Список литературы

Список работ, на которые ссылаются главы книги. Записи приведены на языке оригинала.

Abadi, M., Chu, A., Goodfellow, I., McMahan, H. B., Mironov, I., Talwar, K., Zhang, L. (2016). Deep Learning With Differential Privacy. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security.
Adi, Yossi, Baum, Carsten, Cisse, Moustapha, Pinkas, Benny, Keshet, Joseph (2018). Turning your weakness into a strength: Watermarking deep neural networks by backdooring. 27th USENIX Security Symposium (USENIX Security 18).
Agrawal, Amey, Kedia, Nitin, Panwar, Ashish, Mohan, Jayashree, Kwatra, Nipun, Gulavani, Bhargav S., Tumanov, Alexey, Ramjee, Ramachandran (2024). Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve. 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI 24), 117–134.
Ainslie, Joshua, Lee-Thorp, James, de Jong, Michiel, Zemlyanskiy, Yury, Lebron, Federico, Sanghai, Sumit (2023). GQA: Training Generalized Multi-Query Transformer Models From Multi-Head Checkpoints. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing.
Aizman, Alex, Maltby, Gavin, Breuel, Thomas (2019). High Performance I/O for Large Scale Deep Learning. 2019 IEEE International Conference on Big Data (Big Data).
Aji, Alham Fikri, Heafield, Kenneth (2017). Sparse Communication for Distributed Gradient Descent. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing.
Akidau, Tyler, Bradshaw, Robert, Chambers, Craig, Chernyak, Slava, Fernández-Moctezuma, Rafael J., Lax, Reuven, McVeety, Sam, Mills, Daniel, Perry, Frances, Schmidt, Eric, Whittle, Sam (2015). The dataflow model. Proceedings of the VLDB Endowment.
Al-Fares, Mohammad, Loukissas, Alexander, Vahdat, Amin (2008). A scalable, commodity data center network architecture. ACM SIGCOMM Computer Communication Review.
Alexandrov, Albert D., Ionescu, Mihai F., Schauser, Klaus E., Scheiman, Chris J. (1995). LogGP: Incorporating long messages into the LogP model—one step closer towards a realistic model for parallel computation. Proceedings of the seventh annual ACM symposium on Parallel algorithms and architectures - SPAA ’95.
Alistarh, Dan, Grubic, Demjan, Li, Jerry Z., Tomioka, Ryota, Vojnovic, Milan (2017). QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding. Advances in Neural Information Processing Systems (NeurIPS).
Alizadeh, Mohammad, Greenberg, Albert, Maltz, David A., Padhye, Jitendra, Patel, Parveen, Prabhakar, Balaji, Sengupta, Sudipta, Sridharan, Murari (2010). Data Center TCP (DCTCP). Proceedings of the ACM SIGCOMM 2010 Conference.
Amazon Web Services (2017). Summary of the Amazon S3 Service Disruption in the Northern Virginia (US-EAST-1) Region. AWS service event summary.
Amazon Web Services (2020). Amazon S3 Update – Strong Read-After-Write Consistency. AWS News Blog.
Amazon Web Services (2026). Checking Object Integrity in Amazon S3. Amazon S3 User Guide.
Amazon Web Services (2026). Managing the Lifecycle of Objects. Amazon S3 User Guide.
Amazon Web Services (2026). Naming Amazon S3 objects. Amazon S3 User Guide.
Amazon Web Services (2026). Understanding Archive Retrieval Options. Amazon S3 User Guide.
Amdahl, Gene M. (1967). Validity of the single processor approach to achieving large scale computing capabilities. Proceedings of the April 18-20, 1967, spring joint computer conference on - AFIPS ’67 (Spring).
Amershi, Saleema, Begel, Andrew, Bird, Christian, DeLine, Robert, Gall, Harald, Kamar, Ece, Nagappan, Nachiappan, Nushi, Besmira, Zimmermann, Thomas (2019). Software Engineering for Machine Learning: A Case Study. 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP).
Amiel, Frederic, Clavier, Christophe, Tunstall, Michael (2006). Fault Analysis of DPA-Resistant Algorithms. Fault Diagnosis and Tolerance in Cryptography.
Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J., Mane, D. (2016). Concrete Problems in AI Safety. arXiv preprint arXiv:1606.06565
Amodei, Dario, Hernandez, Danny (2018). AI and Compute. OpenAI Blog.
Anslow, Pete (2016). RS(544,514) FEC Performance Including Precoding. IEEE P802.3cd Task Force.
Anthony, L., Kanding, B., Selvan, R. (2020). Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models. ICML Workshop on Challenges in Deploying and monitoring Machine Learning Systems.
Antonakakis, M., April, T., Bailey, M., Bernhard, M., Bursztein, E., Cochran, J., et al. (2017). Understanding the mirai botnet. 26th USENIX security symposium (USENIX Security 17).
Apple (2021). Boot process for iPad and iPhone devices. Apple Platform Security.
Apple (2021). Secure software updates. Apple Platform Security.
Apple (2024). Facial matching security. Apple Platform Security.
Apple (2024). The Secure Enclave. Apple Platform Security.
Apple Differential Privacy Team (2017). Learning with privacy at scale. Apple Machine Learning Research
Apple Differential Privacy Team (2017). Learning with privacy at scale. Apple Machine Learning Research.
Arifeen, Tooba, Hassan, Abdus Sami, Lee, Jeong-A (2020). Approximate Triple Modular Redundancy: A Survey. IEEE Access.
Arivazhagan, Manoj Ghuhan, Aggarwal, Vinay, Singh, Aaditya Kumar, Choudhary, Sunav (2019). Federated Learning with Personalization Layers. CoRR.
Ashkboos, Saleh, Mohtashami, Amirkeivan, Croci, Maximilian L., Li, Bo, Cameron, Pashmina, Jaggi, Martin, Alistarh, Dan, Hoefler, Torsten, Hensman, James (2024). QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs. Advances in Neural Information Processing Systems (NeurIPS).
Asonov, Dmitri, Agrawal, Rakesh (2004). Keyboard acoustic emanations. IEEE Symposium on Security and Privacy, 2004. Proceedings. 2004.
Ateniese, G., Mancini, L. V., Spognardi, A., Villani, A., Vitali, D., Felici, G. (2015). Hacking smart machines with smarter ones: How to extract meaningful data from machine learning classifiers. International Journal of Security and Networks.
Avizienis, Algirdas, Laprie, Jean-Claude, Randell, Brian, Landwehr, Carl (2004). Basic Concepts and Taxonomy of Dependable and Secure Computing. IEEE Transactions on Dependable and Secure Computing.
Aygun, Sercan, Gunes, Ece Olcay, De Vleeschouwer, Christophe (2021). Efficient and robust bitstream processing in binarised neural networks. Electronics Letters.
Bahdanau, Dzmitry, Cho, Kyunghyun, Bengio, Yoshua (2015). Neural Machine Translation by Jointly Learning to Align and Translate. International Conference on Learning Representations (ICLR).
Bai, Tao, Luo, Jinqi, Zhao, Jun, Wen, Bihan, Wang, Qian (2021). Recent Advances in Adversarial Training for Adversarial Robustness. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence.
Bai, Yuntao, et al. (2022). Constitutional AI: Harmlessness from AI Feedback.
Baldé, Cornelis, Forti, Vanessa, Gray, Vanessa, Kuehr, Ruediger, Stegmann, Paul (2017). The Global E-Waste Monitor 2017: Quantities, Flows and Resources. United Nations University, International Telecommunication Union, International Solid Waste Association.
Banbury, Colby, Reddi, Vijay Janapa, Torelli, Peter, Holleman, Jeremy, Jeffries, Nat, Kiraly, Csaba, Montino, Pietro, Kanter, David, Ahmed, Sebastian, Pau, Danilo, Thakker, Urmish, Torrini, Antonio, Warden, Peter, Cordaro, Jay, Guglielmo, Giuseppe Di, Duarte, Javier, Gibellini, Stephen, Parekh, Videet, Tran, Honson, Tran, Nhan, Wenxu, Niu, Xuesong, Xu (2021). MLPerf Tiny Benchmark. arXiv preprint.
Bannon, Pete, Venkataramanan, Ganesh, Sarma, Debjit Das, Talpes, Emil (2019). Computer and Redundancy Solution for the Full Self-Driving Computer. 2019 IEEE Hot Chips 31 Symposium (HCS).
Barenghi, A., Bertoni, G. M., Breveglieri, L., Pellicioli, M., Pelosi, G. (2010). Low voltage fault attacks to AES. 2010 IEEE International Symposium on Hardware-Oriented Security and Trust (HOST).
Barocas, Solon, Hardt, Moritz, Narayanan, Arvind (2023). Fairness and Machine Learning: Limitations and Opportunities. MIT Press
Barroso, Luiz André, Hölzle, Urs, Ranganathan, Parthasarathy (2019). The Datacenter as a Computer. Springer International Publishing.
Basiri, A., Behnam, N., Rooij, R., Hochstein, L., Kosewski, L., Reynolds, J., Rosenthal, C. (2016). Chaos Engineering. IEEE Software.
Baumann, R. (2005). Soft Errors in Advanced Computer Systems. IEEE Design and Test of Computers.
Baylor, Denis, Breck, Eric, Cheng, Heng-Tze, Fiedel, Noah, Foo, Chuan Yu, Haque, Zakaria, Haykal, Salem, Ispir, Mustafa, Jain, Vihan, Koc, Levent, Koo, Chiu Yuen, Lew, Lukasz, Mewald, Clemens, Modi, Akshay Naresh, Polyzotis, Neoklis, Ramesh, Sukriti, Roy, Sudip, Whang, Steven Euijong, Wicke, Martin, Wilkiewicz, Jarek, Zhang, Xin, Zinkevich, Martin (2017). TFX. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
Beaton, A., Tukey, J. (1974). The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data. Technometrics.
Bellamy, Rachel K. E., Dey, Kuntal, Hind, Michael, Hoffman, Seung, Houde, Sylvain, Kannan, Karthikeyan, et al. (2019). AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias. IBM Journal of Research and Development, 4:1–4:15
Ben-Nun, Tal, Hoefler, Torsten (2019). Demystifying Parallel and Distributed Deep Learning. ACM Computing Surveys.
Bender, E. M., Gebru, T., McMillan-Major, A., Shmitchell, S. (2021). On the Dangers of Stochastic Parrots. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency.
Bengio, Yoshua, Léonard, Nicholas, Courville, Aaron (2013). Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation. arXiv preprint arXiv:1308.3432.
Berger, Vance W., Zhou, YanYan (2014). Kolmogorov–Smirnov Test: Overview. Wiley StatsRef: Statistics Reference Online.
Bernstein, Jeremy, Wang, Yu-Xiang, Azizzadenesheli, Kamyar, Anandkumar, Animashree (2018). signSGD: Compressed Optimisation for Non-Convex Problems. International Conference on Machine Learning (ICML).
Beyer, Betsy, Jones, Chris, Petoff, Jennifer, Murphy, Niall Richard (2016). Site Reliability Engineering: How Google Runs Production Systems. O’Reilly Media.
Biega, A. J., Potash, P., Daume, H., Diaz, F., Finck, M. (2020). Operationalizing the Legal Principle of Data Minimization for Personalization. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 399–408
Biggio, Battista, Nelson, Blaine, Laskov, Pavel (2012). Poisoning Attacks against Support Vector Machines. Proceedings of the 29th International Conference on Machine Learning, ICML 2012, Edinburgh, Scotland, UK, June 26 - July 1, 2012.
Binkert, Nathan, Beckmann, Bradford, Black, Gabriel, Reinhardt, Steven K., Saidi, Ali, Basu, Arkaprava, Hestness, Joel, Hower, Derek R., Krishna, Tushar, Sardashti, Somayeh, Sen, Rathijit, Sewell, Korey, Shoaib, Muhammad, Vaish, Nilay, Hill, Mark D., Wood, David A. (2011). The gem5 simulator. ACM SIGARCH Computer Architecture News.
Bird, Sarah, Dudík, Miro, Edgar, Richard, Horn, Brandon, Lutz, Roman, Milan, Vanessa, et al. (2020). Fairlearn: A toolkit for assessing and improving fairness in AI. Microsoft Technical Report MSR-TR-2020-32
Birolini, A. (2017). Reliability Engineering. Springer Berlin Heidelberg.
Bisong, E. (2019). Kubeflow and Kubeflow Pipelines. Building Machine Learning and Deep Learning Models on Google Cloud Platform.
Black, James R. (1969). Electromigration–A Brief Survey and Some Recent Results. IEEE Transactions on Electron Devices.
Blanchard, Peva, Mhamdi, El Mahdi El, Guerraoui, Rachid, Stainer, Julien (2017). Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent. Advances in Neural Information Processing Systems (NeurIPS).
Bommasani, Rishi, Hudson, Drew A., Adeli, Ehsan, Altman, Russ, Arora, Simran, Arx, Sydney, Bernstein, Michael S., Bohg, Jeannette, Bosselut, Antoine, Brunskill, Emma, Brynjolfsson, Erik, Buch, Shyamal, Card, Dallas, Castellon, Rodrigo, Chatterji, Niladri, Chen, Annie, Creel, Kathleen, Davis, Jared Quincy, Demszky, Dora, Donahue, Chris, Doumbouya, Moussa, Durmus, Esin, Ermon, Stefano, Etchemendy, John, Ethayarajh, Kawin, Fei-Fei, Li, Finn, Chelsea, Gale, Trevor, Gillespie, Lauren, Goel, Karan, Goodman, Noah, Grossman, Shelby, Guha, Neel, Hashimoto, Tatsunori, Henderson, Peter, Hewitt, John, Ho, Daniel E., Hong, Jenny, Hsu, Kyle, Huang, Jing, Icard, Thomas, Jain, Saahil, Jurafsky, Dan, Kalluri, Pratyusha, Karamcheti, Siddharth, Keeling, Geoff, Khani, Fereshte, Khattab, Omar, Koh, Pang Wei, Krass, Mark, Krishna, Ranjay, Kuditipudi, Rohith, Kumar, Ananya, Ladhak, Faisal, Lee, Mina, Lee, Tony, Leskovec, Jure, Levent, Isabelle, Li, Xiang Lisa, Li, Xuechen, Ma, Tengyu, Malik, Ali, Manning, Christopher D., Mirchandani, Suvir, Mitchell, Eric, Munyikwa, Zanele, Nair, Suraj, Narayan, Avanika, Narayanan, Deepak, Newman, Ben, Nie, Allen, Niebles, Juan Carlos, Nilforoshan, Hamed, Nyarko, Julian, Ogut, Giray, Orr, Laurel, Papadimitriou, Isabel, Park, Joon Sung, Piech, Chris, Portelance, Eva, Potts, Christopher, Raghunathan, Aditi, Reich, Rob, Ren, Hongyu, Rong, Frieda, Roohani, Yusuf, Ruiz, Camilo, Ryan, Jack, Ré, Christopher, Sadigh, Dorsa, Sagawa, Shiori, Santhanam, Keshav, Shih, Andy, Srinivasan, Krishnan, Tamkin, Alex, Taori, Rohan, Thomas, Armin W., Tramèr, Florian, Wang, Rose E., Wang, William, Wu, Bohan, Wu, Jiajun, Wu, Yuhuai, Xie, Sang Michael, Yasunaga, Michihiro, You, Jiaxuan, Zaharia, Matei, Zhang, Michael, Zhang, Tianyi, Zhang, Xikun, Zhang, Yuhui, Zheng, Lucia, Zhou, Kaitlyn, Liang, Percy (2021). On the Opportunities and Risks of Foundation Models. arXiv preprint arXiv:2108.07258.
Bonawitz, K., Eichner, H., Grieskamp, W., Huba, D., Ingerman, A., Ivanov, V., Kiddon, C., Konečný, J., Mazzocchi, S., McMahan, H. B., Overveldt, T. V., Petrou, D., Ramage, D., Roselander, J. (2019). Towards Federated Learning at Scale: System Design. Proceedings of Machine Learning and Systems.
Bonawitz, Keith, Ivanov, Vladimir, Kreuter, Ben, Marcedone, Antonio, McMahan, H. Brendan, Patel, Sarvar, Ramage, Daniel, Segal, Aaron, Seth, Karn (2017). Practical Secure Aggregation for Privacy-Preserving Machine Learning. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security.
Bourtoule, Lucas, Chandrasekaran, Varun, Choquette-Choo, Christopher A., Jia, Hengrui, Travers, Adelin, Zhang, Baiwu, et al. (2021). Machine Unlearning. 2021 IEEE Symposium on Security and Privacy (SP), 141–159
Breier, Jakub, Hou, Xiaolu, Jap, Dirmanto, Ma, Lei, Bhasin, Shivam, Liu, Yang (2018). Practical Fault Attack on Deep Neural Networks. Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security.
Brewer, Eric A. (2000). Towards robust distributed systems (abstract). Proceedings of the nineteenth annual ACM symposium on Principles of distributed computing.
Broadcom Inc. (2025). Broadcom Ships Tomahawk 6: World’s First 102.4 Tbps Switch. Broadcom press release.
Brown, Tom B., Mann, Benjamin, Ryder, Nick, Subbiah, Melanie, Kaplan, Jared, Dhariwal, Prafulla, Neelakantan, Arvind, Shyam, Pranav, Sastry, Girish, Askell, Amanda, Agarwal, Sandhini, Herbert-Voss, Ariel, Krueger, Gretchen, Henighan, Tom, Child, Rewon, Ramesh, Aditya, Ziegler, Daniel M., Wu, Jeffrey, Winter, Clemens, Hesse, Christopher, Chen, Mark, Sigler, Eric, Litwin, Mateusz, Gray, Scott, Chess, Benjamin, Clark, Jack, Berner, Christopher, McCandlish, Sam, Radford, Alec, Sutskever, Ilya, Amodei, Dario (2020). Language Models are Few-Shot Learners. Advances in Neural Information Processing Systems.
Bu, Zhiqi, Dong, Jiawen, Long, Qi, Su, Weijie J. (2020). Deep learning with Gaussian differential privacy. Harvard Data Science Review.
Buolamwini, Joy, Gebru, Timnit (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Conference on fairness, accountability and transparency, 77–91
Burns, Brendan, Grant, Brian, Oppenheimer, David, Brewer, Eric, Wilkes, John (2016). Borg, Omega, and Kubernetes. Communications of the ACM.
Bursztein, Elie, Invernizzi, Luca, Král, Karel, Moghimi, Daniel, Picod, Jean-Michel, Zhang, Marina (2024). Generalized Power Attacks Against Crypto Hardware Using Long-Range Deep Learning. IACR Transactions on Cryptographic Hardware and Embedded Systems.
Bursztein, Elie, Picod, Jean-Michel (2019). A Hacker Guide To Deep Learning Based Side Channel Attacks. DEF CON 27.
Bushnell, Michael L, Agrawal, Vishwani D (2002). Built-In Self-Test. Frontiers in Electronic Testing.
Buyya, Rajkumar, Beloglazov, Anton, Abawajy, Jemal (2010). Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges. arXiv preprint arXiv:1006.0308.
Cai, Han, Gan, Chuang, Wang, Tianzhe, Zhang, Zhekai, Han, Song (2020). Once-for-All: Train One Network and Specialize it for Efficient Deployment. International Conference on Learning Representations (ICLR).
Cai, Han, Gan, Chuang, Zhu, Ligeng, Han, Song (2020). TinyTL: Reduce Activations, Not Trainable Parameters for Efficient On-Device Learning. Advances in Neural Information Processing Systems.
Cai, Han, Zhu, Ligeng, Han, Song (2019). ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware. International Conference on Learning Representations (ICLR).
Cai, Tianle, Li, Yuhong, Geng, Zhengyang, Peng, Hongwu, Lee, Jason D., Chen, Deming, Dao, Tri (2024). Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads. Proceedings of the 41st International Conference on Machine Learning (ICML).
Calders, Toon, Verwer, Sicco (2010). Three naive Bayes approaches for discrimination-free classification. Data Mining and Knowledge Discovery, 277–292
California Legislature (2023). California Consumer Privacy Act of 2018. California Legislative Information
Calvo, Rafael A., Peters, Dorian, Vold, Karina, Ryan, Richard M. (2020). Supporting Human Autonomy in AI Systems: A Framework for Ethical Enquiry. Ethics of digital well-being: A multidisciplinary approach, 31–54
Cao, Yinzhi, Yang, Junfeng (2015). Towards Making Systems Forget With Machine Unlearning. 2015 IEEE Symposium on Security and Privacy, 463–480
Carlini, N., Paleka, D., Dvijotham, K., Steinke, T., Hayase, J., Cooper, A., et al. (2024). Stealing Part of a Production Language Model. arXiv preprint arXiv:2403.06634.
Carlini, N., Tramer, F., Wallace, E., Jagielski, M., Herbert-Voss, A., Lee, K., et al. (2021). Extracting Training Data from Large Language Models. 30th USENIX Security Symposium (USENIX Security 21).
Carlini, Nicholas, Wagner, David (2017). Towards Evaluating the Robustness of Neural Networks. 2017 IEEE Symposium on Security and Privacy (SP).
Caveness, E., G. C., P. S., Peng, Z., Polyzotis, N., Roy, S., Zinkevich, M. (2020). TensorFlow Data Validation: Data Analysis and Validation in Continuous ML Pipelines. Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data.
Cavoukian, A. (2012). Privacy by design. Office of the Information and Privacy Commissioner.
Cenci, Marcelo, Scarazzato, Tatiana, Munchen, Daniel, Dartora, Paula, Veit, Hugo, Bernardes, Andrea, Dias, Pablo (2021). Eco-Friendly Electronics—a Comprehensive Review. Advanced Materials Technologies.
Centre for International Governance Innovation (2023). Who Is Responsible When Autonomous Systems Fail?. CIGI policy article
Cerebras Systems (2021). Wafer-Scale Deep Learning Acceleration with the Cerebras CS-2. Cerebras Technical Paper.
Cerebras Systems (2024). Cerebras Systems, Inc. Registration Statement on Form S-1.
Chandola, Varun, Banerjee, Arindam, Kumar, Vipin (2009). Anomaly Detection. ACM Computing Surveys.
Chapelle, Olivier, Joachims, Thorsten, Radlinski, Filip, Yue, Yisong (2012). Large-scale validation and analysis of interleaved search evaluation. ACM Transactions on Information Systems.
Chen, C., Borgeaud, S., Irving, G., Lespiau, J.-B., Sifre, L., Jumper, J. (2023). Accelerating Large Language Model Decoding with Speculative Sampling. arXiv preprint arXiv:2302.01318.
Chen, H.-W. (2006). Gallium, Indium, and Arsenic Pollution of Groundwater From a Semiconductor Manufacturing Area of Taiwan. Bulletin of Environmental Contamination and Toxicology.
Chen, Liyuan, Ye, Zihao, Wu, Yonghao, Zhuo, Danyang, Ceze, Luis, Krishnamurthy, Arvind (2024). Punica: Multi-Tenant LoRA Serving. Proceedings of the 7th Conference on Machine Learning and Systems (MLSys).
Chen, Tianqi, Xu, Bing, Zhang, Chiyuan, Guestrin, Carlos (2016). Training Deep Nets with Sublinear Memory Cost. arXiv preprint arXiv:1604.06174.
Chen, Ting, Kornblith, Simon, Norouzi, Mohammad, Hinton, Geoffrey (2020). A Simple Framework for Contrastive Learning of Visual Representations. Proceedings of the 37th International Conference on Machine Learning.
Chen, Zitao, Narayanan, Niranjhana, Fang, Bo, Li, Guanpeng, Pattabiraman, Karthik, DeBardeleben, Nathan (2020). TensorFI: A Flexible Fault Injection Framework for TensorFlow Applications. 2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE).
Choquette, Jack (2023). NVIDIA Hopper H100 GPU: Scaling Performance. IEEE Micro.
Chouldechova, Alexandra (2017). Fair Prediction With Disparate Impact: A Study of Bias in Recidivism Prediction Instruments. Big Data.
Chowdhery, Aakanksha, Narang, Sharan, Devlin, Jacob, Bosma, Maarten, Mishra, Gaurav, Roberts, Adam, Barham, Paul, Chung, Hyung Won, Sutton, Charles, Gehrmann, Sebastian, Schuh, Parker, Shi, Kensen, Tsvyashchenko, Sasha, Maynez, Joshua, Rao, Abhishek, Barnes, Parker, Tay, Yi, Shazeer, Noam, Prabhakaran, Vinodkumar, Reif, Emily, Du, Nan, Hutchinson, Ben, Pope, Reiner, Bradbury, James, Austin, Jacob, Isard, Michael, Gur-Ari, Guy, Yin, Pengcheng, Duke, Toju, Levskaya, Anselm, Ghemawat, Sanjay, Dev, Sunipa, Michalewski, Henryk, Garcia, Xavier, Misra, Vedant, Robinson, Kevin, Fedus, Liam, Zhou, Denny, Ippolito, Daphne, Luan, David, Lim, Hyeontaek, Zoph, Barret, Spiridonov, Alexander, Sepassi, Ryan, Dohan, David, Agrawal, Shivani, Omernick, Mark, Dai, Andrew M., Pillai, Thanumalayan Sankaranarayana, Pellat, Marie, Lewkowycz, Aitor, Moreira, Erica, Child, Rewon, Polozov, Oleksandr, Lee, Katherine, Zhou, Zongwei, Wang, Xuezhi, Saeta, Brennan, Diaz, Mark, Firat, Orhan, Catasta, Michele, Wei, Jason, Meier-Hellstern, Kathy, Eck, Douglas, Dean, Jeff, Petrov, Slav, Fiedel, Noah (2022). PaLM: Scaling Language Modeling with Pathways. arXiv preprint arXiv:2204.02311.
Christiano, P. F., Leike, J., Brown, T. B., Martic, M., Legg, S., Amodei, D. (2017). Deep Reinforcement Learning from Human Preferences. Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 4299–4307
Chung, Jae-Won, Gu, Yile, Jang, Insu, Meng, Luoxi, Bansal, Nikhil, Chowdhury, Mosharaf (2023). Reducing Energy Bloat in Large Model Training. Proceedings of the 30th ACM SIGOPS Symposium on Operating Systems Principles.
Clos, C. (1953). A Study of Non-Blocking Switching Networks. Bell System Technical Journal.
Cloud Native Computing Foundation (2024). Kubernetes: Production-Grade Container Orchestration.
Cloudflare (2019). Details of the Cloudflare Outage on July 2, 2019. Cloudflare incident report.
CNBC (2023). California DMV Suspends Cruise’s Self-Driving Car Permits. CNBC news article
CNBC (2023). Cruise Under NHTSA Probe Into Autonomous Driving Pedestrian Injuries. CNBC news article
Cohen, Jeremy, Rosenfeld, Elan, Kolter, Zico (2019). Certified Adversarial Robustness via Randomized Smoothing. International Conference on Machine Learning (ICML).
Constantinescu, C. (2008). Intermittent faults and effects on reliability of integrated circuits. 2008 Annual Reliability and Maintainability Symposium.
Cooper, Tom, Fallender, Suzanne, Pafumi, Joyann, Dettling, Jon, Humbert, Sebastien, Lessard, Lindsay (2011). A semiconductor company’s examination of its water footprint approach. Proceedings of the 2011 IEEE International Symposium on Sustainable Systems and Technology.
coreboot contributors (2026). coreboot.
coreboot contributors (2026). vboot: Verified Boot Support.
Courbariaux, Matthieu, Hubara, Itay, Soudry, Daniel, El-Yaniv, Ran, Bengio, Yoshua (2016). Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1. arXiv preprint arXiv:1602.02830.
Covington, Paul, Adams, Jay, Sargin, Emre (2016). Deep Neural Networks for YouTube Recommendations. Proceedings of the 10th ACM Conference on Recommender Systems.
Culler, David, Karp, Richard, Patterson, David, Sahay, Abhijit, Schauser, Klaus Erik, Santos, Eunice, Subramonian, Ramesh, Eicken, Thorsten (1993). LogP: towards a realistic model of parallel computation. ACM SIGPLAN Notices.
Cyberspace Administration of China, National Development and Reform Commission, Ministry of Education, Ministry of Science and Technology, Ministry of Industry and Information Technology, Ministry of Public Security, et al. (2023). Interim Measures for Administration of Generative Artificial Intelligence Services. State Council Gazette
Daly, J.T. (2006). A higher order estimate of the optimum checkpoint interval for restart dumps. Future Generation Computer Systems.
Dao, T., Fu, D. Y., Ermon, S., Rudra, A., Ré, C. (2022). FlashAttention: Fast and Memory-Efficient Exact Attention With IO-Awareness. Advances in Neural Information Processing Systems (NeurIPS).
Dao, Tri (2023). FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning. arXiv preprint arXiv:2307.08691.
Dastin, Jeffrey (2018). Amazon Scraps Secret AI Recruiting Tool That Showed Bias Against Women. Reuters
Databricks (2026). Mosaic Streaming: Main Concepts. Databricks Mosaic AI Training Documentation.
Dayarathna, Miyuru, Wen, Yonggang, Fan, Rui (2016). Data Center Energy Consumption Modeling: A Survey. IEEE Communications Surveys & Tutorials.
De, Soham, Berrada, Leonard, Hayes, Jamie, Smith, Samuel L., Balle, Borja (2022). Unlocking High-Accuracy Differentially Private Image Classification through Scale. arXiv preprint arXiv:2204.13650.
Dean, Jeff (2024). Exciting Directions in Systems for Machine Learning. MLSys 2024 invited talk.
Dean, Jeffrey, Barroso, Luiz André (2013). The tail at scale. Communications of the ACM.
Dean, Jeffrey, Corrado, Greg, Monga, Rajat, Chen, Kai, Devin, Matthieu, Le, Quoc V., Mao, Mark Z., Ranzato, Marc’Aurelio, Senior, Andrew W., Tucker, Paul A., Yang, Ke, Ng, Andrew Y. (2012). Large Scale Distributed Deep Networks. Advances in Neural Information Processing Systems (NeurIPS).
Dean, Jeffrey, Ghemawat, Sanjay (2004). MapReduce: Simplified Data Processing on Large Clusters. Proceedings of the 6th Symposium on Operating Systems Design and Implementation (OSDI).
DeepSpeed Developers (2026). DeepSpeed Model Checkpointing. DeepSpeed documentation.
DeepSpeed Developers (2026). Universal Checkpointing with DeepSpeed: A Practical Guide. DeepSpeed tutorial.
Dell Technologies (2026). Data Center Power and Cooling Solutions.
Dennard et al. (1974). Design of ion-implanted MOSFET’s with very small physical dimensions. IEEE Journal of Solid-State Circuits.
Department for Education, Ofqual (2020). GCSE and A Level Students to Receive Centre Assessment Grades. GOV.UK News Story
Dettmers, Tim, Lewis, Mike, Belkada, Younes, Zettlemoyer, Luke (2022). LLM.int8(): 8-Bit Matrix Multiplication for Transformers at Scale. Advances in Neural Information Processing Systems (NeurIPS).
Devlin, Jacob, Chang, Ming-Wei, Lee, Kenton, Toutanova, Kristina (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
Dixit, H. D., Pendharkar, S., Beadon, M., Mason, C., Chakravarthy, T., Muthiah, B., Sankar, S. (2021). Silent Data Corruptions at Scale. arXiv preprint arXiv:2102.11245.
Dodge, Jesse, Prewitt, Taylor, Combes, Remi, Odmark, Erika, Schwartz, Roy, Strubell, Emma, Luccioni, Alexandra, Smith, Noah, DeCario, Nicole, Buchanan, Will (2022). Measuring the Carbon Intensity of AI in Cloud Instances. 2022 ACM Conference on Fairness Accountability and Transparency.
Dubey, Abhimanyu, Jauhri, Abhinav, Pandey, Abhinav, Kadian, Abhishek, others (2024). The Llama 3 Herd of Models. arXiv preprint arXiv:2407.21783.
Dwork, Cynthia, Hardt, Moritz, Pitassi, Toniann, Reingold, Omer, Zemel, Richard (2012). Fairness Through Awareness. Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, 214–226
Dwork, Cynthia, McSherry, Frank, Nissim, Kobbi, Smith, Adam (2006). Calibrating Noise to Sensitivity in Private Data Analysis. Theory of Cryptography Conference (TCC).
Dwork, Cynthia, Roth, Aaron (2014). The Algorithmic Foundations of Differential Privacy. Foundations and Trends® in Theoretical Computer Science.
Ebrahimi, K., Jones, G. F., Fleischer, A. S. (2014). A review of data center cooling technology, operating conditions and the corresponding low-grade waste heat recovery opportunities. Renewable and Sustainable Energy Reviews.
Eckles, Dean, Karrer, Brian, Ugander, Johan (2017). Design and analysis of experiments in networks: Reducing bias from interference. Journal of Causal Inference.
Egwutuoha, I. P., Levy, D., Selic, B., Chen, S. (2013). A survey of fault tolerance mechanisms and checkpoint/restart implementations for high performance computing systems. The Journal of Supercomputing.
Elsken, Thomas, Metzen, Jan, Hutter, Frank (2019). Neural Architecture Search. The Springer Series on Challenges in Machine Learning.
Engineering at Meta (2016). Introducing FBLearner Flow: Facebook’s AI backbone. Engineering at Meta Blog.
Environment and Climate Change Canada (2026). Emission Factors and Reference Values.
Erlang, Agner Krarup (1909). The Theory of Probabilities and Telephone Conversations. Nyt Tidsskrift for Matematik B.
Ethernet Alliance (2025). 2025 Ethernet Roadmap. Ethernet Alliance roadmap.
European Data Protection Board (2018). Guidelines on Automated Individual Decision-Making and Profiling for the Purposes of Regulation 2016/679.
European Parliament and Council of the European Union (2024). Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence (AI Act). Official Journal of the European Union, L 2024/1689
European Parliament, Council of the European Union (2016). Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016. Official Journal of the European Union
European Parliament, Council of the European Union (2016). Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016. Official Journal of the European Union.
Evans, Richard and Gao, Jim (2016). DeepMind AI Reduces Google Data Centre Cooling Bill by 40%. DeepMind Blog.
Executive Office of the President (2023). Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence. Executive Order 14110, 88 FR 75191
Executive Office of the President (2025). Initial Rescissions of Harmful Executive Orders and Actions. Executive Order 14148, 90 FR 8237
Executive Office of the President (2025). Removing Barriers to American Leadership in Artificial Intelligence. Executive Order 14179
Executive Office of the President (2026). Promoting Advanced Artificial Intelligence Innovation and Security. Executive Order 14409, 91 FR 34565
Eykholt, K., Evtimov, I., Fernandes, E., Li, B., Rahmati, A., Xiao, C., et al. (2018). Robust Physical-World Attacks on Deep Learning Visual Classification. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
Eykholt, Kevin, Evtimov, Ivan, Fernandes, Earlence, Li, Bo, Rahmati, Amir, Xiao, Chaowei, Prakash, Atul, Kohno, Tadayoshi, Song, Dawn (2017). Robust Physical-World Attacks on Deep Learning Models. ArXiv preprint.
Farwell, J. P., Rohozinski, R. (2011). Stuxnet and the Future of Cyber War. Survival.
Federal Aviation Administration (2015). Airworthiness Directive: Boeing 787 Generator Control Units Failsafe Reset. FAA Airworthiness Directive 2015-10066.
Federal Trade Commission (2021). Nixing the Fix: An FTC Report to Congress on Repair Restrictions.
Fedus et al. (2022). Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity. Journal of Machine Learning Research.
Feldman, M., Friedler, S. A., Moeller, J., Scheidegger, C., Venkatasubramanian, S. (2015). Certifying and Removing Disparate Impact. Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 259–268
Finn, Chelsea, Abbeel, Pieter, Levine, Sergey (2017). Model-agnostic meta-learning for fast adaptation of deep networks. Proceedings of the 34th International Conference on Machine Learning (ICML).
Forti, Vanessa, Baldé, C. P., Kuehr, R., Bel, G. (2020). The Global E-waste Monitor 2020: Quantities, Flows and the Circular Economy Potential.
Framework Computer (2022). Modular Laptops: A New Approach to Sustainable Computing.
Francalanza, Adrian, Aceto, Luca, Achilleos, Antonis, Attard, Duncan Paul, Cassar, Ian, Della Monica, Dario, Ingólfsdóttir, Anna (2017). A Foundation for Runtime Monitoring. Runtime Verification.
Frantar, Elias, Ashkboos, Saleh, Hoefler, Torsten, Alistarh, Dan (2023). GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers. International Conference on Learning Representations (ICLR).
Fredrikson, Matt, Jha, Somesh, Ristenpart, Thomas (2015). Model Inversion Attacks That Exploit Confidence Information and Basic Countermeasures. Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security.
Friedman, B. (1996). Value-Sensitive Design. Interactions, 16–23
Gal, Yarin, Ghahramani, Zoubin (2016). Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning. Proceedings of the 33rd International Conference on Machine Learning (ICML).
Gama, João, Žliobaitė, Indrė, Bifet, Albert, Pechenizkiy, Mykola, Bouchachia, Abdelhamid (2014). A survey on concept drift adaptation. ACM Computing Surveys.
Gandolfi, Karine, Mourtel, Christophe, Olivier, Francis (2001). Electromagnetic Analysis: Concrete Results. Cryptographic Hardware and Embedded Systems — CHES 2001.
Gangidi, Adi, Miao, Rui, Hebbani, Sandeep, Nagarajan, Gaya, Baldonado, Omar, Gao, Lixin, Goes, Hany Morsy, Puri, Rohit, Riftadi, Mohammad, Shetty, Ashmitha Jeevaraj, Yang, Jingyi, Zhang, Shuqiang, Fernandez, Mikel Jimenez, Gandham, Shashidhar, Zeng, Hongyi (2024). RDMA over Ethernet for Distributed AI Training at Meta Scale. Proceedings of the ACM SIGCOMM 2024 Conference.
Gao, J. (2014). Machine Learning Applications for Data Center Optimization. Google White Paper.
Gao, Y., Al-Sarawi, S. F., Abbott, D. (2020). Physical unclonable functions. Nature Electronics.
Gassend, Blaise, Clarke, Dwaine, van Dijk, Marten, Devadas, Srinivas (2002). Silicon physical random functions. Proceedings of the 9th ACM conference on Computer and communications security.
Gebru, Timnit, Morgenstern, Jamie, Vecchione, Briana, Vaughan, Jennifer Wortman, Wallach, Hanna, Daumé III, Hal, et al. (2021). Datasheets for datasets. Communications of the ACM, 86–92
Geiger, Atticus, Lu, Hanson, Icard, Thomas, Potts, Christopher (2021). Causal Abstractions of Neural Networks. Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 9574–9586
Genkin, Daniel, Shamir, Adi, Tromer, Eran (2017). Acoustic cryptanalysis. Journal of Cryptology.
Gentry, C. (2009). Fully Homomorphic Encryption Using Ideal Lattices. Proceedings of the forty-first annual ACM symposium on Theory of computing.
Ghodsi, Ali, Zaharia, Matei, Hindman, Benjamin, Konwinski, Andy, Shenker, Scott, Stoica, Ion (2011). Dominant Resource Fairness: Fair Allocation of Multiple Resource Types. Proceedings of the 8th USENIX Symposium on Networked Systems Design and Implementation (NSDI 11).
Gholami, Amir, Kim, Sehoon, Dong, Zhen, Yao, Zhewei, Mahoney, Michael, Keutzer, Kurt (2022). A Survey of Quantization Methods for Efficient Neural Network Inference. Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence.
Gibiansky, A. (2017). Bringing HPC Techniques to Deep Learning. Baidu Research Technical Blog.
Gilbert, Seth, Lynch, Nancy (2002). Brewer’s conjecture and the feasibility of consistent, available, partition-tolerant web services. ACM SIGACT News.
GitLab (2017). Postmortem of Database Outage of January 31. GitLab postmortem.
Gnad, D. R. E., Oboril, F., Tahoori, M. B. (2017). Voltage drop-based fault attacks on FPGAs using valid bitstreams. 2017 27th International Conference on Field Programmable Logic and Applications (FPL).
Goldberg, David (1991). What every computer scientist should know about floating-point arithmetic. ACM Computing Surveys.
Gomez-Uribe, Carlos A., Hunt, Neil (2015). The Netflix Recommender System. ACM Transactions on Management Information Systems.
Goncalves, A., Ray, P., Soper, B., Stevens, J., Coyle, L., Sales, A. P. (2020). Generation and evaluation of synthetic patient data. BMC Medical Research Methodology.
Goodfellow, I. J., Shlens, J., Szegedy, C. (2015). Explaining and Harnessing Adversarial Examples. International Conference on Learning Representations (ICLR).
Google (2024). ShieldGemma: Generative AI Content Moderation Based on Gemma. Google AI for Developers documentation.
Google Cloud (2026). About Cloud Storage Objects. Google Cloud Documentation.
Google Data Centers (2023). Efficiency: How We Do It.
Government of Ireland (2022). Government Statement on the Role of Data Centres in Ireland’s Enterprise Strategy. Government policy statement.
Goyal, Priya, Dollár, Piotr, Girshick, Ross, Noordhuis, Pieter, Wesolowski, Lukasz, Kyrola, Aapo, Tulloch, Andrew, Jia, Yangqing, He, Kaiming (2017). Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour. arXiv preprint arXiv:1706.02677.
Graham, R. L., Bureddy, D., Lui, P., Rober, H., Bloch, G., Shainer, G., Poole, J., Tygert, M., Nguyen, P., Srivastava, A., others (2020). Scalable hierarchical aggregation and reduction protocol (SHARP) streaming-aggregation hardware design and evaluation. International Conference on High Performance Computing.
Gray, J. N. (1978). Notes on data base operating systems. Operating Systems: An Advanced Course.
Greshake, Kai, Abdelnabi, Sahar, Mishra, Shailesh, Endres, Christoph, Holz, Thorsten, Fritz, Mario (2023). Not what you’ve signed up for: Compromising real-world LLM-integrated applications with indirect prompt injection. Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security.
Grossman, E. (2007). High tech trash: Digital devices, hidden toxics, and human health. Island press.
Gräfe, Ralf, Sha, Qutub Syed, Geissler, Florian, Paulitsch, Michael (2023). Large-Scale Application of Fault Injection Into PyTorch Models -an Extension to PyTorchFI for Validation Efficiency. 2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S).
Gu, J., Chowdhury, M., Shin, K. G., Zhu, Y., Jeon, M., Qian, J., Liu, H. H., Guo, C. (2019). Tiresias: A GPU Cluster Manager for Distributed Deep Learning. Proceedings of the 16th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’19).
Gu, Tianyu, Dolan-Gavitt, Brendan, Garg, Siddharth (2017). BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain. arXiv preprint arXiv:1708.06733.
Guo, Chuan, Pleiss, Geoff, Sun, Yu, Weinberger, Kilian Q. (2017). On Calibration of Modern Neural Networks. International Conference on Machine Learning (ICML).
Guo, Chuanxiong, Wu, Haitao, Deng, Zhong, Soni, Gaurav, Ye, Jianxi, Padhye, Jitendra, Lipshteyn, Marina (2016). RDMA over Commodity Ethernet at Scale. Proceedings of the 2016 ACM SIGCOMM Conference.
Gupta, Maanak, Akiri, Charankumar, Aryal, Kshitiz, Parker, Eli, Praharaj, Lopamudra (2023). From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy. IEEE Access.
Gupta, Udit, Kim, Young Geun, Lee, Sylvia, Tse, Jordan, Lee, Hsien-Hsin S., Wei, Gu-Yeon, Brooks, David, Wu, Carole-Jean (2022). Chasing Carbon: The Elusive Environmental Footprint of Computing. IEEE Micro.
Gupta, Udit, Wu, Carole-Jean, Wang, Xiaodong, Naumov, Maxim, Reagen, Brandon, Brooks, David, Cottel, Bradford, Hazelwood, Kim, Hempstead, Mark, Jia, Bill, Lee, Hsien-Hsin S., Malevich, Andrey, Mudigere, Dheevatsa, Smelyanskiy, Mikhail, Xiong, Liang, Zhang, Xuan (2020). The Architectural Implications of Facebook’s DNN-Based Personalized Recommendation. 2020 IEEE International Symposium on High Performance Computer Architecture (HPCA), 488–501.
Gustafson, John L. (1988). Reevaluating Amdahl’s Law. Communications of the ACM.
Hamming, R. W. (1950). Error Detecting and Error Correcting Codes. Bell System Technical Journal.
Han, Song, Pool, Jeff, Tran, John, Dally, William J. (2015). Learning both Weights and Connections for Efficient Neural Networks. Advances in Neural Information Processing Systems 28 (NeurIPS 2015).
Hard, Andrew, Rao, Kanishka, Mathews, Rajiv, Ramaswamy, Swaroop, Beaufays, Françoise, Augenstein, Sean, Eichner, Hubert, Kiddon, Chloé, Ramage, Daniel (2018). Federated Learning for Mobile Keyboard Prediction. arXiv preprint arXiv:1811.03604.
Hardt, Moritz, Price, Eric, Srebro, Nathan (2016). Equality of Opportunity in Supervised Learning. Advances in Neural Information Processing Systems (NeurIPS).
Hayes, T. L., Kafle, K., Shrestha, R., Acharya, M., Kanan, C. (2020). REMIND Your Neural Network to Prevent Catastrophic Forgetting. Computer Vision – ECCV 2020.
Hazelwood, Kim, Bird, Sarah, Brooks, David, Chintala, Soumith, Diril, Utku, Dzhulgakov, Dmytro, Fawzy, Mohamed, Jia, Bill, Jia, Yangqing, Kalro, Aditya, Law, James, Lee, Kevin, Lu, Jason, Noordhuis, Pieter, Smelyanskiy, Misha, Xiong, Liang, Wang, Xiaodong (2018). Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective. 2018 IEEE International Symposium on High Performance Computer Architecture (HPCA), 620–629.
He, Kaiming, Zhang, Xiangyu, Ren, Shaoqing, Sun, Jian (2016). Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
He, Yi, Balaprakash, Prasanna, Li, Yanjing (2020). FIdelity: Efficient Resilience Analysis Framework for Deep Learning Accelerators. 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).
He, Yi, Hutton, Mike, Chan, Steven, De Gruijl, Robert, Govindaraju, Rama, Patil, Nishant, Li, Yanjing (2023). Understanding and Mitigating Hardware Failures in Deep Learning Training Systems. Proceedings of the 50th Annual International Symposium on Computer Architecture.
Hebert-Johnson, U., Kim, M. P., Reingold, O., Rothblum, G. N. (2018). Multicalibration: Calibration for the (Computationally-Identifiable) Masses. Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholm, Sweden, 1944–1953
Henderson, Peter, Hu, Jieru, Romoff, Joshua, Brunskill, Emma, Jurafsky, Dan, Pineau, Joelle (2020). Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. CoRR.
Hendrycks, Dan, Dietterich, Thomas (2019). Benchmarking Neural Network Robustness to Common Corruptions and Perturbations. arXiv preprint arXiv:1903.12261.
Hendrycks, Dan, Gimpel, Kevin (2017). A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks. International Conference on Learning Representations (ICLR).
Hennessy and Patterson (2019). A new golden age for computer architecture. Communications of the ACM.
Hennessy, J. L., Patterson, D. A. (2011). Computer Architecture: A Quantitative Approach. Morgan Kaufmann.
Hennessy, John L., Patterson, David A. (2017). Computer Architecture: A Quantitative Approach. Morgan Kaufmann.
Hermann, Jeremy, Del Balso, Mike (2017). Meet Michelangelo: Uber’s Machine Learning Platform. Uber Engineering Blog.
Himmelstein, Gracie, Bates, David, Zhou, Li (2022). Examination of Stigmatizing Language in the Electronic Health Record. JAMA Network Open, e2144967
Hindman, Benjamin, Konwinski, Andy, Zaharia, Matei, Ghodsi, Ali, Joseph, Anthony D., Katz, Randy, Shenker, Scott, Stoica, Ion (2011). Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center. Proceedings of the 8th USENIX Symposium on Networked Systems Design and Implementation (NSDI 11).
Hinton, Geoffrey, Vinyals, Oriol, Dean, Jeff (2015). Distilling the Knowledge in a Neural Network. arXiv preprint.
Ho, Qirong, Cipar, James, Cui, Henggang, Lee, Seunghak, Kim, Jin Kyu, Gibbons, Phillip B., Gibson, Garth A., Ganger, Greg, Xing, Eric P. (2013). More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server. Advances in Neural Information Processing Systems (NeurIPS).
Hockney, Roger W. (1994). The communication challenge for MPP: Intel Paragon and Meiko CS-2. Parallel Computing.
Hoffmann, Jordan, Borgeaud, Sebastian, Mensch, Arthur, Buchatskaya, Elena, Cai, Trevor, Rutherford, Eliza, de Las Casas, Diego, Hendricks, Lisa Anne, Welbl, Johannes, Clark, Aidan, Hennigan, Tom, Noland, Eric, Millican, Katie, van den Driessche, George, Damoc, Bogdan, Guy, Aurelia, Osindero, Simon, Simonyan, Karen, Elsen, Erich, Rae, Jack W., Vinyals, Oriol, Sifre, Laurent (2022). Training Compute-Optimal Large Language Models. Advances in Neural Information Processing Systems (NeurIPS).
Horovod Developers (2026). Elastic Horovod. Horovod documentation.
Horowitz, Mark (2014). 1.1 Computing’s energy problem (and what we can do about it). 2014 IEEE International Solid-State Circuits Conference Digest of Technical Papers (ISSCC).
Hosseini, Hossein, Kannan, Sreeram, Zhang, Baosen, Poovendran, Radha (2017). Deceiving Google’s Perspective API Built for Detecting Toxic Comments. arXiv preprint arXiv:1702.08138.
Houlsby, Neil, Giurgiu, Andrei, Jastrzebski, Stanislaw, Morrone, Bruna, Laroussilhe, Chloé, Gesmundo, Andrea, Attariyan, Mohammad, Gelly, Sylvain (2019). Parameter-efficient transfer learning for NLP. International Conference on Machine Learning (ICML).
Howard, A. G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., Adam, H. (2017). MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. CoRR.
Hsiao, Yu-Shun, Wan, Zishen, Jia, Tianyu, Ghosal, Radhika, Mahmoud, Abdulrahman, Raychowdhury, Arijit, et al. (2023). MAVFI: An End-To-End Fault Analysis Framework With Anomaly Detection and Recovery for Micro Aerial Vehicles. 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE).
Hsu, Liang-Ching, Huang, Ching-Yi, Chuang, Yen-Hsun, Chen, Ho-Wen, Chan, Ya-Ting, Teah, Heng, Chen, Tsan-Yao, Chang, Chiung-Fen, Liu, Yu-Ting, Tzou, Yu-Min (2016). Accumulation of heavy metals and trace elements in fluvial sediments received effluents from traditional and semiconductor industries. Scientific Reports.
Hu, Edward J., Shen, Yelong, Wallis, Phillip, Allen-Zhu, Zeyuan, Li, Yuanzhi, Wang, Shean, Wang, Lu, Chen, Weizhu (2021). LoRA: Low-Rank Adaptation of Large Language Models. arXiv preprint arXiv:2106.09685.
Huang, Cheng, Simitci, Huseyin, Xu, Yikang, Ogus, Aaron, Calder, Brad, Gopalan, Parikshit, Li, Jin, Yekhanin, Sergey (2012). Erasure Coding in Windows Azure Storage. 2012 USENIX Annual Technical Conference (USENIX ATC 12).
Huang, Y., Cheng, Y., Bapna, A., Firat, O., Chen, D., Chen, M. X., Lee, H., Ngiam, J., Le, Q. V., Wu, Y., Chen, Z. (2019). GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism. Advances in Neural Information Processing Systems (NeurIPS).
Hudgens, Michael G., Halloran, M. Elizabeth (2008). Toward causal inference with interference. Journal of the American Statistical Association.
Hugging Face (2026). Safetensors Documentation.
Hutter, Michael, Schmidt, Jorn-Marc, Plos, Thomas (2009). Contact-based fault injections and power analysis on RFID tags. 2009 European Conference on Circuit Theory and Design.
Hwang, Changho, Cui, Wei, Xiong, Yifan, Yang, Ziyue, Liu, Ze, Hu, Han, Wang, Zilong, Salas, Rafael, Jose, Jithin, Ram, Prabhat, Chau, Joe, Cheng, Peng, Yang, Fan, Yang, Mao, Xiong, Yongqiang (2023). Tutel: Adaptive Mixture-of-Experts at Scale. Proceedings of Machine Learning and Systems (MLSys).
Iandola, Forrest N., Han, Song, Moskewicz, Matthew W., Ashraf, Khalid, Dally, William J., Keutzer, Kurt (2016). SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size. ArXiv preprint.
IEEE 802.1 Working Group (2018). IEEE Standard for Local and Metropolitan Area Networks—Secure Device Identity. IEEE Std 802.1AR-2018.
IEEE Standards Association (2019). IEEE 754-2019: Standard for Floating-Point Arithmetic.
Illinois General Assembly (2020). Artificial Intelligence Video Interview Act (Public Act 101-0260). 820 ILCS 42, effective January 1, 2020
Inan, H., Upasani, K., Chi, J., Rungta, R., Iyer, K., Mao, Y., et al. (2023). Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations. arXiv preprint arXiv:2312.06674.
InfiniBand Trade Association (2000). InfiniBand Architecture Specification Volume 1. Release 1.0. InfiniBand Trade Association.
International Energy Agency (2023). World Energy Outlook 2023. IEA.
International Energy Agency (2024). Data Centre Electricity Demand Estimates as a Share of Total Electricity Demand in Ireland and Virginia, 2023. IEA chart.
International Organization for Standardization (2006). ISO 14040:2006 Environmental Management – Life Cycle Assessment – Principles and Framework. ISO standard.
International Organization for Standardization (2006). ISO 14044:2006 Environmental Management – Life Cycle Assessment – Requirements and Guidelines. ISO standard.
International Organization for Standardization (2014). Environmental Management—Water Footprint—Principles, Requirements and Guidelines.
International Organization for Standardization, International Electrotechnical Commission (2023). ISO/IEC 23894:2023 Information Technology – Artificial Intelligence – Guidance on Risk Management. ISO/IEC standard
International Organization for Standardization, International Electrotechnical Commission (2023). ISO/IEC 42001:2023 Information Technology – Artificial Intelligence – Management System. ISO/IEC standard
Irimia-Vladu, M. (2014). Green electronics: biodegradable and biocompatible materials and devices for sustainable future. Chemical Society Reviews.
Jacob, Benoit, Kligys, Skirmantas, Chen, Bo, Zhu, Menglong, Tang, Matthew, Howard, Andrew, Adam, Hartwig, Kalenichenko, Dmitry (2018). Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
Jacobs, Sam Ade, Tanaka, Masahiro, Zhang, Chengming, Guo, Minjia, Zhu, Shuaiwen, Song, Shuai, Rajbhandari, Samyam, Awan, Ammar Ahmad, Zheng, Connor, He, Yuxiong (2023). DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. arXiv preprint arXiv:2309.14509.
Jagielski, Matthew, Severi, Giorgio, Pousette Harger, Niklas, Oprea, Alina (2021). Subpopulation data poisoning attacks. Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security.
Jain, R. (1991). The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling. John Wiley & Sons.
Janardhan, Santosh (2021). More Details About the October 4 Outage. Meta Engineering postmortem.
Jeaugey, Sylvain (2017). NCCL 2.0. GPU Technology Conference presentation.
Jeon, Myeongjae, Venkataraman, Shivaram, Phanishayee, Amar, Qian, Junjie, Xiao, Wencong, Yang, Fan (2019). Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads. Proceedings of the 2019 USENIX Annual Technical Conference (USENIX ATC 19).
Jevons, William Stanley (1865). The Coal Question: An Inquiry Concerning the Progress of the Nation, and the Probable Exhaustion of Our Coal Mines. Macmillan and Co.
Jha, A.R. (2014). Rare Earth Materials. CRC Press.
Jha, S., Banerjee, S., Tsai, T., Hari, S. K. S., Sullivan, M. B., Kalbarczyk, Z. T., Keckler, S. W., Iyer, R. K. (2019). ML-Based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection. 2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN).
Jiang et al. (2024). Mixtral of Experts. arXiv preprint arXiv:2401.04088.
Jiang, Ziheng, Lin, Haibin, Zhong, Yinmin, Huang, Qi, Chen, Yangrui, Zhang, Zhi, Peng, Yanghua, Li, Xiang, Xie, Cong, Nong, Shibiao, Jia, Yulu, He, Sun, Chen, Hongmin, Bai, Zhihao, Hou, Qi, Yan, Shipeng, Zhou, Ding, Sheng, Yiyao, Jiang, Zhuo, Xu, Haohan, Wei, Haoran, Zhang, Zhang, Nie, Pengfei, Zou, Leqi, Zhao, Sida, Xiang, Liang, Liu, Zherui, Li, Zhe, Jia, Xiaoying, Ye, Jianxi, Jin, Xin, Liu, Xin (2024). MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs. 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24), 745–760.
Jouppi et al. (2017). In-Datacenter Performance Analysis of a Tensor Processing Unit. Proceedings of the 44th Annual International Symposium on Computer Architecture.
Jouppi et al. (2023). TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning With Hardware Support for Embeddings. Proceedings of the 50th Annual International Symposium on Computer Architecture.
Joye, Marc, Tunstall, Michael (2012). Fault Analysis in Cryptography. Springer Berlin Heidelberg.
Kairouz, P., McMahan, H. B. (2021). Advances and Open Problems in Federated Learning. Foundations and Trends in Machine Learning.
Kaplan, J., McCandlish, S., Henighan, T., Brown, T. B., Chess, B., Child, R., Gray, S., Radford, A., Wu, J., Amodei, D. (2020). Scaling Laws for Neural Language Models. ArXiv preprint.
Karger, D., Lehman, E., Leighton, T., Panigrahy, R., Levine, M., Lewin, D. (1997). Consistent hashing and random trees. Proceedings of the twenty-ninth annual ACM symposium on Theory of computing - STOC ’97.
Karimireddy, Sai Praneeth, Rebjock, Quentin, Stich, Sebastian U., Jaggi, Martin (2019). Error feedback fixes SignSGD and other gradient compression schemes. Proceedings of the 36th International Conference on Machine Learning (ICML).
Kasperkevic, Jana (2015). Google Says Sorry for Racist Auto-Tag in Photo App. The Guardian.
Kawazoe Aguilera, Marcos, Chen, Wei, Toueg, Sam (1997). Heartbeat: A timeout-free failure detector for quiescent reliable communication. Lect. Notes Comput. Sci..
Kim, J., Dally, W. J., Scott, S., Abts, D. (2008). Technology-Driven, Highly-Scalable Dragonfly Topology. 2008 International Symposium on Computer Architecture.
Kim, Jungrae, Sullivan, Michael, Erez, Mattan (2015). Bamboo ECC: Strong, safe, and flexible codes for reliable computer memory. 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA).
Kingma, Diederik P., Ba, Jimmy (2015). Adam: A Method for Stochastic Optimization. 3rd International Conference on Learning Representations (ICLR).
Kirkpatrick, J., Pascanu, R., Rabinowitz, N., Veness, J., Desjardins, G., Rusu, A. A., Milan, K., Quan, J., Ramalho, T., Grabska-Barwinska, A., Hassabis, D., Clopath, C., Kumaran, D., Hadsell, R. (2017). Overcoming catastrophic forgetting in neural networks. Proceedings of the National Academy of Sciences.
Kleinberg, Jon, Mullainathan, Sendhil, Raghavan, Manish (2017). Inherent Trade-Offs in the Fair Determination of Risk Scores. 8th Innovations in Theoretical Computer Science Conference (ITCS 2017).
Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience.
Kleppmann, Martin (2016). Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. O’Reilly Media.
Klutke, G., Kiessler, P. C., Wortman, M. A. (2003). A critical look at the bathtub curve. IEEE Transactions on Reliability.
Ko, Y. (2021). Characterizing System-Level Masking Effects Against Soft Errors. Electronics.
Kocher, Paul, Horn, Jann, Fogh, Anders, Genkin, Daniel, Gruss, Daniel, Haas, Werner, et al. (2019). Spectre Attacks: Exploiting Speculative Execution. 2019 IEEE Symposium on Security and Privacy (SP).
Kocher, Paul, Jaffe, Joshua, Jun, Benjamin (1999). Differential Power Analysis. Advances in Cryptology — CRYPTO’ 99.
Kocher, Paul, Jaffe, Joshua, Jun, Benjamin, Rohatgi, Pankaj (2011). Introduction to differential power analysis. Journal of Cryptographic Engineering.
Koh, Pang, Liang, Percy (2017). Understanding Black-box Predictions via Influence Functions. International Conference on Machine Learning (ICML).
Kohavi, Ron, Longbotham, Roger, Sommerfield, Dan, Henne, Randal M. (2009). Controlled experiments on the web: survey and practical guide. Data Mining and Knowledge Discovery.
Kohavi, Ron, Tang, Diane, Xu, Ya (2020). Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press.
Kokolis, Apostolos, Kuchnik, Michael, Hoffman, John, Kumar, Adithya, Malani, Parth, Ma, Faye, DeVito, Zach, Sengupta, Shubho, Saladi, Kalyan, Wu, Carole-Jean (2025). Revisiting Reliability in Large-Scale Machine Learning Research Clusters. 2025 IEEE International Symposium on High Performance Computer Architecture (HPCA).
Konečný, J., McMahan, H. B., Ramage, D., Richtárik, P. (2016). Federated Optimization: Distributed Machine Learning for On-Device Intelligence. CoRR.
Koren, Yehuda, Bell, Robert, Volinsky, Chris (2009). Matrix Factorization Techniques for Recommender Systems. Computer.
Korosec, Kirsten (2019). Tesla Sues Former Employees, Zoox for Alleged Trade Secret Theft. TechCrunch.
Korthikanti, Vijay Anand, Casper, Jared, Lym, Sangkug, McAfee, Lawrence, Andersch, Michael, Shoeybi, Mohammad, Catanzaro, Bryan (2023). Reducing Activation Recomputation in Large Transformer Models. Proceedings of Machine Learning and Systems (MLSys).
Krishna, Kalpesh, Tomar, Gaurav Singh, Parikh, Ankur P., Papernot, Nicolas, Iyyer, Mohit (2020). Thieves on Sesame Street! Model extraction of BERT-based APIs. International Conference on Learning Representations (ICLR).
Krishnamoorthi, Raghuraman (2018). Quantizing deep convolutional networks for efficient inference: A whitepaper. arXiv preprint arXiv:1806.08342.
Krizhevsky, Alex, Sutskever, Ilya, Hinton, Geoffrey E. (2012). ImageNet Classification with Deep Convolutional Neural Networks. Advances in Neural Information Processing Systems (NeurIPS).
Kung (1982). Why systolic architectures? Computer.
Kung and Leiserson (1979). Systolic arrays (for VLSI). Sparse Matrix Proceedings 1978.
Kurakin, Alexey, Goodfellow, Ian, Bengio, Samy (2017). Adversarial Examples in the Physical World. International Conference on Learning Representations (ICLR), Workshop Track.
Kusner, Matt J., Loftus, Joshua, Russell, Chris, Silva, Ricardo (2017). Counterfactual Fairness. Advances in Neural Information Processing Systems, 4066–4076
Kwon, Woosuk, Li, Zhuohan, Zhuang, Siyuan, Sheng, Ying, Zheng, Lianmin, Yu, Cody Hao, Gonzalez, Joseph, Zhang, Hao, Stoica, Ion (2023). Efficient Memory Management for Large Language Model Serving with PagedAttention. Proceedings of the 29th Symposium on Operating Systems Principles.
Kwon, Y. D., Li, R., Venieris, S. I., Chauhan, J., Lane, N. D. (2024). TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge. Proceedings of the 41st International Conference on Machine Learning (ICML).
Kwon, Youngeun, Rhu, Minsoo (2018). TensorDIMM. Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture.
Lacoste, Alexandre, Luccioni, Alexandra, Schmidt, Victor, Dandres, Thomas (2019). Quantifying the Carbon Emissions of Machine Learning. arXiv preprint arXiv:1910.09700.
Lai, Liangzhen, Suda, Naveen, Chandra, Vikas (2018). CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs. ArXiv preprint.
Lakshminarayanan, Balaji, Pritzel, Alexander, Blundell, Charles (2017). Simple and Scalable Predictive Uncertainty Estimation Using Deep Ensembles. Advances in Neural Information Processing Systems (NeurIPS).
Lamport, Leslie, Shostak, Robert, Pease, Marshall (1982). The Byzantine Generals Problem. ACM Transactions on Programming Languages and Systems.
Langston, Jennifer (2020). Microsoft Announces New Supercomputer, Lays Out Vision for Future AI Work. Microsoft Source.
Lannelongue, Loïc, Grealey, Jason, Inouye, Michael (2021). Green Algorithms: Quantifying the Carbon Footprint of Computation. Advanced Science.
Lazer, David, Kennedy, Ryan, King, Gary, Vespignani, Alessandro (2014). The Parable of Google Flu: Traps in Big Data Analysis. Science, 1203–1205
Lei, Jing, G’Sell, Max, Rinaldo, Alessandro, Tibshirani, Ryan J., Wasserman, Larry (2018). Distribution-Free Predictive Inference for Regression. Journal of the American Statistical Association.
Leiserson, Charles E. (1985). Fat-trees: Universal networks for hardware-efficient supercomputing. IEEE Transactions on Computers.
Lepikhin et al. (2021). GShard: Scaling giant models with conditional computation and automatic sharding. International Conference on Learning Representations (ICLR).
Leviathan, Yaniv, Kalman, Matan, Matias, Yossi (2023). Fast Inference from Transformers via Speculative Decoding. International Conference on Machine Learning (ICML).
Lewis, Patrick, Perez, Ethan, Piktus, Aleksandra, Petroni, Fabio, Karpukhin, Vladimir, Goyal, Naman, Küttler, Heinrich, Lewis, Mike, Yih, Wen-tau, Rocktäschel, Tim, Riedel, Sebastian, Kiela, Douwe (2020). Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. Advances in Neural Information Processing Systems.
Li, Chengwei (2020). Estimating the Training Cost of GPT-3. Lambda Labs Blog.
Li, Guanpeng, Hari, Siva Kumar Sastry, Sullivan, Michael, Tsai, Timothy, Pattabiraman, Karthik, Emer, Joel, Keckler, Stephen W. (2017). Understanding error propagation in deep learning neural network (DNN) accelerators and applications. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis.
Li, Jie, Michelogiannakis, George, Cook, Brandon, Cooray, Dulanya, Chen, Yong (2023). Analyzing Resource Utilization in an HPC System: A Case Study of NERSC’s Perlmutter. Lecture Notes in Computer Science, vol. 13948, Springer Nature Switzerland.
Li, M., Andersen, D. G., Park, J. W., Smola, A. J., Ahmed, A., Josifovski, V., Long, J., Shekita, E. J., Su, B.-Y. (2014). Scaling Distributed Machine Learning With the Parameter Server. Proceedings of the 2014 International Conference on Big Data Science and Computing.
Li, Shen, Zhao, Yanli, Varma, Rohan, Salpekar, Omkar, Noordhuis, Pieter, Li, Teng, Paszke, Adam, Smith, Jeff, Vaughan, Brian, Damania, Pritam, Chintala, Soumith (2020). PyTorch distributed. Proceedings of the VLDB Endowment.
Li, Tian, Sahu, Anit Kumar, Talwalkar, Ameet, Smith, Virginia (2020). Federated Learning: Challenges, Methods, and Future Directions. IEEE Signal Processing Magazine.
Li, Yuliang, Miao, Rui, Liu, Hongqiang Harry, Zhuang, Yan, Feng, Fei, Tang, Lingbo, Cao, Zheng, Zhang, Ming, Kelly, Frank, Alizadeh, Mohammad, Yu, Minlan (2019). HPCC: High Precision Congestion Control. Proceedings of the ACM Special Interest Group on Data Communication (SIGCOMM).
Lifka, David A. (1995). The ANL/IBM SP Scheduling System. Job Scheduling Strategies for Parallel Processing, Lecture Notes in Computer Science, vol. 949.
Lin, Ji, Chen, Wei-Ming, Lin, Yujun, Cohn, John, Gan, Chuang, Han, Song (2020). MCUNet: Tiny Deep Learning on IoT Devices. Advances in Neural Information Processing Systems 33 (NeurIPS 2020).
Lin, Ji, Tang, Jiaming, Tang, Haotian, Yang, Shang, Chen, Wei-Ming, Wang, Wei-Chen, Xiao, Guangxuan, Dang, Xingyu, Gan, Chuang, Han, Song (2024). AWQ: Activation-aware Weight Quantization for on-device LLM compression and acceleration. Proceedings of Machine Learning and Systems.
Lin, Yujun, Han, Song, Mao, Huizi, Wang, Yu, Dally, William J (2018). Deep gradient compression: Reducing the communication bandwidth for distributed training. International Conference on Learning Representations (ICLR).
Lindholm, Andreas, Zachariah, Dave, Stoica, Petre, Schon, Thomas B. (2019). Data Consistency Approach to Model Validation. IEEE Access.
Linux man-pages project (2026). perfquery(8): Query InfiniBand Port Counters on a Single Port. Linux man-pages.
linux-rdma project (2026). perftest: InfiniBand Verbs Performance Tests. GitHub repository.
Lipp, M., Schwarz, M., Gruss, D., Prescher, T., Haas, W., Horn, J., et al. (2018). Meltdown. Proceedings of the 27th USENIX Security Symposium (USENIX Security).
Lipton, Zachary, Wang, Yu-Xiang, Smola, Alexander (2018). Detecting and Correcting for Label Shift with Black Box Predictors. International Conference on Machine Learning (ICML).
Little, John D. C. (1961). A Proof for the Queuing Formula: $L = λW$ . Operations Research.
Liu, Hao, Zaharia, Matei, Abbeel, Pieter (2023). Ring Attention with Blockwise Transformers for Near-Infinite Context. arXiv preprint arXiv:2310.01889.
Liu, W., Xi, Y., Qin, J., Sun, F., Chen, B., Zhang, W., Zhang, R., Tang, R. (2022). Neural Re-Ranking in Multi-Stage Recommender Systems: A Review. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.
Luccioni, Alexandra Sasha, Viguier, Sylvain, Ligozat, Anne-Laure (2023). Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model. Journal of Machine Learning Research.
Lundberg, Scott M., Lee, Su-In (2017). A Unified Approach to Interpreting Model Predictions. Advances in Neural Information Processing Systems (NeurIPS), 4765–4774
Lustre Wiki (2017). lfs setstripe: set striping pattern of a file. Lustre Wiki manual page.
Lustre Wiki (2019). Configuring Lustre File Striping. Lustre Wiki.
Ma, Jeffrey, Pei, Hengzhi, Lausen, Leonard, Karypis, George (2025). Understanding Silent Data Corruption in LLM Training. arXiv preprint arXiv:2502.12340.
Ma, Jeffrey, Tu, Alan, Chen, Yiling, Reddi, Vijay Janapa (2024). FedStaleWeight: Buffered Asynchronous Federated Learning with Fair Aggregation via Staleness Reweighting. arXiv preprint arXiv:2406.02877.
Ma, Xiaoyu, Patterson, David (2026). Challenges and Research Directions for Large Language Model Inference Hardware.
Madry, Aleksander, Makelov, Aleksandar, Schmidt, Ludwig, Tsipras, Dimitris, Vladu, Adrian (2018). Towards Deep Learning Models Resistant to Adversarial Attacks. International Conference on Learning Representations (ICLR).
Mahajan, Kshiteej, Balasubramanian, Arjun, Singhvi, Arjun, Venkataraman, Shivaram, Akella, Aditya, Phanishayee, Amar, Chawla, Shuchi (2020). Themis: Fair and Efficient GPU Cluster Scheduling. 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20).
Mahmoud, A., Aggarwal, N., Nobbe, A., Vicarte, J. R. S., Adve, S. V., Fletcher, C. W., Frosio, I., Hari, S. K. S. (2020). PyTorchFI: A Runtime Perturbation Tool for DNNs. 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W).
Malkov, Yury A., Yashunin, Dmitry A. (2020). Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence.
Marulli, Fiammetta, Marrone, Stefano, Verde, Laura (2022). Sensitivity of Machine Learning Approaches to Fake and Untrusted Data in Healthcare Domain. Journal of Sensor and Actuator Networks.
Masanet, Eric, Shehabi, Arman, Lei, Nuoa, Smith, Sarah, Koomey, Jonathan (2020). Recalibrating global data center energy-use estimates. Science.
Mattson, Peter, Cheng, Christine, Coleman, Cody, Diamos, Greg, Micikevicius, Paulius, Patterson, David, Tang, Hanlin, Wei, Gu-Yeon, Bailis, Peter, Bittorf, Victor, Brooks, David, Chen, Dehao, Dutta, Debojyoti, Gupta, Udit, Hazelwood, Kim, Hock, Andrew, Huang, Xinyuan, Ike, Atsushi, Jia, Bill, Kang, Daniel, Kanter, David, Kumar, Naveen, Liao, Jeffery, Ma, Guokai, Narayanan, Deepak, Oguntebi, Tayo, Pekhimenko, Gennady, Pentecost, Lillian, Reddi, Vijay Janapa, Robie, Taylor, St. John, Tom, Tabaru, Tsuguchika, Wu, Carole-Jean, Xu, Lingjie, Yamazaki, Masafumi, Young, Cliff, Zaharia, Matei (2020). MLPerf Training Benchmark. Proceedings of Machine Learning and Systems (MLSys).
McCandlish, Sam, Kaplan, Jared, Amodei, Dario, OpenAI Dota Team (2018). An Empirical Model of Large-Batch Training. arXiv preprint arXiv:1812.06162.
McCarthy, J. (1981). Epistemological Problems of Artificial Intelligence. Readings in Artificial Intelligence, 459–465
McMahan, Brendan, Moore, Eider, Ramage, Daniel, Hampson, Seth, y Arcas, Blaise Aguera (2017). Communication-Efficient Learning of Deep Networks from Decentralized Data. International Conference on Artificial Intelligence and Statistics (AISTATS).
Message Passing Interface Forum (1993). MPI. Proceedings of the 1993 ACM/IEEE conference on Supercomputing - Supercomputing ’93.
Message Passing Interface Forum (2015). MPI: A Message-Passing Interface Standard, Version 3.1.
Meta AI (2022). Building the Most Powerful AI Supercomputer: Meta’s AI Research SuperCluster. Meta AI Blog.
Meta AI Research (2022). OPT-175B Training Logbook. Companion repository to the OPT-175B model release.
Meta Engineering (2024). Building Meta’s GenAI Infrastructure. Engineering at Meta Blog.
Micikevicius, Paulius, Stosic, Dusan, Burgess, Neil, Cornea, Marius, Dubey, Pradeep, Grisenthwaite, Richard, Ha, Sangwon, Heinecke, Alexander, Judd, Patrick, Kamalu, John, Mellempudi, Naveen, Oberman, Stuart, Shoeybi, Mohammad, Siu, Michael, Wu, Hao (2022). FP8 Formats for Deep Learning. arXiv preprint arXiv:2209.05433.
Microsoft (2025). Inside the World’s Most Powerful AI Datacenter. The Official Microsoft Blog.
Miller, C. (2019). Lessons learned from hacking a car. IEEE Design & Test.
Miller, Charlie, Valasek, Chris (2015). Remote Exploitation of an Unaltered Passenger Vehicle. Black Hat USA 2015 Whitepaper.
Mironov, I. (2017). Rényi Differential Privacy. 2017 IEEE 30th Computer Security Foundations Symposium (CSF).
Mitchell, Margaret, Wu, Simone, Zaldivar, Andrew, Barnes, Parker, Vasserman, Lucy, Hutchinson, Ben, et al. (2019). Model Cards for Model Reporting. Proceedings of the Conference on Fairness, Accountability, and Transparency, 220–229
Mittal, Radhika, Shpiner, Alexander, Panda, Aurojit, Zahavi, Eitan, Krishnamurthy, Arvind, Ratnasamy, Sylvia, Shenker, Scott (2018). Revisiting Network Support for RDMA. Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication.
Mitzenmacher, M. (2001). The power of two choices in randomized load balancing. IEEE Transactions on Parallel and Distributed Systems.
ML.ENERGY Initiative, Chung, Jae-Won, Gu, Jiachen, Yan, Zhewei, Lo, Tony, Park, Yejin, Chowdhury, Mosharaf (2023). The ML.ENERGY Leaderboard. SymbioticLab, University of Michigan.
Mnih, Volodymyr, Kavukcuoglu, Koray, Silver, David, Rusu, Andrei A., Veness, Joel, Bellemare, Marc G., Graves, Alex, Riedmiller, Martin, Fidjeland, Andreas K., Ostrovski, Georg, Petersen, Stig, Beattie, Charles, Sadik, Amir, Antonoglou, Ioannis, King, Helen, Kumaran, Dharshan, Wierstra, Daan, Legg, Shane, Hassabis, Demis (2015). Human-level control through deep reinforcement learning. Nature.
Mohanram, K., Touba, N. A. (2003). Partial error masking to reduce soft error failure rate in logic circuits. Proceedings. 18th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems.
Monyei, C. G., Jenkins, Kirsten E. H. (2018). Electrons have no identity: Setting right misrepresentations in Google and Apple’s clean energy purchasing. Energy Research & Social Science.
Mukherjee, S. S., Emer, J., Reinhardt, S. K. (2005). The Soft Error Problem: An Architectural Perspective. 11th International Symposium on High-Performance Computer Architecture.
Nabi, Razieh, Shpitser, Ilya (2018). Fair Inference on Outcomes. Proceedings of the AAAI Conference on Artificial Intelligence
Narayanan, Arvind, Shmatikov, Vitaly (2006). How To Break Anonymity of the Netflix Prize Dataset.
Narayanan, Arvind, Shmatikov, Vitaly (2008). Robust De-Anonymization of Large Sparse Datasets. 2008 IEEE Symposium on Security and Privacy (SP 2008).
Narayanan, Deepak, Harlap, Aaron, Phanishayee, Amar, Seshadri, Vivek, Devanur, Nikhil R., Ganger, Gregory R., Gibbons, Phillip B., Zaharia, Matei (2019). PipeDream. Proceedings of the 27th ACM Symposium on Operating Systems Principles.
Narayanan, Deepak, Shoeybi, Mohammad, Casper, Jared, LeGresley, Patrick, Patwary, Mostofa, Korthikanti, Vijay, Vainbrand, Dmitri, Kashinkunti, Prethvi, Bernauer, Julie, Catanzaro, Bryan, Phanishayee, Amar, Zaharia, Matei (2021). Efficient large-scale language model training on GPU clusters using Megatron-LM. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis.
NASA Mars Program Independent Assessment Team (2000). Report on the Loss of the Mars Polar Lander and Deep Space 2 Missions. National Aeronautics and Space Administration.
Nasr, Milad, Shokri, Reza, Houmansadr, Amir (2019). Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-Box Inference Attacks Against Centralized and Federated Learning. 2019 IEEE Symposium on Security and Privacy (SP).
National Transportation Safety Board (2017). Collision Between a Car Operating With Automated Vehicle Control Systems and a Tractor-Semitrailer Truck Near Williston, Florida, May 7, 2016.
National Transportation Safety Board (2019). Collision Between Vehicle Controlled by Developmental Automated Driving System and Pedestrian, Tempe, Arizona, March 18, 2018. National Transportation Safety Board
National Transportation Safety Board (2019). Collision Between Vehicle Controlled by Developmental Automated Driving System and Pedestrian, Tempe, Arizona, March 18, 2018. Report HAR-19/03.
Naumov, Maxim, Mudigere, Dheevatsa, Shi, Hao-Jun Michael, Huang, Jianyu, Sundaraman, Narayanan, Park, Jongsoo, Wang, Xiaodong, Gupta, Udit, Wu, Carole-Jean, Azzolini, Alisson G., Dzhulgakov, Dmytro, Malevich, Andrey, Cherniavskii, Ilia, Lu, Yinghai, Krishnamoorthi, Raghuraman, Yu, Ansha, Kondratenko, Volodymyr, Pereira, Stephanie, Chen, Xianjie, Chen, Wenlin, Rao, Vijay, Jia, Bill, Xiong, Liang, Smelyanskiy, Misha (2019). Deep Learning Recommendation Model for Personalization and Recommendation Systems. arXiv preprint arXiv:1906.00091.
Netflix Technology Blog (2017). Innovating faster on personalization algorithms at Netflix using interleaving. Netflix Tech Blog.
New York State Department of Financial Services (2021). Report on Apple Card Investigation. New York State Department of Financial Services
Ngo, Richard, Chan, Lawrence, Mindermann, Soren (2022). The Alignment Problem from a Deep Learning Perspective. ArXiv preprint
Nguyen, John, Malik, Kshitiz, Zhan, Hongyuan, Yousefpour, Ashkan, Rabbat, Michael, Malek, Mani, Huba, Dzmitry (2021). Federated Learning with Buffered Asynchronous Aggregation. Proceedings of Machine Learning Research (AISTATS).
NVIDIA (2023). NVIDIA DGX SuperPOD: Next Generation Scalable Infrastructure for AI Leadership. Reference architecture RA-11333-001 V11.
NVIDIA (2026). GPUDirect RDMA. CUDA 13.3 documentation.
NVIDIA (2026). NCCL User Guide. NCCL 2.30.7 documentation.
NVIDIA (2026). NVIDIA CUDA Multi-Process Service. NVIDIA Documentation. https://docs.nvidia.com/deploy/mps/index.html
NVIDIA (2026). NVIDIA Quantum-X800 InfiniBand Platform. NVIDIA product documentation.
NVIDIA Corporation (2017). NVIDIA Tesla V100 GPU Architecture. NVIDIA Whitepaper.
NVIDIA Corporation (2020). NVIDIA A100 Tensor Core GPU Architecture. NVIDIA Whitepaper, V1.0.
NVIDIA Corporation (2025). Product Carbon Footprint Summary for NVIDIA HGX H100. NVIDIA Datasheet.
NVIDIA Corporation (2026). CUDA Graphs: CUDA Programming Guide.
Nygard, Michael (2007). Release It!: Design and Deploy Production-Ready Software. Pragmatic Bookshelf.
Obermeyer, Ziad, Powers, Brian, Vogeli, Christine, Mullainathan, Sendhil (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 447–453
Ofqual (2020). Awarding GCSE, AS, A Level, Advanced Extension Awards and Extended Project Qualifications in Summer 2020: Interim Report. Office of Qualifications and Examinations Regulation
Olah, C., Cammarata, N., Schubert, L., Goh, G., Petrov, M., Carter, S. (2020). Zoom In: An Introduction to Circuits. Distill, e00024–001
Oliynyk, Daryna, Mayer, Rudolf, Rauber, Andreas (2023). I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences. ACM Computing Surveys.
Olston, Christopher, Fiedel, Noah, Gorovoy, Kiril, Harmsen, Jeremiah, Lao, Li, Li, Fangwei, Rajashekhar, Vinu, Ramesh, Sukriti, Soyke, Jordan (2017). TensorFlow-Serving: Flexible, High-Performance ML Serving. CoRR.
OpenAI, Achiam, Josh, Adler, Steven, Agarwal, Sandhini, Ahmad, Lama, Akkaya, Ilge, Aleman, Florencia Leoni, Almeida, Diogo, Altenschmidt, Janko, Altman, Sam, Anadkat, Shyamal, Avila, Red, Babuschkin, Igor, Balaji, Suchir, Balcom, Valerie, Baltescu, Paul, Bao, Haiming, Bavarian, Mohammad, Belgum, Jeff, Bello, Irwan, Berdine, Jake, Bernadett-Shapiro, Gabriel, Berner, Christopher, Bogdonoff, Lenny, Boiko, Oleg, Boyd, Madelaine, Brakman, Anna-Luisa, Brockman, Greg, Brooks, Tim, Brundage, Miles, Button, Kevin, Cai, Trevor, Campbell, Rosie, Cann, Andrew, Carey, Brittany, Carlson, Chelsea, Carmichael, Rory, Chan, Brooke, Chang, Che, Chantzis, Fotis, Chen, Derek, Chen, Sully, Chen, Ruby, Chen, Jason, Chen, Mark, Chess, Ben, Cho, Chester, Chu, Casey, Chung, Hyung Won, Cummings, Dave, Currier, Jeremiah, Dai, Yunxing, Decareaux, Cory, Degry, Thomas, Deutsch, Noah, Deville, Damien, Dhar, Arka, Dohan, David, Dowling, Steve, Dunning, Sheila, Ecoffet, Adrien, Eleti, Atty, Eloundou, Tyna, Farhi, David, Fedus, Liam, Felix, Niko, Fishman, Simon Posada, Forte, Juston, Fulford, Isabella, Gao, Leo, Georges, Elie, Gibson, Christian, Goel, Vik, Gogineni, Tarun, Goh, Gabriel, Gontijo-Lopes, Rapha, Gordon, Jonathan, Grafstein, Morgan, Gray, Scott, Greene, Ryan, Gross, Joshua, Gu, Shixiang Shane, Guo, Yufei, Hallacy, Chris, Han, Jesse, Harris, Jeff, He, Yuchen, Heaton, Mike, Heidecke, Johannes, Hesse, Chris, Hickey, Alan, Hickey, Wade, Hoeschele, Peter, Houghton, Brandon, Hsu, Kenny, Hu, Shengli, Hu, Xin, Huizinga, Joost, Jain, Shantanu, Jain, Shawn, Jang, Joanne, Jiang, Angela, Jiang, Roger, Jin, Haozhun, Jin, Denny, Jomoto, Shino, Jonn, Billie, Jun, Heewoo, Kaftan, Tomer, Kaiser, \Lukasz, Kamali, Ali, Kanitscheider, Ingmar, Keskar, Nitish Shirish, Khan, Tabarak, Kilpatrick, Logan, Kim, Jong Wook, Kim, Christina, Kim, Yongjik, Kirchner, Jan Hendrik, Kiros, Jamie, Knight, Matt, Kokotajlo, Daniel, Kondraciuk, \Lukasz, Kondrich, Andrew, Konstantinidis, Aris, Kosic, Kyle, Krueger, Gretchen, Kuo, Vishal, Lampe, Michael, Lan, Ikai, Lee, Teddy, Leike, Jan, Leung, Jade, Levy, Daniel, Li, Chak Ming, Lim, Rachel, Lin, Molly, Lin, Stephanie, Litwin, Mateusz, Lopez, Theresa, Lowe, Ryan, Lue, Patricia, Makanju, Anna, Malfacini, Kim, Manning, Sam, Markov, Todor, Markovski, Yaniv, Martin, Bianca, Mayer, Katie, Mayne, Andrew, McGrew, Bob, McKinney, Scott Mayer, McLeavey, Christine, McMillan, Paul, McNeil, Jake, Medina, David, Mehta, Aalok, Menick, Jacob, Metz, Luke, Mishchenko, Andrey, Mishkin, Pamela, Monaco, Vinnie, Morikawa, Evan, Mossing, Daniel, Mu, Tong, Murati, Mira, Murk, Oleg, Mely, David, Nair, Ashvin, Nakano, Reiichiro, Nayak, Rajeev, Neelakantan, Arvind, Ngo, Richard, Noh, Hyeonwoo, Ouyang, Long, O’Keefe, Cullen, Pachocki, Jakub, Paino, Alex, Palermo, Joe, Pantuliano, Ashley, Parascandolo, Giambattista, Parish, Joel, Parparita, Emy, Passos, Alex, Pavlov, Mikhail, Peng, Andrew, Perelman, Adam, de Avila Belbute Peres, Filipe, Petrov, Michael, de Oliveira Pinto, Henrique Ponde, Michael, Pokorny, Pokrass, Michelle, Pong, Vitchyr H., Powell, Tolly, Power, Alethea, Power, Boris, Proehl, Elizabeth, Puri, Raul, Radford, Alec, Rae, Jack, Ramesh, Aditya, Raymond, Cameron, Real, Francis, Rimbach, Kendra, Ross, Carl, Rotsted, Bob, Roussez, Henri, Ryder, Nick, Saltarelli, Mario, Sanders, Ted, Santurkar, Shibani, Sastry, Girish, Schmidt, Heather, Schnurr, David, Schulman, John, Selsam, Daniel, Sheppard, Kyla, Sherbakov, Toki, Shieh, Jessica, Shoker, Sarah, Shyam, Pranav, Sidor, Szymon, Sigler, Eric, Simens, Maddie, Sitkin, Jordan, Slama, Katarina, Sohl, Ian, Sokolowsky, Benjamin, Song, Yang, Staudacher, Natalie, Such, Felipe Petroski, Summers, Natalie, Sutskever, Ilya, Tang, Jie, Tezak, Nikolas, Thompson, Madeleine B., Tillet, Phil, Tootoonchian, Amin, Tseng, Elizabeth, Tuggle, Preston, Turley, Nick, Tworek, Jerry, Uribe, Juan Felipe Ceron, Vallone, Andrea, Vijayvergiya, Arun, Voss, Chelsea, Wainwright, Carroll, Wang, Justin Jay, Wang, Alvin, Wang, Ben, Ward, Jonathan, Wei, Jason, Weinmann, CJ, Welihinda, Akila, Welinder, Peter, Weng, Jiayi, Weng, Lilian, Wiethoff, Matt, Willner, Dave, Winter, Clemens, Wolrich, Samuel, Wong, Hannah, Workman, Lauren, Wu, Sherwin, Wu, Jeff, Wu, Michael, Xiao, Kai, Xu, Tao, Yoo, Sarah, Yu, Kevin, Yuan, Qiming, Zaremba, Wojciech, Zellers, Rowan, Zhang, Chong, Zhang, Marvin, Zhao, Shengjia, Zheng, Tianhao, Zhuang, Juntang, Zhuk, William, Zoph, Barret (2023). GPT-4 Technical Report. arXiv preprint arXiv:2303.08774.
Oprea, Alina, Singhal, Anoop, Vassilev, Apostol (2022). Poisoning Attacks Against Machine Learning: Can Machine Learning Be Trustworthy? Computer.
Orekondy, Tribhuvanesh, Schiele, Bernt, Fritz, Mario (2019). Knockoff Nets: Stealing Functionality of Black-Box Models. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Organisation for Economic Co-operation and Development (2024). Recommendation of the Council on Artificial Intelligence. OECD Legal Instruments
Ousterhout, John K. (1982). Scheduling Techniques for Concurrent Systems. Proceedings of the 3rd International Conference on Distributed Computing Systems (ICDCS).
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., et al. (2022). Training language models to follow instructions with human feedback. Advances in Neural Information Processing Systems (NeurIPS).
OVHcloud (2021). Strasbourg Datacentre: Latest Information. OVHcloud incident update.
Pan, Sinno, Yang, Qiang (2010). A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering.
Papadimitriou, George, Gizopoulos, Dimitris (2021). Demystifying the System Vulnerability Stack: Transient Fault Effects Across the Layers. 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA).
Papernot, Nicolas, McDaniel, Patrick, Goodfellow, Ian (2016). Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples. arXiv preprint arXiv:1605.07277.
Parrish, Alicia, Kirk, Hannah Rose, Quaye, Jessica, Rastogi, Charvi, Bartolo, Max, Inel, Oana, et al. (2023). Adversarial Nibbler: A Data-Centric Challenge for Improving the Safety of Text-to-Image Models. ArXiv preprint.
Patarasuk, Pitch, Yuan, Xin (2009). Bandwidth optimal all-reduce algorithms for clusters of workstations. Journal of Parallel and Distributed Computing.
Patel, Dylan, Wong, Gerald (2023). GPT-4 Architecture, Infrastructure, Training Dataset, Costs, Vision, MoE. SemiAnalysis Blog.
Patel, Pratyush, Choukse, Esha, Zhang, Chaojie, Shah, Aashaka, Goiri, Íñigo, Maleki, Saeed, Bianchini, Ricardo (2024). Splitwise: Efficient Generative LLM Inference Using Phase Splitting. 2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA), 118–132.
Patterson, David A., Gibson, Garth, Katz, Randy H. (1988). A Case for Redundant Arrays of Inexpensive Disks (RAID). Proceedings of the 1988 ACM SIGMOD International Conference on Management of Data.
Patterson, David, Gonzalez, Joseph, Le, Quoc, Liang, Chen, Munguia, Lluis-Miquel, Rothchild, Daniel, So, David, Texier, Maud, Dean, Jeff (2021). Carbon Emissions and Large Neural Network Training. arXiv preprint arXiv:2104.10350.
Patterson, David, Gonzalez, Joseph, Le, Quoc, Texier, Maud, Dean, Jeff (2022). Carbon-Aware Computing for Sustainable AI. Communications of the ACM.
Perez, Fábio, Ribeiro, Ian (2022). Ignore previous prompt: Attack techniques for language models. arXiv preprint arXiv:2211.09527.
Personal Information Protection Commission, Japan (2023). Act on the Protection of Personal Information. Personal Information Protection Commission, Japan
Peters, D., Calvo, R. A., Ryan, R. M. (2018). Designing for Motivation, Engagement and Wellbeing in Digital Experience. Frontiers in Psychology, 797
Peterson, W. W., Brown, D. T. (1961). Cyclic Codes for Error Detection. Proceedings of the IRE.
Phillips, P. J., Hahn, C. A., Fontana, P. C., Broniatowski, D. A., Przybocki, M. A. (2020). Four Principles of Explainable Artificial Intelligence. Gaithersburg, Maryland
Plank, James S. (1997). A tutorial on Reed-Solomon coding for fault-tolerance in RAID-like systems. Software: Practice and Experience.
Polyzotis, Neoklis, Roy, Sudip, Whang, Steven Euijong, Zinkevich, Martin (2017). Data Management Challenges in Production Machine Learning. Proceedings of the 2017 ACM International Conference on Management of Data.
Pont, Michael J, Ong, Royan HL (2002). Using watchdog timers to improve the reliability of single-processor embedded systems: Seven new patterns and a case study. Proceedings of the First Nordic Conference on Pattern Languages of Programs.
Pope, Reiner, Douglas, Sholto, Chowdhery, Aakanksha, Devlin, Jacob, Bradbury, James, Heek, Jonathan, Xiao, Kefan, Agrawal, Shivani, Dean, Jeff (2023). Efficiently Scaling Transformer Inference. Proceedings of Machine Learning and Systems (MLSys).
Prakash, Shvetank, Stewart, Matthew, Banbury, Colby, Mazumder, Mark, Warden, Pete, Plancher, Brian, Janapa Reddi, Vijay (2023). Is TinyML Sustainable? Assessing the Environmental Impacts of Machine Learning on Microcontrollers. arXiv preprint arXiv:2301.11899.
Present, Elaina, Gagnon, Pieter, Wilson, Eric, Merket, Noel, White, Philip, Horowitz, Scott (2024). Choosing the Best Carbon Factor for the Job: Exploring Available Carbon Emissions Factors and the Impact of Factor Selection.
PyTorch Contributors (2026). Distributed Checkpoint: torch.distributed.checkpoint.
PyTorch Contributors (2026). Torch Distributed Elastic Rendezvous. PyTorch documentation.
PyTorch Contributors (2026). torchrun (Elastic Launch). PyTorch documentation.
Qiao, Aurick, Choe, Sang Keun, Subramanya, Suhas Jayaram, Neiswanger, Willie, Ho, Qirong, Zhang, Hao, Ganger, Gregory R., Xing, Eric P. (2021). Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21).
Quaye, J., Parrish, A., Inel, O., Rastogi, C., Kirk, H. R., Kahng, M., et al. (2024). Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-To-Image Generation. The 2024 ACM Conference on Fairness, Accountability, and Transparency.
Quiñonero-Candela, Joaquin, Sugiyama, Masashi, Schwaighofer, Anton, Lawrence, Neil D. (eds.) (2009). Dataset Shift in Machine Learning. The MIT Press.
Radovanovic, Ana, Koningstein, Ross, Schneider, Ian, Chen, Bokan, Duarte, Alexandre, Roy, Binz, Xiao, Diyue, Haridasan, Maya, Hung, Patrick, Care, Nick, Talukdar, Saurav, Mullen, Eric, Smith, Kendal, Cottman, MariEllen, Cirne, Walfredo (2021). Carbon-Aware Computing for Datacenters. arXiv preprint arXiv:2106.11750.
Rafailov, Rafael, Sharma, Archit, Mitchell, Eric, Ermon, Stefano, Manning, Christopher D., Finn, Chelsea (2023). Direct Preference Optimization: Your Language Model Is Secretly a Reward Model. Advances in Neural Information Processing Systems (NeurIPS).
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., Liu, P. (2020). Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. Journal of Machine Learning Research.
Rajbhandari, Samyam, Rasley, Jeff, Ruwase, Olatunji, He, Yuxiong (2020). ZeRO: Memory Optimizations Toward Training Trillion Parameter Models. SC20: International Conference for High Performance Computing, Networking, Storage and Analysis.
Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., Sutskever, I. (2021). Zero-Shot Text-to-Image Generation. Proceedings of the 38th International Conference on Machine Learning (ICML 2021), PMLR 139, 8821–8831.
Rashid, Layali, Pattabiraman, Karthik, Gopalakrishnan, Sathish (2012). Intermittent Hardware Errors Recovery: Modeling and Evaluation. 2012 Ninth International Conference on Quantitative Evaluation of Systems.
Rashid, Layali, Pattabiraman, Karthik, Gopalakrishnan, Sathish (2015). Characterizing the Impact of Intermittent Hardware Faults on Programs. IEEE Transactions on Reliability.
Rasley, Jeff, Rajbhandari, Samyam, Ruwase, Olatunji, He, Yuxiong (2020). DeepSpeed: System Optimizations Enable Training Deep Learning Models with Over 100 Billion Parameters. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.
Ray Project (2026). Ray Train: Handling Failures and Node Preemption. Ray documentation.
Reagen, B., Gupta, U., Pentecost, L., Whatmough, P., Lee, S. K., Mulholland, N., Brooks, D., Wei, G.-Y. (2018). Ares: A framework for quantifying the resilience of deep neural networks. 2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC).
Rebuffi, Sylvestre-Alvise, Bilen, Hakan, Vedaldi, Andrea (2017). Learning multiple visual domains with residual adapters. Advances in Neural Information Processing Systems (NeurIPS).
Reddi, Vijay Janapa, Cheng, Christine, Kanter, David, Mattson, Peter, Schmuelling, Guenther, Wu, Carole-Jean, Anderson, Brian, Breughe, Maximilien, Charlebois, Mark, Chou, William, Chukka, Ramesh, Coleman, Cody, Davis, Sam, Deng, Pan, Diamos, Greg, Duke, Jared, Fick, Dave, Gardner, J. Scott, Hubara, Itay, Idgunji, Sachin, Jablin, Thomas B., Jiao, Jeff, John, Tom St., Kanwar, Pankaj, Lee, David, Liao, Jeffery, Lokhmotov, Anton, Massa, Francisco, Meng, Peng, Micikevicius, Paulius, Osborne, Colin, Pekhimenko, Gennady, Rajan, Arun Tejusve Raghunath, Sequeira, Dilip, Sirasao, Ashish, Sun, Fei, Tang, Hanlin, Thomson, Michael, Wei, Frank, Wu, Ephrem, Xu, Lingjie, Yamada, Koichi, Yu, Bing, Yuan, George, Zhong, Aaron, Zhang, Peizhao, Zhou, Yuchen (2019). MLPerf Inference Benchmark. 2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture (ISCA).
Reddi, Vijay Janapa, Gupta, Meeta Sharma (2013). Resilient Architecture Design for Voltage Variation. Springer International Publishing.
Reed, I. S., Solomon, G. (1960). Polynomial Codes Over Certain Finite Fields. Journal of the Society for Industrial and Applied Mathematics.
Regenscheid, Andrew (2018). Platform Firmware Resiliency Guidelines. National Institute of Standards and Technology.
Reis, G. A., Chang, J., Vachharajani, N., Rangan, R., August, D. I. (2005). SWIFT: Software Implemented Fault Tolerance. International Symposium on Code Generation and Optimization.
Reuters (2023). Human-Machine Teams Driven by AI Are About to Reshape Warfare. Reuters news article
Reuters (2024). Water-guzzling chipmaker TSMC and drought-plagued Arizona.
Rhodes, Christopher (2019). Endangered Elements, Critical Raw Materials and Conflict Minerals. Science Progress.
Ribeiro, M. H., Ottoni, R., West, R., Almeida, V. A. F., Meira, Jr. (2020). Auditing radicalization pathways on YouTube. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 131–141
Ribeiro, Marco Tulio, Singh, Sameer, Guestrin, Carlos (2016). Why Should I Trust You?: Explaining the Predictions of Any Classifier. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1135–1144
Robertson, J., Riley, M. (2018). The Big Hack: How China Used a Tiny Chip to Infiltrate U.S. Companies - Bloomberg.
Rodio, Angelo, Neglia, Giovanni (2024). FedStale: leveraging stale client updates in federated learning. Frontiers in Artificial Intelligence and Applications (ECAI 2024).
Rolnick, David, Ahuja, Arun, Schwarz, Jonathan, Lillicrap, Timothy, Wayne, Greg (2019). Experience Replay for Continual Learning. Advances in Neural Information Processing Systems (NeurIPS).
Rubin, Donald B. (1980). Randomization Analysis of Experimental Data: The Fisher Randomization Test Comment. Journal of the American Statistical Association.
Rudin, C. (2019). Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence, 206–215
Russell, Jon (2018). Strava Says It Will Simplify Privacy Settings and Review App Features After Exposing Military Bases. TechCrunch.
Russell, S. (2021). Human-Compatible Artificial Intelligence. Human-like machine intelligence, 3–23
Rusu, A. A., Rabinowitz, N. C., Desjardins, G., Soyer, H., Kirkpatrick, J., Kavukcuoglu, K., Pascanu, R., Hadsell, R. (2016). Progressive Neural Networks. arXiv preprint arXiv:1606.04671.
Ryan, R. M., Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 68–78
Saltzer, J. H., Schroeder, M. D. (1975). The Protection of Information in Computer Systems. Proceedings of the IEEE.
Sandler, Mark, Howard, Andrew, Zhu, Menglong, Zhmoginov, Andrey, Chen, Liang-Chieh (2018). MobileNetV2: Inverted Residuals and Linear Bottlenecks. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
Sangchoolie, Behrooz, Pattabiraman, Karthik, Karlsson, Johan (2017). One Bit Is (Not) Enough: An Empirical Study of the Impact of Single and Multiple Bit-Flip Errors. 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN).
Sanh, Victor, Debut, Lysandre, Chaumond, Julien, Wolf, Thomas (2019). DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. 5th Workshop on Energy Efficient Machine Learning and Cognitive Computing at NeurIPS 2019.
Schaeffer, Rylan, Miranda, Brando, Koyejo, Sanmi (2023). Are Emergent Abilities of Large Language Models a Mirage?. Advances in Neural Information Processing Systems (NeurIPS).
Schafer, Mike S. (2023). The Notorious GPT: science communication in the age of artificial intelligence. Journal of Science Communication, Y02
Schmidt, Victor, Goyal, Kamal, Joshi, Aditya, Feld, Boris, Conell, Liam, Laskaris, Nikolas, Blank, Doug, Wilson, Jonathan, Friedler, Sorelle, Luccioni, Sasha (2021). CodeCarbon: Estimate and Track Carbon Emissions from Machine Learning Computing. Zenodo software citation.
Schmuck, Frank, Haskin, Roger (2002). GPFS: A Shared-Disk File System for Large Computing Clusters. Proceedings of the USENIX Conference on File and Storage Technologies (FAST ’02).
Schneider Electric (2024). Schneider Electric Announces New Solutions to Address the Energy and Sustainability Challenges Spurred by AI.
Schroeder, Bianca, Pinheiro, Eduardo, Weber, Wolf-Dietrich (2009). DRAM errors in the wild. ACM SIGMETRICS Performance Evaluation Review.
Schulman, John, Wolski, Filip, Dhariwal, Prafulla, Radford, Alec, Klimov, Oleg (2017). Proximal Policy Optimization Algorithms. arXiv preprint arXiv:1707.06347.
Schwan, P. (2003). Lustre: Building a File System for 1,000-node Clusters. Proceedings of the 2003 Linux Symposium.
Schwartz, Roy, Dodge, Jesse, Smith, Noah A., Etzioni, Oren (2020). Green AI. Communications of the ACM.
Sculley, D., Holt, Gary, Golovin, Daniel, Davydov, Eugene, Phillips, Todd, Ebner, Dietmar, Chaudhary, Vinay, Young, Michael, Crespo, Jean-François, Dennison, Dan (2015). Hidden Technical Debt in Machine Learning Systems. Advances in Neural Information Processing Systems (NeurIPS).
Seide, Frank, Fu, Hao, Droppo, Jasha, Li, Gang, Yu, Dong (2014). 1-Bit Stochastic Gradient Descent and Its Application to Data-Parallel Distributed Training of Speech DNNs. Interspeech 2014.
Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D. (2017). Grad-CAM: Visual Explanations From Deep Networks via Gradient-Based Localization. 2017 IEEE International Conference on Computer Vision (ICCV), 618–626
Seong, N. H., Woo, D. H., Srinivasan, V., Rivers, J. A., Lee, H.-H. S. (2010). SAFER: Stuck-At-Fault Error Recovery for Memories. 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture.
Sergeev, Alexander, Del Balso, Mike (2018). Horovod: fast and easy distributed deep learning in TensorFlow. CoRR.
Sevilla, Jaime, Heim, Lennart, Ho, Anson, Besiroglu, Tamay, Hobbhahn, Marius, Villalobos, Pablo (2022). Compute Trends Across Three Eras of Machine Learning. 2022 International Joint Conference on Neural Networks (IJCNN).
Shafahi, Ali, Huang, W., Najibi, Mahyar, Suciu, Octavian, Studer, Christoph, Dumitras, Tudor, et al. (2018). Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks. Advances in Neural Information Processing Systems.
Shafahi, Ali, Najibi, Mahyar, Ghiasi, Amin, Xu, Zheng, Dickerson, John, Studer, Christoph, Davis, Larry, Taylor, Gavin, Goldstein, Tom (2019). Adversarial Training for Free!. arXiv preprint arXiv:1904.12843.
Shalev-Shwartz, S. (2012). Online Learning and Online Convex Optimization. Foundations and Trends in Machine Learning.
Shalev-Shwartz, Shai, Shammah, Shaked, Shashua, Amnon (2017). On a Formal Model of Safe and Scalable Self-driving Cars. ArXiv preprint
Shallue, Christopher J., Lee, Jaehoon, Antognini, Joseph, Sohl-Dickstein, Jascha, Frostig, Roy, Dahl, George E. (2019). Measuring the Effects of Data Parallelism on Neural Network Training. Journal of Machine Learning Research.
Shazeer et al. (2017). Outrageously large neural networks: The sparsely-gated mixture-of-experts layer. International Conference on Learning Representations (ICLR).
Sheaffer, J. W., Luebke, D. P., Skadron, K. (2007). A hardware redundancy and recovery mechanism for reliable scientific computation on graphics processors. Graphics Hardware.
Sheng, Ying, Cao, Shiyi, Li, Dacheng, Hooper, Coleman, Chen, Shuo, Jiang, Daxin, Rodriguez, Christopher, Keutzer, Kurt, Gonzalez, Joseph E., Liang, Percy, Stoica, Ion (2024). S-LoRA: Serving Thousands of Concurrent LoRA Adapters. Proceedings of the 7th Conference on Machine Learning and Systems (MLSys).
Shewhart, Walter A. (1931). Economic Control of Quality of Manufactured Product. D. Van Nostrand Company.
Shneiderman, B. (2020). Bridging the Gap Between Ethics and Practice. ACM Transactions on Interactive Intelligent Systems, 1–31
Shneiderman, B. (2022). Human-centered AI. Oxford University Press
Shoeybi, Mohammad, Patwary, Mostofa, Puri, Raul, LeGresley, Patrick, Casper, Jared, Catanzaro, Bryan (2019). Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism. arXiv preprint arXiv:1909.08053.
Shokri, Reza, Stronati, Marco, Song, Congzheng, Shmatikov, Vitaly (2017). Membership Inference Attacks Against Machine Learning Models. 2017 IEEE Symposium on Security and Privacy (SP).
Shumailov, Ilia, Shumaylov, Zakhar, Zhao, Yiren, Papernot, Nicolas, Anderson, Ross, Gal, Yarin (2024). AI Models Collapse When Trained on Recursively Generated Data. Nature.
Shvachko, Konstantin, Kuang, Hairong, Radia, Sanjay, Chansler, Robert (2010). The Hadoop Distributed File System. 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST).
Sigelman, Benjamin H, Barroso, Luiz André, Burrows, Mike, Stephenson, Pat, Plakal, Manoj, Beaver, Donald, Jaspan, Saul, Shanbhag, Chandan (2010). Dapper, a large-scale distributed systems tracing infrastructure.
Sigler, Eric (2021). Scaling Kubernetes to 7,500 Nodes. OpenAI Blog.
Skorobogatov, S. (2009). Local heating attacks on Flash memory devices. 2009 IEEE International Workshop on Hardware-Oriented Security and Trust.
Skorobogatov, S. P., Anderson, R. J. (2003). Optical Fault Induction Attacks. Cryptographic Hardware and Embedded Systems - CHES 2002.
Slade, G. (2007). Made to Break. Harvard University Press.
Song, Liwei, Shokri, Reza, Mittal, Prateek (2019). Privacy risks of securing machine learning models against adversarial examples. Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security.
Spotify Engineering (2019). The winding road to better machine learning infrastructure through TensorFlow Extended and Kubeflow. Spotify Engineering Blog.
Sridharan, V., DeBardeleben, N., Blanchard, S., Ferreira, K. B., Stearley, J., Shalf, J., Gurumurthi, S. (2015). Memory Errors in Modern Systems. ACM SIGPLAN Notices.
Srivastava, Nitish, Hinton, Geoffrey, Krizhevsky, Alex, Sutskever, Ilya, Salakhutdinov, Ruslan (2014). Dropout: a simple way to prevent neural networks from overfitting. Journal of Machine Learning Research.
Stahel, Walter (2016). The circular economy. Nature.
Statista (2022). Number of Internet of Things (IoT) connected devices worldwide from 2019 to 2030.
Steck, Harald, Baltrunas, Linas, Elahi, Ehtsham, Liang, Dawen, Raimond, Yves, Basilico, Justin (2021). Deep learning for recommender systems: A Netflix case study. AI Magazine.
Stich, S. U., Cordonnier, J.-B., Jaggi, M. (2018). Sparsified SGD with Memory. Advances in Neural Information Processing Systems.
Stich, Sebastian U. (2019). Local SGD Converges Fast and Communicates Little. International Conference on Learning Representations (ICLR).
Stoica, Ion, Song, Dawn, Popa, Raluca Ada, Patterson, David, Mahoney, Michael W., Katz, Randy, et al. (2017). A Berkeley View of Systems Challenges for AI. arXiv preprint arXiv:1712.05855
Strubell, Emma, Ganesh, Ananya, McCallum, Andrew (2019). Energy and Policy Considerations for Deep Learning in NLP. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.
Subramanya, Suhas Jayaram, Devvrit, Fnu, Simhadri, Harsha Vardhan, Krishnawamy, Ravishankar, Kadekodi, Rohan (2019). DiskANN: Fast Accurate Billion-point Nearest Neighbor Search on a Single Node. Advances in Neural Information Processing Systems (NeurIPS).
Sudhakar, Soumya, Sze, Vivienne, Karaman, Sertac (2023). Data Centers on Wheels: Emissions From Computing Onboard Autonomous Vehicles. IEEE Micro.
Sundararajan, Mukund, Taly, Ankur, Yan, Qiqi (2017). Axiomatic Attribution for Deep Networks. International Conference on Machine Learning (ICML), 3319–3328
Sutton, Richard S. (2019). The Bitter Lesson. incompleteideas.net.
Sweeney, Latanya (2002). K-ANONYMITY: A MODEL for PROTECTING PRIVACY. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 557–570
Szegedy, Christian, Zaremba, Wojciech, Sutskever, Ilya, Bruna, Joan, Erhan, Dumitru, Goodfellow, Ian, et al. (2013). Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199.
Tabassi, Elham (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). National Institute of Standards and Technology
Tan, Mingxing, Le, Quoc V (2019). EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. International Conference on Machine Learning (ICML).
Tang, Hanlin, Gan, Shaoduo, Awan, Ammar Ahmad, Rajbhandari, Samyam, Li, Conglong, Lian, Xiangru, Liu, Ji, Zhang, Ce, He, Yuxiong (2021). 1-bit Adam: Communication efficient large-scale training with Adam’s convergence speed. Proceedings of the 38th International Conference on Machine Learning (ICML).
Thakur, Rajeev, Rabenseifner, Rolf, Gropp, William (2005). Optimization of Collective Communication Operations in MPICH. The International Journal of High Performance Computing Applications.
The Green Grid (2007). Green Grid Data Center Power Efficiency Metrics: PUE and DCIE.
The Green Grid (2011). Water Usage Effectiveness (WUE): A Green Grid Data Center Sustainability Metric.
The New York Times (2017). Google’s Self-Driving Car Company Sues Uber Over Trade Secrets. The New York Times.
The U-Boot Project (2026). Das U-Boot.
The U-Boot Project (2026). UEFI on U-Boot.
Thompson, N. C., Greenewald, K., Lee, K., Manso, G. F. (2021). Deep Learning’s Diminishing Returns: The Cost of Improvement Is Becoming Unsustainable. IEEE Spectrum, 58(10).
Tillet, Philippe, Kung, H. T., Cox, David (2019). Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations. Proceedings of the 3rd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages.
Tiwari, Devesh, Gupta, Saurabh, Rogers, James, Maxwell, Don, Rech, Paolo, Vazhkudai, Sudharshan, Oliveira, Daniel, Londo, Dave, DeBardeleben, Nathan, Navaux, Philippe, Carro, Luigi, Bland, Arthur (2015). Understanding GPU Errors on Large-Scale HPC Systems and the Implications for System Design and Operation. 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA).
Touvron, Hugo, Martin, Louis, Stone, Kevin, Albert, Peter, Almahairi, Amjad, Babaei, Yasmine, Bashlykov, Nikolay, Batra, Soumya, Bhargava, Prajjwal, Bhosale, Shruti, Bikel, Dan, Blecher, Lukas, Ferrer, Cristian Canton, Chen, Moya, Cucurull, Guillem, Esiobu, David, Fernandes, Jude, Fu, Jeremy, Fu, Wenyin, Fuller, Brian, Gao, Cynthia, Goswami, Vedanuj, Goyal, Naman, Hartshorn, Anthony, Hosseini, Saghar, Hou, Rui, Inan, Hakan, Kardas, Marcin, Kerkez, Viktor, Khabsa, Madian, Kloumann, Isabel, Korenev, Artem, Koura, Punit Singh, Lachaux, Marie-Anne, Lavril, Thibaut, Lee, Jenya, Liskovich, Diana, Lu, Yinghai, Mao, Yuning, Martinet, Xavier, Mihaylov, Todor, Mishra, Pushkar, Molybog, Igor, Nie, Yixin, Poulton, Andrew, Reizenstein, Jeremy, Rungta, Rashi, Saladi, Kalyan, Schelten, Alan, Silva, Ruan, Smith, Eric Michael, Subramanian, Ranjan, Tan, Xiaoqing Ellen, Tang, Binh, Taylor, Ross, Williams, Adina, Kuan, Jian Xiang, Xu, Puxin, Yan, Zheng, Zarov, Iliyan, Zhang, Yuchen, Fan, Angela, Kambadur, Melanie, Narang, Sharan, Rodriguez, Aurelien, Stojnic, Robert, Edunov, Sergey, Scialom, Thomas (2023). Llama 2: Open Foundation and Fine-Tuned Chat Models. arXiv preprint arXiv:2307.09288.
Tramèr, Florian, Kurakin, Alexey, Papernot, Nicolas, Goodfellow, Ian, Boneh, Dan, McDaniel, Patrick (2017). Ensemble Adversarial Training: Attacks and Defenses. International Conference on Learning Representations.
Tramèr, Florian, Zhang, Fan, Juels, Ari, Reiter, Michael K, Ristenpart, Thomas (2016). Stealing machine learning models via prediction APIs. 25th USENIX Security Symposium (USENIX Security 16).
Tran, Brandon, Li, Jerry, Madry, Aleksander (2018). Spectral Signatures in Backdoor Attacks. Advances in Neural Information Processing Systems (NeurIPS).
Trusted Computing Group (2018). Hardware requirements for a Device Identifier Composition Engine. Trusted Computing Group.
Tsai, Min-Jen, Lin, Ping-Yi, Lee, Ming-En (2023). Adversarial Attacks on Medical Image Classification. Cancers.
Tsai, Timothy, Hari, Siva Kumar Sastry, Sullivan, Michael, Villa, Oreste, Keckler, Stephen W. (2021). NVBitFI: Dynamic Fault Injection for GPUs. 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN).
U.S. Department of Health and Human Services (2003). Summary of the HIPAA Privacy Rule.
U.S. Department of Health and Human Services (2005). Summary of the HIPAA Security Rule.
U.S. Department of Health and Human Services (2026). Annual Civil Monetary Penalties Inflation Adjustment. Federal Register.
U.S. Department of Health and Human Services (2026). The HIPAA Security Rule. HHS.gov guidance.
Uddin, Mueen, Rahman, Azizah Abdul (2012). Energy efficiency and low carbon enabler green IT framework for data centers considering green metrics. Renewable and Sustainable Energy Reviews.
Ultra Ethernet Consortium (2025). Ultra Ethernet Specification v1.0. Ultra Ethernet Consortium.
UNESCO (2022). Recommendation on the Ethics of Artificial Intelligence. UNESCO
United States Congress (2022). CHIPS and Science Act of 2022 (Public Law 117-167). Public Law 117-167, 136 Stat. 1366.
Uptime Institute (2022). Uptime Institute Global Data Center Survey 2022.
Uptime Institute (2026). Tier Classification System. Uptime Institute web page.
Valiant, Leslie G. (1990). A bridging model for parallel computation. Communications of the ACM.
van Wynsberghe, Aimee (2021). Sustainable AI: AI for Sustainability and the Sustainability of AI. AI and Ethics.
Velazco, Raoul, Foucard, Gilles, Peronnard, Paul (2010). Combining Results of Accelerated Radiation Tests and Fault Injections to Predict the Error Rate of an Application Implemented in SRAM-Based FPGAs. IEEE Transactions on Nuclear Science.
Villalobos, Pablo, Ho, Anson, Sevilla, Jaime, Besiroglu, Tamay, Heim, Lennart, Hobbhahn, Marius (2022). Will we run out of data? Limits of LLM scaling based on human-generated data. arXiv preprint arXiv:2211.04325.
Vinuesa, Ricardo, Azizpour, Hossein, Leite, Iolanda, Balaam, Madeline, Dignum, Virginia, Domisch, Sami, Felländer, Anna, Langhans, Simone Daniela, Tegmark, Max, Fuso Nerini, Francesco (2020). The Role of Artificial Intelligence in Achieving the Sustainable Development Goals. Nature Communications.
Vogels, Thijs, Karimireddy, Sai Praneeth, Jaggi, Martin (2019). PowerSGD: Practical low-rank gradient compression for distributed optimization. Advances in Neural Information Processing Systems (NeurIPS).
von Neumann, John (1928). Zur Theorie Der Gesellschaftsspiele. Mathematische Annalen.
Wachter, Sandra, Mittelstadt, Brent, Russell, Chris (2017). Counterfactual Explanations Without Opening the Black Box: Automated Decisions and the GDPR. SSRN Electronic Journal, 841
Wan, Z., Anwar, A., Hsiao, Y.-S., Jia, T., Reddi, V. J., Raychowdhury, A. (2021). Analyzing and Improving Fault Tolerance of Learning-Based Navigation Systems. 2021 58th ACM/IEEE Design Automation Conference (DAC).
Wang, Jianyu, Charles, Zachary, Xu, Zheng, Joshi, Gauri, McMahan, H. Brendan, Arcas, Blaise Aguera, Al-Shedivat, Maruan, Andrew, Galen, Avestimehr, Salman, Daly, Katharine, Data, Deepesh, Diggavi, Suhas, Eichner, Hubert, Gadhikar, Advait, Garrett, Zachary, Girgis, Antonious M., Hanzely, Filip, Hard, Andrew, He, Chaoyang, Horvath, Samuel, Huo, Zhouyuan, Ingerman, Alex, Jaggi, Martin, Javidi, Tara, Kairouz, Peter, Kale, Satyen, Karimireddy, Sai Praneeth, Konecny, Jakub, Koyejo, Sanmi, Li, Tian, Liu, Luyang, Mohri, Mehryar, Qi, Hang, Reddi, Sashank J., Richtarik, Peter, Singhal, Karan, Smith, Virginia, Soltanolkotabi, Mahdi, Song, Weikang, Suresh, Ananda Theertha, Stich, Sebastian U., Talwalkar, Ameet, Wang, Hongyi, Woodworth, Blake, Wu, Shanshan, Yu, Felix X., Yuan, Honglin, Zaheer, Manzil, Zhang, Mi, Zhang, Tong, Zheng, Chunxiang, Zhu, Chen, Zhu, Wennan (2021). A Field Guide to Federated Optimization. arXiv preprint arXiv:2107.06917.
Wang, Y., Yao, Q., Kwok, J. T., Ni, L. M. (2020). Generalizing From a Few Examples. ACM Computing Surveys.
Warden, Pete (2018). Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition. arXiv preprint arXiv:1804.03209.
Warden, Pete, Situnayake, Daniel (2020). TinyML: Machine learning with TensorFlow Lite on Arduino and ultra-low-power microcontrollers. O’Reilly Media.
Wei, Jason, Tay, Yi, Bommasani, Rishi, Raffel, Colin, Zoph, Barret, Borgeaud, Sebastian, Yogatama, Dani, Bosma, Maarten, Zhou, Denny, Metzler, Donald, Chi, Ed H., Hashimoto, Tatsunori, Vinyals, Oriol, Liang, Percy, Dean, Jeff, Fedus, William (2022). Emergent Abilities of Large Language Models. Transactions on Machine Learning Research.
Widmer, Gerhard, Kubat, Miroslav (1996). Learning in the Presence of Concept Drift and Hidden Contexts. Machine Learning.
Wiener, N. (1960). Some Moral and Technical Consequences of Automation. Science, 1355–1358
Williams et al. (2009). Roofline. Communications of the ACM.
Wongpanich, A., Oguntebi, T., Baiocchi Paredes, J., Wang, Y. E., Phothilimthana, P. M., Mitra, R., Zhou, Z., Kumar, N., Reddi, V. J. (2025). Machine Learning Fleet Efficiency: Analyzing and Optimizing Large-Scale Google TPU Systems with ML Productivity Goodput.
World Resources Institute and World Business Council for Sustainable Development (2023). Greenhouse Gas Protocol: Corporate Standard.
Wright, Peter, Greengrass, Paul (1987). Spycatcher: The Candid Autobiography of a Senior Intelligence Officer. Viking Penguin.
Wulf and McKee (1995). Hitting the memory wall. ACM SIGARCH Computer Architecture News.
Xiao, Guangxuan, Lin, Ji, Seznec, Mickaël, Wu, Hao, Demouth, Julien, Han, Song (2023). SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models. International Conference on Machine Learning (ICML).
Xiao, Wencong, Bhardwaj, Romil, Ramjee, Ramachandran, Sivathanu, Muthian, Kwatra, Nipun, Han, Zhenhua, Patel, Prabal, Peng, Xuan, Zhao, Hanyu, Zhang, Quanlu, Yang, Fan, Li, Lidong (2018). Gandiva: Introspective Cluster Scheduling for Deep Learning. 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18).
Xu, Dianlei, Li, Tong, Li, Yong, Su, Xiang, Tarkoma, Sasu, Jiang, Tao, Crowcroft, Jon, Hui, Pan (2020). Edge Intelligence: Architectures, Challenges, and Applications. arXiv preprint arXiv:2003.12172.
Yao, Andrew C. (1982). Protocols for secure computations. 23rd Annual Symposium on Foundations of Computer Science (sfcs 1982).
Yeh, Y.C. (1996). Triple-triple redundant 777 primary flight computer. 1996 IEEE Aerospace Applications Conference. Proceedings.
Yin, Dong, Chen, Yudong, Ramchandran, Kannan, Bartlett, Peter (2018). Byzantine-robust distributed learning: Towards optimal statistical rates. International Conference on Machine Learning (ICML).
Yin, Shuang, Zhou, Xiang, Lam, Cedric (2022). FEC Requirements for 800GbE/1.6TbE Optics. IEEE 802.3df Task Force.
Yoo, A. B., Jette, M. A., Grondona, M. (2003). SLURM: Simple Linux Utility for Resource Management. Job Scheduling Strategies for Parallel Processing.
You, Jie, Chung, Jae-Won, Chowdhury, Mosharaf (2023). Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training. 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23).
You, Y., Li, J., Reddi, S., Hseu, J., Kumar, S., Bhojanapalli, S., Song, X., Demmel, J., Keutzer, K., Hsieh, C.-J. (2020). Large Batch Optimization for Deep Learning: Training BERT in 76 minutes. International Conference on Learning Representations (ICLR).
You, Yang, Gitman, Igor, Ginsburg, Boris (2017). Large Batch Training of Convolutional Networks. arXiv preprint arXiv:1708.03888.
Young, John W. (1974). A first order approximation to the optimum checkpoint interval. Communications of the ACM.
Yu, Gyeong-In, Jeong, Joo Seong, Kim, Geon-Woo, Kim, Soojeong, Chun, Byung-Gon (2022). Orca: A Distributed Serving System for Transformer-Based Generative Models. 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22), 521–538.
Yurdakul, Bilal, Naranjo, Joshua (2020). Statistical properties of the population stability index. The Journal of Risk Model Validation.
Zafrir, Ofir, Boudoukh, Guy, Izsak, Peter, Wasserblat, Moshe (2019). Q8BERT: Quantized 8Bit BERT. 2019 Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing (EMC2-NIPS).
Zaharia, M., Xin, R. S., Wendell, P., Das, T., Armbrust, M., Dave, A., Meng, X., Rosen, J., Venkataraman, S., Franklin, M. J., Ghodsi, A., Gonzalez, J., Shenker, S., Stoica, I. (2016). Apache Spark. Communications of the ACM.
Zaharia, Matei, Chen, Andrew, Davidson, Aaron, Ghodsi, Ali, Hong, Sue Ann, Konwinski, Andy, Murching, Siddharth, Nykodym, Tomas, Ogilvie, Paul, Parkhe, Mani, Xie, Fen, Zumar, Corey (2018). Accelerating the Machine Learning Lifecycle with MLflow. IEEE Data Engineering Bulletin.
Zhang, Jeff Jun, Gu, Tianyu, Basu, Kanad, Garg, Siddharth (2018). Analyzing and mitigating the impact of permanent faults on a systolic array based neural network accelerator. 2018 IEEE 36th VLSI Test Symposium (VTS).
Zhang, Jeff, Rangineni, Kartheek, Ghodsi, Zahra, Garg, Siddharth (2018). ThUnderVolt: Enabling Aggressive Voltage Underscaling and Timing Error Resilience for Energy Efficient Deep Learning Accelerators. 2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC).
Zhang, Susan, Roller, Stephen, Goyal, Naman, Artetxe, Mikel, Chen, Moya, Chen, Shuohui, Dewan, Christopher, Diab, Mona, Li, Xian, Lin, Xi, Mihaylov, Todor, Ott, Myle, Shleifer, Sam, Shuster, Kurt, Simig, Daniel, Koura, Punit Singh, Sridhar, Anjali, Wang, Tianlu, Zettlemoyer, Luke (2022). OPT: Open Pre-trained Transformer Language Models. arXiv preprint arXiv:2205.01068.
Zhao, M., Suh, G. E. (2018). FPGA-Based Remote Power Side-Channel Attacks. 2018 IEEE Symposium on Security and Privacy (SP).
Zhao, Yanli, Gu, Andrew, Varma, Rohan, Luo, Liang, Huang, Chien-Chin, Xu, Min, Wright, Less, Shojanazeri, Hamid, Ott, Myle, Shleifer, Sam, Desmaison, Alban, Balioglu, Can, Damania, Pritam, Nguyen, Bernard, Chauhan, Geeta, Hao, Yuchen, Mathews, Ajit, Li, Shen (2023). PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel. Proceedings of the VLDB Endowment.
Zhao, Yue, Li, Meng, Lai, Liangzhen, Suda, Naveen, Civin, Damon, Chandra, Vikas (2018). Federated Learning with Non-IID Data. CoRR.
Zhong, Yinmin, Liu, Shengyu, Chen, Junda, Hu, Jianbo, Zhu, Yibo, Liu, Xuanzhe, Jin, Xin, Zhang, Hao (2024). DistServe: Disaggregating Prefill and Decoding for Goodput-Optimized Large Language Model Serving. 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI 24).
Zhu, Ligeng, Liu, Zhijian, Han, Song (2019). Deep Leakage from Gradients. Advances in Neural Information Processing Systems (NeurIPS).
Zhu, Y., Eran, H., Firestone, D., Guo, C., Lipshteyn, M., Liron, Y., Padhye, J., Raindel, S., Yahia, M. H., Zhang, M. (2015). Congestion Control for Large-Scale RDMA Deployments. ACM SIGCOMM Computer Communication Review, 45(4).
Zhu, Y., Eran, H., Firestone, D., Guo, C., Lipshteyn, M., Liron, Y., Padhye, J., Raindel, S., Yahia, M. H., Zhang, M. (2015). Congestion Control for Large-Scale RDMA Deployments. ACM SIGCOMM Computer Communication Review.
Ziegler, J. F., Curtis, H. W., Muhlfeld, H. P., Montrose, C. J., Chin, B., Nicewicz, M., Russell, C. A., Wang, W. Y., Freeman, L. B., Hosier, P., LaFave, L. E., Walsh, J. L., Orro, J. M., Unger, G. J., Ross, J. M., O’Gorman, T. J., Messina, B., Sullivan, T. D., Sykes, A. J., Yourke, H., Enger, T. A., Tolat, V., Scott, T. S., Taber, A. H., Sussman, R. J., Klein, W. A., Wahaus, C. W. (1996). IBM experiments in soft fails in computer electronics (1978–1994). IBM Journal of Research and Development.
Zou, Andy, Wang, Zifan, Carlini, Nicholas, Nasr, Milad, Kolter, J. Zico, Fredrikson, Matt (2023). Universal and Transferable Adversarial Attacks on Aligned Language Models.
Zu, Y., Ghaffarkhah, A., Dang, H.-V., Towles, B., Hand, S., Huda, S., Bello, A., Kolbasov, A., Rezaei, A., Du, D., Lacy, S., Wang, H., Wisner, A., Lewis, C., Bahini, H. (2024). Resiliency at Scale: Managing Google’s TPUv4 Machine Learning Supercomputer. 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24).

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