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PopPy combines an ahead-of-time compiler with a runtime, addressing three key challenges in extracting parallelism from Python applications: language complexity, dynamic dispatch, and variable mutation.
This work introduces Gremlin, a system for generating adversarial benchmarks of queries with high headroom, and applies Bayesian optimization to search the joint space of queries and witness plans, seeking query-plan pairs that maximize headroom.
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