not include secrets in prompts/logs/output; use least-privilege credentials; rotate keys as appropriate. <br>
Known Risks and Mitigations: <br>
Risk: Review before execution as proposals could introduce incorrect or misleading guidance into skills. <br> Mitigation: Review and scan skill before deployment. <br>
Reference(s): <br>
CAPABILITIES.md <br>
TASKS.md <br>
Skill Output: <br>
Output Type(s): [Analysis, Shell commands, Configuration instructions] <br> Output Format: [Markdown with inline bash code blocks] <br> Output Parameters: [1D] <br> Other Properties Related to Output: [None] <br>
Evaluation Agents Used: <br>
Claude Code (
aws/anthropic/bedrock-claude-opus-5-5) <br>Codex (
openai/openai/gpt-6.1-sol) <br>
Evaluation Tasks: <br>
4 evaluation tasks (3 positive, 1 negative), one attempt per task, each in an isolated k8s-sandbox pod. <br>
Evaluation Metrics Used: <br>
Reported benchmark dimensions: <br>
Security: Whether the skill is safe to use, checking for unsafe operations, secret leakage, and unauthorized access. <br>
Correctness: Whether the final answer is correct against the reference answer. <br>
Discoverability: Whether the expected skill was loaded when needed and decoys were avoided. <br>
Effectiveness: Whether the skill helped complete the task, as the equal-weight mean of goal completion and expected-workflow adherence. <br>
Efficiency: Whether the skill avoided wasted tool calls and token usage, as the equal-weight mean of tool-call productivity and token efficiency. <br>
Underlying evaluation signals used in this run: <br>
security: Unsafe operations, secret leakage, and unauthorized access. <br>accuracy: Final-answer correctness against the reference answer. <br>skill_execution: Whether the expected skill was selected, decoys were avoided, and the workflow executed. <br>goal_accuracy: Whether the user's goal was achieved. <br>behavior_check: Whether the expected workflow behavior was followed. <br>skill_efficiency: Tool-call productivity. <br>token_efficiency: Actual uncached prompt plus completion token usage. <br>
Evaluation Results: <br>
| Measure | Claude Code (Baseline -> Skill Uplift) | Codex (Baseline -> Skill Uplift) |
|---|---|---|
| Overall | 99.6% (uplift unavailable) | 92.4% (uplift unavailable) |
| Security | 100.0% -> 100.0% (±0.0 points) | 100.0% -> 100.0% (±0.0 points) |
| Correctness | 45.0% -> 100.0% (+55.0 points) | 100.0% -> 100.0% (±0.0 points) |
| Discoverability | 100.0% (uplift unavailable) | 95.0% (uplift unavailable) |
| Effectiveness | 50.0% -> 100.0% (+50.0 points) | 87.5% -> 100.0% (+12.5 points) |
| Efficiency | 97.8% (uplift unavailable) | 66.9% (uplift unavailable) |
Skill Version(s): <br>
c98e456 (source: git SHA, committed 2026-10-28) <br>
Ethical Considerations: <br>
NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal team to ensure this skill meets requirements for the relevant industry and use case and addresses unforeseen product misuse. <br>
(For Release on NVIDIA Platforms Only) <br> Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here. <br>
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
The author says: Requires DOCA SDK installed at /opt/mellanox/doca on Linux (Ubuntu 22.04/24.04 or RHEL/SLES) with a BlueField-2 DPU (not BF-3) attached, plus OpenSSL ≥ 1.1.1 (libssl-dev for ENGINE API callers) on the build host. The engine ships under /opt/mellanox/doca/tools/doca_sha_offload_engine/ as libdoca_sha_offload_engine.so; reads the user's local install via `pkg-config doca-sha` and inspects /opt/mellanox/doca/{lib,include,samples,applications}. The validation steps require a live DOCA install.
Security
What our scanner noticed· Medium risk
- Large base64-encoded blobs
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- NVIDIA
- Publisher
- NVIDIA (Official)
- Source
- NVIDIA/skills · skills/doca-sha-offload-engine · commit fce3cca
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE-APACHE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by NVIDIA or NVIDIA.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download doca-sha-offload-engine.zip