Heterogeneous Memory Subsystem for Natural Graph Analytics. - Abraham Addisie; Hiwot Kassa; Opeoluwa Matthews; Valeria Bertacco (IISWC, 2018)

STOMP: A Tool for Evaluation of Scheduling Policies in Heterogeneous Multi-Processors. - Augusto Vega; Aporva Amarnath; John-David Wellman; Hiwot Kassa; Subhankar Pal; Hubertus Franke; Alper Buyuktosunoglu; Ronald G. Dreslinski; Pradip Bose (CoRR, 2020)

ChipAdvisor: A Machine Learning Approach for Mapping Applications to Heterogeneous Systems. - Hiwot Tadese Kassa; Tarunesh Verma; Todd M. Austin; Valeria Bertacco (ISQED, 2021)

Improving Performance of Flash Based Key-Value Stores Using Storage Class Memory as a Volatile Memory Extension. - Hiwot Tadese Kassa; Jason Akers; Mrinmoy Ghosh; Zhichao Cao 002; Vaibhav Gogte; Ronald G. Dreslinski (USENIX ATC, 2021)

Heterogeneity-Aware Scheduling on SoCs for Autonomous Vehicles. - Aporva Amarnath; Subhankar Pal; Hiwot Tadese Kassa; Augusto Vega; Alper Buyuktosunoglu; Hubertus Franke; John-David Wellman; Ronald Dreslinski Jr.; Pradip Bose (IEEE Comput. Archit. Lett., 2021)

HetSched: Quality-of-Mission Aware Scheduling for Autonomous Vehicle SoCs. - Aporva Amarnath; Subhankar Pal; Hiwot Kassa; Augusto Vega; Alper Buyuktosunoglu; Hubertus Franke; John-David Wellman; Ronald G. Dreslinski; Pradip Bose (CoRR, 2022)

Power-optimized Deployment of Key-value Stores Using Storage Class Memory. - Hiwot Tadese Kassa; Jason Akers; Mrinmoy Ghosh; Zhichao Cao 002; Vaibhav Gogte; Ronald G. Dreslinski (ACM Trans. Storage, 2022)

Efficient Utilization of Heterogeneous Compute and Memory Systems - Hiwot Tadese Kassa (2022)

MTrainS: Improving DLRM training efficiency using heterogeneous memories. - Hiwot Tadese Kassa; Paul Johnson; Jason Akers; Mrinmoy Ghosh; Andrew Tulloch; Dheevatsa Mudigere; Jongsoo Park; Xing Liu; Ronald G. Dreslinski; Ehsan K. Ardestani (CoRR, 2023)

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)

Lumos: Efficient Performance Modeling and Estimation for Large-scale LLM Training. - Mingyu Liang; Hiwot Tadese Kassa; Wenyin Fu; Brian Coutinho; Louis Feng; Christina Delimitrou (CoRR, 2025)