Doca Sha

DOCA SHA

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 TASKS.md if the user wants to do something (configure / build / modify / run / test / debug); open CAPABILITIES.md 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 CAPABILITIES.md ## Capabilities and modes is the first stop.

Example questions this skill answers well

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.

• "Should I offload this hash to DOCA SHA, or just compute it on the CPU?" — worked example: "I am verifying file integrity on a 4 GiB image; is doca-sha worth the setup vs OpenSSL on the CPU?". Answered by the path-selection table in CAPABILITIES.md ## Capabilities and modes
  • the "when NOT to use doca-sha" bullets in CAPABILITIES.md ## Safety policy.
• "Does my device support the SHA algorithm I want?" — worked example: "is SHA-256 in the accelerator on this BlueField, and what is the minimum destination buffer size for it?". Answered by the algorithm + buffer-sizing capability-query rule (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 CAPABILITIES.md ## Capabilities and modes
  • the discovery step in TASKS.md ## configure.
• "How do I pick between the one-shot and the partial / incremental hash task?" — worked example: "my input is 1 GiB and the device cap says max source buffer is 64 MiB". Answered by the one-shot-vs-partial table in CAPABILITIES.md ## Capabilities and modes
  • the task-config workflow in TASKS.md ## modify.
• "What permissions does the source / destination mmap need?" — worked example: "my doca_sha_task_hash returns DOCA_ERROR_NOT_PERMITTED". Answered by the permission matrix in CAPABILITIES.md ## Safety policy
  • the mmap-set-permissions checklist in TASKS.md ## test.
• "Is this DOCA SHA API available on my installed DOCA version?" — worked example: "is doca_sha_task_partial_hash in the DOCA I have installed?". Answered by the version-compatibility overlay in CAPABILITIES.md ## Version compatibility, which cross-links the canonical detection chain in doca-version and adds the SHA-specific "discover, do not assume" bullets.
• "What does this 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 CAPABILITIES.md ## Error taxonomy
  • the layered ladder in TASKS.md ## debug that escalates to doca-debug.

Audience

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 TASKS.md 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.

When to load this skill

Load this skill when the user is doing hands-on DOCA SHA work, in any language. Concretely:

• Initializing a 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().
• Choosing between the one-shot task (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.
• Setting permissions on 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).
• Sizing the destination buffer against doca_sha_cap_get_min_dst_buf_size(devinfo, algorithm) and the source buffer against doca_sha_cap_get_max_src_buf_size(devinfo).
• Checking which SHA algorithm enums (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.
• Validating a digest against a published test vector before pushing bulk input through the accelerator.
• Debugging a 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.
• Designing or extending non-C bindings (Rust, Go, Python, …) that wrap the SHA C ABI — for the lifecycle, permission, capability, and one-shot-vs-partial rules the wrapper must honor.

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.