Performance Implications of Big Data in Scalable Deep Learning: On the Importance of Bandwidth and Caching. - Miro Hodak; David Ellison; Peter Seidel; Ajay Dholakia (IEEE BigData, 2018)

Towards Evaluation of Tensorflow Performance in a Distributed Compute Environment. - Miro Hodak; Ajay Dholakia (TPCTC, 2018)

Towards Power Efficiency in Deep Learning on Data Center Hardware. - Miro Hodak; Masha Gorkovenko; Ajay Dholakia (IEEE BigData, 2019)

Challenges in Distributed MLPerf. - Miro Hodak; Ajay Dholakia (TPCTC, 2019)

Benchmarking AI Inference: Where we are in 2020. - Miro Hodak; David Ellison; Ajay Dholakia (TPCTC, 2020)

Recent Efficiency Gains in Deep Learning: Performance, Power, and Sustainability. - Miro Hodak; Ajay Dholakia (IEEE BigData, 2021)

Scanflow: an end-to-end agent-based autonomic ML workflow manager for clusters. - Peini Liu; Gusseppe Bravo Rocca; Jordi Guitart; Ajay Dholakia; David Ellison; Miroslav Hodak (Middleware Demos/Posters, 2021)

Everyone is a Winner: Interpreting MLPerf Inference Benchmark Results. - Miro Hodak; David Ellison; Ajay Dholakia (TPCTC, 2021)

Scanflow: A multi-graph framework for Machine Learning workflow management, supervision, and debugging. - Gusseppe Bravo Rocca; Peini Liu; Jordi Guitart; Ajay Dholakia; David Ellison; Jeffrey Falkanger; Miroslav Hodak (CoRR, 2021)

Scanflow-K8s: Agent-based Framework for Autonomic Management and Supervision of ML Workflows in Kubernetes Clusters. - Peini Liu; Gusseppe Bravo Rocca; Jordi Guitart; Ajay Dholakia; David Ellison; Miroslav Hodak (CCGRID, 2022)

Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation. - Gusseppe Bravo Rocca; Peini Liu; Jordi Guitart; Ajay Dholakia; David Ellison; Miroslav Hodak (COMPSAC, 2022)

Benchmarking Considerations for Trustworthy and Responsible AI (Panel). - Ajay Dholakia; David Ellison; Miro Hodak; Debojyoti Dutta (TPCTC, 2022)

More the Merrier: Comparative Evaluation of TPCx-AI and MLPerf Benchmarks for AI. - Yingrui Liu Olesiuk; Miro Hodak; David Ellison; Ajay Dholakia (TPCTC, 2022)

Scanflow: A multi-graph framework for Machine Learning workflow management, supervision, and debuggin. - Gusseppe Bravo Rocca; Peini Liu; Jordi Guitart; Ajay Dholakia; David Ellison; Jeffrey Falkanger; Miroslav Hodak (Expert Syst. Appl., 2022)

Benchmarking Generative AI Performance Requires a Holistic Approach. - Ajay Dholakia; David Ellison; Miro Hodak; Debojyoti Dutta; Carsten Binnig (TPCTC, 2023)

Benchmarking Large Language Models: Opportunities and Challenges. - Miro Hodak; David Ellison; Chris Van Buren; Xiaotong Jiang; Ajay Dholakia (TPCTC, 2023)

Preliminary Results of the MLPerf BERT Inference Benchmark on AMD Instinct GPUs. - Zixian Wang; Khai Vu; Miro Hodak; Aarush Mehrotra; Francisco Gutierrez; Kyle Smith; Gloria Seo; Austin Garcia; Bryan Chin; Marty Kandes; Mary P. Thomas (PEARC, 2024)

MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI. - Arya Tschand; Arun Tejusve Raghunath Rajan; Sachin Idgunji; Anirban Ghosh; Jeremy Holleman; Csaba Király 002; Pawan Ambalkar; Ritika Borkar; Ramesh Chukka; Trevor Cockrell; Oliver Curtis; Grigori Fursin; et al. (CoRR, 2024)

MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from μWatts to MWatts for Sustainable AI. - Arya Tschand; Arun Tejusve Raghunath Rajan; Sachin Idgunji; Anirban Ghosh; Jeremy Holleman; Csaba Király 002; Pawan Ambalkar; Ritika Borkar; Ramesh Chukka; Trevor Cockrell; Oliver Curtis; Grigori Fursin; et al. (HPCA, 2025)