What problem does it solve?
Developers offloading Reed-Solomon erasure coding to BlueField DPUs or ConnectX NICs face a complex configuration surface: choosing among create/recover/update tasks, sizing N+K layouts and block sizes against device capabilities, setting correct mmap permissions, and interpreting DOCA_ERROR_* failures. This Skill gives an AI agent the structured guidance to walk those decisions correctly against the user's actual installed DOCA version and hardware.
Core Features & Use Cases
- Task-type and path selection: Distinguishes create (encode N data blocks into K parity), recover (reconstruct up to K missing blocks), and update (cheap incremental parity refresh when one block changes), and tells the agent when erasure coding is the wrong primitive entirely (pure replication, non-Reed-Solomon codes, network FEC).
- Capability-driven configuration: Enforces querying doca_ec_cap_* functions (task support, max block size, max buffer list length, matrix variants) before committing matrix type, N, K, or block size, preventing hallucinated API assumptions.
- Error taxonomy and debug ladder: Maps DOCA_ERROR_* returns (BAD_STATE, INVALID_VALUE, NOT_SUPPORTED, NOT_PERMITTED, AGAIN, DRIVER) to EC-specific root causes with a layered debug workflow.
- Use Case: A developer building a distributed object store asks "one data block changed, how do I refresh parity without re-encoding?" The agent routes to doca_ec_task_update instead of a wasteful full re-encode, verifies device support, and prescribes a known-vector recover smoke test before bulk data flows.
Quick Start
Ask your agent to help configure a doca_ec context with create and recover tasks for an 8+4 RAID-style layout on your BlueField DPU and verify device capabilities first.