Stability & Versioning

This page summarizes which parts of the MIND toolchain are production-stable today and which remain experimental.

Stable

  • Core IR (mind-spec Core v1): The SSA-based core IR defined in mind-spec/spec/v1.0 is locked for compatibility guarantees.
  • Autodiff: Reverse-mode differentiation over the core IR with deterministic gradient IR output.
  • Shapes & broadcasting: Shape inference, static shapes, and broadcasting semantics are fixed for 1.0.
  • Deterministic canonicalization: Canonical forms and rewrite ordering are stable to enable reproducible builds.
  • IR runtime contract (mindc 0.2.5+): The mic@1 textual IR is the stable boundary between mindc and downstream backends. Public API: libmind::ir::load(bytes), libmind::ir::save(module), and the AOT helper libmind::compile_to_mic_text(src, opts). See mind/docs/ir-stability.md.
  • Pratt expression parser (mindc 0.2.5+): Single-dispatch operator-precedence parser for the expression layer; faster than the pre-Phase-10.5 baseline on representative programs. New operators (Phase 11/12) become O(1) inserts to the binding-power table. CI bench-gate enforces a +2% regression cap.

Conditionally Stable

  • MLIR lowering (feature-gated): Available behind compiler feature flags; interfaces may change.
  • Core v1 GPU profile (contract): Device kinds / backend targets, backend-selection error model, and the GPUBackend trait surface are defined and stable when GPU features are enabled.

Experimental

  • Concrete GPU backends: CUDA backend available via Enterprise license. Open-source GPU backends (ROCm, Metal, WebGPU, WebNN) are experimental and in development.
  • Package manager: Design specified in mind-spec; implementation is early. Dependency resolution and registry workflows are not yet finalized.
  • Future ops / extensions: New operators and language extensions will ship behind experimental flags.
Tip: Experimental areas may change without notice; feature flags are required for MLIR lowering. GPU backends require Enterprise license (CUDA) or are in development (ROCm, Metal, WebGPU, WebNN).

References