Nova: An End-to-End MLIR Compiler for Deep Learning

arXiv cs.AIAugust 4, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2608.00029v1 Announce Type: new Abstract: The performance of deep learning models at scale relies heavily on how effectively high-level mathematical operations are mapped to underlying physical hardware. While high-level tensor frameworks provide flexible abstractions for model design, their eager execution models inherently lack the whole-graph visibility and granular control over hardware and memory required to maximize physical hardware utilization natively. To bridge this gap, we designed Nova, an automated end-to-end JIT compiler whose defining purpose is to achieve absolute control over this hardware mapping: fusing operations across operation boundaries, optimizing complex memor

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