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ORCID4th EuroMLSys@EuroSys 2024: Athens, Greece
- Proceedings of the 4th Workshop on Machine Learning and Systems, EuroMLSys 2024, Athens, Greece, 22 April 2024. ACM 2024
- Sandra Deepthy Siby, Sina Abdollahi
, Mohammad Maheri, Marios Kogias, Hamed Haddadi:
GuaranTEE: Towards Attestable and Private ML with CCA. 1-9 - Taiyi Wang, Eiko Yoneki:
IA2: Leveraging Instance-Aware Index Advisor with Reinforcement Learning for Diverse Workloads. 10-17 - Houssem Eddine Souid, Lucas Ody, Youssef Achenchabe, Valentin Lemaire, Gianmarco Aversano, Sabri Skhiri:
Temporal Graph Generative Models: An empirical study. 18-27 - Hamid Ghasemirahni, Alireza Farshin, Mariano Scazzariello, Marco Chiesa, Dejan Kostic:
Deploying Stateful Network Functions Efficiently using Large Language Models. 28-38 - Konstantinos Papaioannou, Thaleia Dimitra Doudali:
The Importance of Workload Choice in Evaluating LLM Inference Systems. 39-46 - Connor Espenshade, Rachel Peng, Eumin Hong, Max Calman, Yue Zhu, Pritish Parida, Eun Kyung Lee, Martha A. Kim:
Characterizing Training Performance and Energy for Foundation Models and Image Classifiers on Multi-Instance GPUs. 47-55 - Neil Hurley, Erika Duriakova, James Geraci, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Barry Smyth, Aonghus Lawlor:
ALS Algorithm for Robust and Communication-Efficient Federated Learning. 56-64 - Rahma Nouaji, Stella Bitchebe, Oana Balmau:
SpeedyLoader: Efficient Pipelining of Data Preprocessing and Machine Learning Training. 65-72 - Yushan Huang, Josh Millar, Yuxuan Long, Yuchen Zhao, Hamed Haddadi:
Towards Low-Energy Adaptive Personalization for Resource-Constrained Devices. 73-80 - Ties Robroek, Ehsan Yousefzadeh-Asl-Miandoab, Pinar Tözün:
An Analysis of Collocation on GPUs for Deep Learning Training. 81-90 - Dejan Grubisic, Volker Seeker, Gabriel Synnaeve, Hugh Leather, John M. Mellor-Crummey, Chris Cummins:
Priority Sampling of Large Language Models for Compilers. 91-97 - Yongjun He, Yao Lu, Gustavo Alonso:
Deferred Continuous Batching in Resource-Efficient Large Language Model Serving. 98-106 - Foteini Strati, Paul Elvinger, Tolga Kerimoglu, Ana Klimovic:
ML Training with Cloud GPU Shortages: Is Cross-Region the Answer? 107-116 - Keshav Santhanam, Deepti Raghavan, Muhammad Shahir Rahman, Thejas Venkatesh, Neha Kunjal, Pratiksha Thaker, Philip Alexander Levis, Matei Zaharia:
ALTO: An Efficient Network Orchestrator for Compound AI Systems. 117-125 - Zeling Zhang, Dongqi Cai, Yiran Zhang, Mengwei Xu, Shangguang Wang, Ao Zhou:
FedRDMA: Communication-Efficient Cross-Silo Federated LLM via Chunked RDMA Transmission. 126-133 - Petru Neague, Marcel Gregoriadis, Johan Pouwelse:
De-DSI: Decentralised Differentiable Search Index. 134-143 - Pol G. Recasens, Yue Zhu, Chen Wang, Eun Kyung Lee, Olivier Tardieu, Alaa Youssef, Jordi Torres, Josep Lluis Berral:
Towards Pareto Optimal Throughput in Small Language Model Serving. 144-152 - Georgia Christofidi, Thaleia Dimitra Doudali:
Do Predictors for Resource Overcommitment Even Predict? 153-160 - Diarmuid O'Reilly-Morgan, Elias Z. Tragos, James Geraci, Qinqin Wang, Neil Hurley, Barry Smyth, Aonghus Lawlor:
A Hybrid Decentralised Learning Topology for Recommendations with Improved Privacy. 161-168 - Connor Imes, Andrew Rittenbach, Peng Xie, Dong-In Kang, John Paul Walters, Stephen P. Crago:
Evaluating Deep Learning Recommendation Model Training Scalability with the Dynamic Opera Network. 169-175 - Bradley Aldous, Ahmed M. Abdelmoniem:
Comparative Profiling: Insights Into Latent Diffusion Model Training. 176-183 - Kamran Razavi, Saeid Ghafouri, Max Mühlhäuser, Pooyan Jamshidi, Lin Wang:
Sponge: Inference Serving with Dynamic SLOs Using In-Place Vertical Scaling. 184-191 - Ahmed Menshawy, Muhammad Zeeshan Nawaz, Mahmoud Fahmy:
Navigating Challenges and Technical Debt in Large Language Models Deployment. 192-199 - Kouider Chadli, Goetz Botterweck, Takfarinas Saber:
The Environmental Cost of Engineering Machine Learning-Enabled Systems: A Mapping Study. 200-207 - Abir Chebbi, Guido Kniesel, Nabil Abdennadher, Giovanna Dimarzo:
Enhancing Named Entity Recognition for Agricultural Commodity Monitoring with Large Language Models. 208-213
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