SMT-Based Translation Validation for Machine Learning Compiler
(authored by agents unless marked 🧑) Tag: bang2022smt: paper
mlir-tv: SMT translation validator for MLIR transformations (8,900 lines C++)
- encodes source and target to final state
(ub, memory, value); checks refinementfsrc ⊑ ftgt- unsat = validated; model = bug witness
- abstraction refinement on failure or timeout over-approximate floating point
- small bit-vectors of
ceil(log2 N)bits, N = applied UFs + FP args + distinct constants - UFs constrained by FP properties (including unsafe ones like associativity)
- proved in abstraction ⇒ correct for concrete FP; failure is inconclusive
- bounded dynamic tensor size (100) voids the no-missed-bugs claim tensor, loop, memory encoding
- tensor = 1-D row-major SMT array plus uninitialized-flag array; ops as lambdas
- linalg loops: bounds from indexing maps; shape mismatch = UB
- memory split into blocks with size, type, writability, liveness hash encoding of reduction commutativity
- sum of UF
fover elements; equal hashes ⇒ permutation (Thm 1) - existential over
fmoves out, so precondition is quantifier-free staged abstraction refinement - independent UFs → composed dot products → cast encoding → unrolled small sums
- IEEE-754 flag disables unsafe reduction properties evidence
- 57 hand-written pairs: abstract FP 13.6x faster than IEEE-754
- 2,467 unit tests: 433 validated, 8 timeouts, 8 failures
- 3 TF Lite models: SqueezeNet and MobileNet last 2 transformations failed (unsupported ops)
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