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Compiler Optimization
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Machine learning guided compiler optimization
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Bridging the PLC Binary Analysis Gap: A Cross-Compiler Dataset and Neural Framework for Industrial Control Systems
Accelerating Large Language Models through Partially Linear Feed-Forward Network
Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
Automated Strategy Invention for Confluence of Term Rewrite Systems
Optimizing Tensor Computation Graphs with Equality Saturation and Monte Carlo Tree Search
Meta Large Language Model Compiler: Foundation Models of Compiler Optimization
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization
Optimization of Armv9 architecture general large language model inference performance based on Llama.cpp
Automated Creation of Source Code Variants of a Cryptographic Hash Function Implementation Using Generative Pre-Trained Transformer Models
Offline Imitation Learning from Multiple Baselines with Applications to Compiler Optimization
Compiler generated feedback for Large Language Models
Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning
WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models
Large Language Models for Compiler Optimization
Target-independent XLA optimization using Reinforcement Learning
AMULET: Adaptive Matrix-Multiplication-Like Tasks
Tensor Slicing and Optimization for Multicore NPUs
Robust Scheduling with GFlowNets
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction
oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation
Compiler Optimization for Quantum Computing Using Reinforcement Learning
BaCO: A Fast and Portable Bayesian Compiler Optimization Framework
Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration
NEON: Enabling Efficient Support for Nonlinear Operations in Resistive RAM-based Neural Network Accelerators
Leveraging Artificial Intelligence on Binary Code Comprehension
SimCLF: A Simple Contrastive Learning Framework for Function-level Binary Embeddings
Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching
Securing Optimized Code Against Power Side Channels
CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN Execution
Learning to Combine Instructions in LLVM Compiler
Learning to Superoptimize Real-world Programs
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research
GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity
Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search
FOGA: Flag Optimization with Genetic Algorithm
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.