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Compiler Design Programming Languages

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Compiler Design Programming Languages

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Research Frontiers in Machine Learning Compiler Optimization

Application of neural networks and reinforcement learning to predict optimal compiler optimization passes and parameters.

Neural Cost Models for Adaptive Loop Fusion
Learned Tensor Layout Optimization Beyond Polyhedral Bounds
Differentiable Compilation: End-to-End Auto-Tuning Pipelines
Graph Neural Networks for Instruction Selection
Probabilistic Memory Access Pattern Prediction
Multi-Objective Pareto Frontiers in Code Generation
Latent Space Exploration of Compiler Transformation Sequences
Generative Models for Architecture-Specific Kernel Synthesis
Reinforcement Learning for Cross-Device Code Portability
Symbolic Reasoning in ML-Driven Register Allocation

All Compiler Design & Programming Languages PhD categories