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Compiler Optimization

Machine learning guided compiler optimization

Papers

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Showing 1–25 of 45 papers

TitleStatusHype
Compiler Optimization via LLM Reasoning for Efficient Model ServingCode2
Bridging the PLC Binary Analysis Gap: A Cross-Compiler Dataset and Neural Framework for Industrial Control SystemsCode1
Accelerating Large Language Models through Partially Linear Feed-Forward Network—0
Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey—0
Automated Strategy Invention for Confluence of Term Rewrite Systems—0
Optimizing Tensor Computation Graphs with Equality Saturation and Monte Carlo Tree Search—0
Meta Large Language Model Compiler: Foundation Models of Compiler Optimization—0
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization—0
Optimization of Armv9 architecture general large language model inference performance based on Llama.cppCode0
Automated Creation of Source Code Variants of a Cryptographic Hash Function Implementation Using Generative Pre-Trained Transformer Models—0
Offline Imitation Learning from Multiple Baselines with Applications to Compiler Optimization—0
Compiler generated feedback for Large Language Models—0
Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning—0
WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language ModelsCode1
Large Language Models for Compiler Optimization—0
Target-independent XLA optimization using Reinforcement Learning—0
AMULET: Adaptive Matrix-Multiplication-Like Tasks—0
Tensor Slicing and Optimization for Multicore NPUs—0
Robust Scheduling with GFlowNets—0
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction—0
oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation—0
Compiler Optimization for Quantum Computing Using Reinforcement LearningCode1
BaCO: A Fast and Portable Bayesian Compiler Optimization FrameworkCode1
Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration—0
NEON: Enabling Efficient Support for Nonlinear Operations in Resistive RAM-based Neural Network Accelerators—0
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