Energy efficiency in cloud-based MapReduce applications through better performance estimation. - Seyed Morteza Nabavinejad; Maziar Goudarzi (DATE, 2016)

Communication-Awareness for Energy-Efficiency in Datacenters. - Seyed Morteza Nabavinejad; Maziar Goudarzi (Adv. Comput., 2016)

The Memory Challenge in Reduce Phase of MapReduce Applications. - Seyed Morteza Nabavinejad; Maziar Goudarzi; Shirin Mozaffari (IEEE Trans. Big Data, 2016)

QoR-aware power capping for approximate big data processing. - Seyed Morteza Nabavinejad; Xin Zhan; Reza Azimi; Maziar Goudarzi; Sherief Reda (DATE, 2018)

Data locality and VM interference aware mitigation of data skew in hadoop leveraging modern portfolio theory. - Seyed Morteza Nabavinejad; Maziar Goudarzi (SAC, 2018)

MapReduce service provisioning for frequent big data jobs on clouds considering data transfers. - Seyed Morteza Nabavinejad; Maziar Goudarzi; Saeed Abedi (Comput. Electr. Eng., 2018)

Coordinated DVFS and Precision Control for Deep Neural Networks. - Seyed Morteza Nabavinejad; Hassan Hafez-Kolahi; Sherief Reda (IEEE Comput. Archit. Lett., 2019)

Faster MapReduce Computation on Clouds Through Better Performance Estimation. - Seyed Morteza Nabavinejad; Maziar Goudarzi (IEEE Trans. Cloud Comput., 2019)

ApproxDNN: Incentivizing DNN Approximation in Cloud. - Seyed Morteza Nabavinejad; Lena Mashayekhy; Sherief Reda (CCGRID, 2020)

An Overview of Efficient Interconnection Networks for Deep Neural Network Accelerators. - Seyed Morteza Nabavinejad; Mohammad Baharloo; Kun-Chih Chen; Maurizio Palesi; Tim Kogel; Masoumeh Ebrahimi (IEEE J. Emerg. Sel. Topics Circuits Syst., 2020)

BatchSizer: Power-Performance Trade-off for DNN Inference. - Seyed Morteza Nabavinejad; Sherief Reda; Masoumeh Ebrahimi (ASP-DAC, 2021)

BayesTuner: Leveraging Bayesian Optimization For DNN Inference Configuration Selection. - Seyed Morteza Nabavinejad; Sherief Reda (IEEE Comput. Archit. Lett., 2021)

On the Impact of Device-Level Techniques on Energy-Efficiency of Neural Network Accelerators. - Seyed Morteza Nabavinejad; Behzad Salami 001 (CoRR, 2021)

Profit Maximization of Big Data Jobs in Cloud Using Stochastic Optimization. - Seyed Morteza Nabavinejad; Maziar Goudarzi (IEEE Trans. Cloud Comput., 2021)

Inference Time Reduction of Deep Neural Networks on Embedded Devices: A Case Study. - Isma-Ilou Sadou; Seyed Morteza Nabavinejad; Zhonghai Lu; Masoumeh Ebrahimi (DSD, 2022)

Coordinated Batching and DVFS for DNN Inference on GPU Accelerators. - Seyed Morteza Nabavinejad; Sherief Reda; Masoumeh Ebrahimi (IEEE Trans. Parallel Distributed Syst., 2022)

Opportunities of Renewable Energy Powered DNN Inference. - Seyed Morteza Nabavinejad; Tian Guo 001 (CoRR, 2023)

Throughput Maximization of DNN Inference: Batching or Multi-Tenancy? - Seyed Morteza Nabavinejad; Masoumeh Ebrahimi; Sherief Reda (CoRR, 2023)

Mobility-Aware Computation Offloading in Edge Computing Using Machine Learning. - Erfan Farhangi Maleki; Lena Mashayekhy; Seyed Morteza Nabavinejad (IEEE Trans. Mob. Comput., 2023)

MediatorDNN: Contention Mitigation for Co-Located DNN Inference Jobs. - Seyed Morteza Nabavinejad; Sherief Reda; Tian Guo 001 (CLOUD, 2024)

FairCIM: Fair Interference Mitigation by DNN Switching for Latency-Sensitive Inference Jobs. - Seyed Morteza Nabavinejad; Sherief Reda; Tian Guo 001 (ACSOS, 2024)