Perceptron Learning for Reuse Prediction

时间 2020-12-31

标签 preceptron LLC cache block reuse prediction 繁體版

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Perceptron Learning for Reuse Prediction 论文的主要贡献：通过结合多种特征作为输入，感知器学习可以大大的改善 cache block reuse预测基于感知器的预测结果可以用于帮助cache的replacement和bypass优化基于感知器学习的cache管理策略会比更大一倍的基于LRU的cache 更高效感知器学习在微体系结构中的应用：最早的感

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1. Octave implementation for Programming Assignment 1: The perceptron learning algorithm.
2. Automatically Learning Semantic Features for Defect Prediction
3. Perceptron Learning Algorithm
4. LC-RNN: A Deep Learning Model for Traffic Speed Prediction
5. Learning Discriminative Model Prediction for Tracking --- 论文翻译
6. Learning Informative Edge Maps for Indoor Scene Layout Prediction
7. Model-Reuse Attacks on Deep Learning Systems
8. Java Design Patterns for Reuse
9. Perceptron Learning Algorithm(python实现)
10. [Reinforcement Learning] Model-Free Prediction

>>更多相关文章<<