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This work argues that the fix is to change the generation target: instead of asking an LLM to emit dialect-specific SQL, it has it emit a dialect-agnostic relational algebra query plan, which a deterministic compiler then renders into SQL for any supported backend.
This work targets the middle ground between per-operator hand-written kernels and bespoke implementations synthesized for an entire workload or execution engine, and finds that strong code models can often generate buildable and equivalent fused Triton kernels, and that these kernels can improve end-to-end runtime when...
DataKernelBench is introduced, which translates SQL into validated PyTorch TorchPlan programs and evaluates LLMs that optimize either the core tensor-bounded snippet or the full query in CUDA or Triton through execution-guided repair and finds that higher-performing implementations commonly use kernel fusion and execut...
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