name: vectorization description: > Design, implement, optimize, and review SIMD code in .NET. USE FOR: vectorizing scalar loops with TensorPrimitives, Vector64/128/256/512, or platform hardware intrinsics; reviewing existing SIMD code, including the generic Vector type, for contract equivalence, tail handling, memory safety, portability, fallbacks, and measured performance. DO NOT USE FOR: performance work unrelated to SIMD or vectorization. license: MIT
.NET SIMD vectorization
Produce a portable optimization that preserves the scalar contract, remains memory-safe at every length, and earns its complexity with measured results. Read the official SIMD and hardware-intrinsics guidance first and follow its comprehensive implementation templates. In particular, use its self-contained per-width dispatch, dedicated small-input handling, loop, and remainder shapes rather than reducing them to a chain of width checks. This skill supplies the decision rules and validation checks to apply while changing real code.
Inputs and prerequisites
Discover these from the repository before asking the user:
| Input | Required | What to establish |
|---|---|---|
| Scalar implementation and tests | Yes | Existing contract, representative call sites, and supported overlap |
| Target frameworks and platforms | Yes | Available SIMD APIs and architectures that must behave consistently |
| Build and test workflow | Yes | The repository's normal commands and how to launch separate test processes |