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Compiler Optimization

Machine learning guided compiler optimization

Papers

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Showing 26–45 of 45 papers

TitleStatusHype
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction—0
oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation—0
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
Leveraging Artificial Intelligence on Binary Code Comprehension—0
SimCLF: A Simple Contrastive Learning Framework for Function-level Binary EmbeddingsCode0
Securing Optimized Code Against Power Side Channels—0
Learning to Combine Instructions in LLVM Compiler—0
Learning to Superoptimize Real-world Programs—0
GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity—0
Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search—0
FOGA: Flag Optimization with Genetic Algorithm—0
MLComp: A Methodology for Machine Learning-based Performance Estimation and Adaptive Selection of Pareto-Optimal Compiler Optimization Sequences—0
Towards Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning—0
Deep Data Flow Analysis—0
Static Neural Compiler Optimization via Deep Reinforcement Learning—0
Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization—0
An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices—0
Toward Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning—0
A Survey on Compiler Autotuning using Machine Learning—0
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