Miro Hodak

According to our database, Miro Hodak authored at least 14 papers between 2018 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

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

More the Merrier: Comparative Evaluation of TPCx-AI and MLPerf Benchmarks for AI.

Yingrui Liu Olesiuk, Miro Hodak, David Ellison, Ajay Dholakia

Proceedings of the Performance Evaluation and Benchmarking, 2022

Benchmarking Considerations for Trustworthy and Responsible AI (Panel).

Ajay Dholakia, David Ellison, Miro Hodak, Debojyoti Dutta

Proceedings of the Performance Evaluation and Benchmarking, 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

Proceedings of the 46th IEEE Annual Computers, Software, and Applications Conferenc, 2022

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

Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

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

Everyone is a Winner: Interpreting MLPerf Inference Benchmark Results.

Miro Hodak, David Ellison, Ajay Dholakia

Proceedings of the Performance Evaluation and Benchmarking, 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

Proceedings of the Middleware '21: Proceedings of the 22nd International Middleware Conference: Demos and Posters, Virtual Event / Québec City, Canada, December 6, 2021

Recent Efficiency Gains in Deep Learning: Performance, Power, and Sustainability.

Miro Hodak, Ajay Dholakia

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Benchmarking AI Inference: Where we are in 2020.

Miro Hodak, David Ellison, Ajay Dholakia

Proceedings of the Performance Evaluation and Benchmarking, 2020

2019

Challenges in Distributed MLPerf.

Miro Hodak, Ajay Dholakia

Proceedings of the Performance Evaluation and Benchmarking for the Era of Cloud(s), 2019

Towards Power Efficiency in Deep Learning on Data Center Hardware.

Miro Hodak, Masha Gorkovenko, Ajay Dholakia

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Towards Evaluation of Tensorflow Performance in a Distributed Compute Environment.

Miro Hodak, Ajay Dholakia

Proceedings of the Performance Evaluation and Benchmarking for the Era of Artificial Intelligence, 2018

Performance Implications of Big Data in Scalable Deep Learning: On the Importance of Bandwidth and Caching.

Miro Hodak, David Ellison, Peter Seidel, Ajay Dholakia

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018