bibliography.bib

@inproceedings{alam2019,
  title = {A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions},
  author = {Alam, Mejbah and Gottschlich, Justin and Tatbul, Nesime and Turek, Javier S and Mattson, Tim and Muzahid, Abdullah},
  booktitle = {Advances in Neural Information Processing Systems 32},
  pages = {11627--11639},
  year = {2019},
  publisher = {Curran Associates, Inc.},
  annote = {CATEGORY=Computer Architecture,Performance Counters;TYPE=Anomaly Detection;STRATEGIES=Autoencoders},
}

@incollection{chen2018,
  title = {Learning to Optimize Tensor Programs},
  author = {Chen, Tianqi and Zheng, Lianmin and Yan, Eddie and Jiang, Ziheng and Moreau, Thierry and Ceze, Luis and Guestrin, Carlos and Krishnamurthy, Arvind},
  booktitle = {Advances in Neural Information Processing Systems 31},
  pages = {3389--3400},
  year = {2018},
  publisher = {Curran Associates, Inc.},
  annote = {CATEGORY=Compilers,Optimizations;TYPE=Optimization;STRATEGIES=Supervised Learning,Transfer Learning,Gradient Boosted Trees,TreeGRU},
}

@inproceedings{delimitrou2013,
  title = {Paragon: QoS-Aware Scheduling for Heterogeneous Datacenters},
  author = {Delimitrou, Christina and Kozyrakis, Christos},
  year = {2013},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  booktitle = {Proceedings of the Eighteenth International Conference on Architectural Support for Programming Languages and Operating Systems},
  pages = {77-–88},
  numpages = {12},
  location = {Houston, Texas, USA},
  series = {ASPLOS '13}
  annote = {CATEGORY=Computer Systems,Scheduling;TYPE=Extrapolation;STRATEGIES=Collaborative Filtering},
}

@inproceedings{delimitrou2014,
  title = {Quasar: Resource-Efficient and QoS-Aware Cluster Management},
  author = {Delimitrou, Christina and Kozyrakis, Christos},
  year = {2014},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  booktitle = {Proceedings of the 19th International Conference on Architectural Support for Programming Languages and Operating Systems},
  pages = {127-–144},
  numpages = {18},
  location = {Salt Lake City, Utah, USA},
  series = {ASPLOS '14},
  annote = {CATEGORY=Computer Systems,Scheduling;TYPE=Extrapolation;STRATEGIES=Collaborative Filtering},
}

@inproceedings{feng2019,
  title = {PES: Proactive Event Scheduling for Responsive and Energy-Efficient Mobile Web Computing},
  author = {Feng, Yu and Zhu, Yuhao},
  year = {2019},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  booktitle = {Proceedings of the 46th International Symposium on Computer Architecture},
  pages = {66--78},
  numpages = {13},
  location = {Phoenix, Arizona},
  series = {ISCA '19},
  annote = {CATEGORY=Computer Systems,Scheduling;TYPE=Forecasting;STRATEGIES=Logistic Regression},
}

@inproceedings{hashemi2018,
  title = {Learning Memory Access Patterns},
  author = {Hashemi, Milad and Swersky, Kevin and Smith, Jamie and Ayers, Grant and Litz, Heiner and Chang, Jichuan and Kozyrakis, Christos and Ranganathan, Parthasarathy},
  booktitle = {Proceedings of the 35th International Conference on Machine Learning},
  pages = {1919--1928},
  year = {2018},
  volume = {80},
  series = {Proceedings of Machine Learning Research},
  address = {Stockholmsmässan, Stockholm Sweden},
  month = {10--15 Jul},
  publisher = {PMLR},
  annote = {CATEGORY=Computer Architecture,Speculation;TYPE=Forecasting;STRATEGIES=Supervised Learning,LSTMs,Clustering},
}

@inproceedings{jimenez2001,
  title = {Dynamic branch prediction with perceptrons},
  author = {Jimenez, Daniel A. and Lin, Calvin},
  booktitle = {Proceedings HPCA Seventh International Symposium on High-Performance Computer Architecture},
  year = {2001},
  pages = {197-206},
  annote = {CATEGORY=Computer Architecture,Speculation;TYPE=Forecasting;STRATEGIES=Supervised Learning,Perceptrons},
}

@misc{kaufman2020,
  title = {A Learned Performance Model for the Tensor Processing Unit},
  author = {Samuel J. Kaufman and Phitchaya Mangpo Phothilimthana and Yanqi Zhou and Mike Burrows},
  year = {2020},
  eprint = {2008.01040},
  archivePrefix = {arXiv},
  primaryClass = {cs.PF},
  annote = {CATEGORY=Compilers,Performance Models;TYPE=Extrapolation,Forecasting;STRATEGIES=Supervised Learning,Graph Neural Networks},
}

@inproceedings{kraska2018,
  title = {The Case for Learned Index Structures},
  author = {Kraska, Tim and Beutel, Alex and Chi, Ed H. and Dean, Jeffrey and Polyzotis, Neoklis},
  year = {2018},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  booktitle = {Proceedings of the 2018 International Conference on Management of Data},
  pages = {489-–504},
  numpages = {16},
  location = {Houston, TX, USA},
  annote = {CATEGORY=Databases,Index Structures;TYPE=Forecasting;STRATEGIES=Supervised Learning,Neural Networks},
}

@inproceedings{lujing2020,
  title = {Learned Garbage Collection},
  author = {Cen, Lujing and Marcus, Ryan and Mao, Hongzi and Gottschlich, Justin and Alizadeh, Mohammad and Kraska, Tim},
  year = {2020},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  booktitle = {Proceedings of the 4th ACM SIGPLAN International Workshop on Machine Learning and Programming Languages},
  pages = {38–-44},
  numpages = {7},
  location = {London, UK},
  annote = {CATEGORY=Language Runtime Systems,Memory Management;TYPE=Discovery;STRATEGIES=Reinforcement Learning},
}

@inproceedings{maas2020,
  title = {Learning-Based Memory Allocation for C++ Server Workloads},
  author = {Maas, Martin and Andersen, David G. and Isard, Michael and Javanmard, Mohammad Mahdi and McKinley, Kathryn S. and Raffel, Colin},
  year = {2020},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  booktitle = {Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems},
  pages = {541--556},
  numpages = {16},
  location = {Lausanne, Switzerland},
  series = {ASPLOS ’20}
  annote = {CATEGORY=Language Runtime Systems,Memory Management;TYPE=Extrapolation,Forecasting;STRATEGIES=Supervised learning,LSTMs},
}

@inproceedings{mao2019,
  title = {Learning Scheduling Algorithms for Data Processing Clusters},
  author = {Mao, Hongzi and Schwarzkopf, Malte and Venkatakrishnan, Shaileshh Bojja and Meng, Zili and Alizadeh, Mohammad},
  year = {2019},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  booktitle = {Proceedings of the ACM Special Interest Group on Data Communication},
  pages = {270–-288},
  numpages = {19},
  location = {Beijing, China},
  series = {SIGCOMM '19},
  annote = {CATEGORY=Computer Systems,Scheduling;TYPE=Discovery;STRATEGIES=Reinforcement Learning},
}

@inproceedings{mendis2019,
  title = {Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks},
  author = {Mendis, Charith and Renda, Alex and Amarasinghe, Saman and Carbin, Michael},
  year = {2019},
  pages = {4505--4515},
  booktitle = {ICML},
  annote = {CATEGORY=Compilers,Performance Models;TYPE=Extrapolation,Forecasting;STRATEGIES=Supervised Learning,LSTMs},
}

@incollection{mendis2019b,
  title = {Compiler Auto-Vectorization with Imitation Learning},
  author = {Mendis, Charith and Yang, Cambridge and Pu, Yewen and Amarasinghe, Dr.Saman and Carbin, Michael},
  booktitle = {Advances in Neural Information Processing Systems 32},
  pages = {14625--14635},
  year = {2019},
  publisher = {Curran Associates, Inc.},
  annote = {CATEGORY=Compilers,Optimizations;TYPE=Discovery,Optimization;STRATEGIES=Imitation Learning,Graph Neural Networks},
}

@inproceedings{mirhoseini2017,
  title = {Device Placement Optimization with Reinforcement Learning},
  author = {Mirhoseini, Azalia and Pham, Hieu and Le, Quoc V. and Steiner, Benoit and Larsen, Rasmus and Zhou, Yuefeng and Kumar, Naveen and Norouzi, Mohammad and Bengio, Samy and Dean, Jeff},
  year = {2017},
  publisher = {JMLR.org},
  booktitle = {Proceedings of the 34th International Conference on Machine Learning - Volume 70},
  pages = {2430–-2439},
  numpages = {10},
  location = {Sydney, NSW, Australia},
  series = {ICML'17}
  annote = {CATEGORY=Computer Systems,Scheduling;TYPE=Optimization;STRATEGIES=Reinforcement Learning,LSTMs},
}

@misc{mirhoseini2020,
  title = {Chip Placement with Deep Reinforcement Learning},
  author = {Azalia Mirhoseini and Anna Goldie and Mustafa Yazgan and Joe Jiang and Ebrahim Songhori and Shen Wang and Young-Joon Lee and Eric Johnson and Omkar Pathak and Sungmin Bae and Azade Nazi and Jiwoo Pak and Andy Tong and Kavya Srinivasa and William Hang and Emre Tuncer and Anand Babu and Quoc V. Le and James Laudon and Richard Ho and Roger Carpenter and Jeff Dean},
  year = {2020},
  eprint = {2004.10746},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG}
  annote = {CATEGORY=Computer Architecture,Hardware Design;TYPE=Optimization;STRATEGIES=Reinforcement Learning},
}

@inproceedings{song2020,
  title = {Learning Relaxed Belady for Content Distribution Network Caching},
  author = {Zhenyu Song and Daniel S. Berger and Kai Li and Wyatt Lloyd},
  booktitle = {17th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 20)},
  address = {Santa Clara, CA},
  pages = {529--544},
  publisher = {{USENIX} Association},
  annote = {CATEGORY=Computer Systems,Storage Systems;TYPE=Discovery;STRATEGIES=Imitation Learning},
}

@inproceedings{yu2019,
  title = {Seer: Leveraging Big Data to Navigate the Complexity of Performance Debugging in Cloud Microservices},
  author = {Gan, Yu and Zhang, Yanqi and Hu, Kelvin and Cheng, Dailun and He, Yuan and Pancholi, Meghna and Delimitrou, Christina},
  year = {2019},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  booktitle = {Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems},
  pages = {19–-33},
  numpages = {15},
  location = {Providence, RI, USA},
  series = {ASPLOS '19},
  annote = {CATEGORY=Computer Systems,Distributed Systems;TYPE=Anomaly Detection;STRATEGIES=Supervised learning,LSTMS},
}

@inproceedings{zongheng2019,
  title = {Deep Unsupervised Cardinality Estimation},
  author = {Yang, Zongheng and Liang, Eric and Kamsetty, Amog and Wu, Chenggang and Duan, Yan and Chen, Xi and Abbeel, Pieter and Hellerstein, Joseph M. and Krishnan, Sanjay and Stoica, Ion},
  year = {2019},
  issue_date = {November 2019},
  publisher = {VLDB Endowment},
  volume = {13},
  number = {3},
  journal = {Proc. VLDB Endow.},
  pages = {279-–292},
  numpages = {14}
  annote = {CATEGORY=Databases,Query Optimization;TYPE=Forecasting;STRATEGIES=Autoregressive Models},
}

@inproceedings{zhou2019,
  title = {Multi-Task Learning for Storage Systems},
  author = {Giulio Zhou and Martin Maas},
  booktitle = {Workshop on ML for Systems at NeurIPS 2019},
  address = {Vancouver, Canada},
  annote = {CATEGORY=Computer Systems,Storage Systems;TYPE=Extrapolation;STRATEGIES=Supervised learning,Transformers,Multi-Task Learning}
}