DeepNVM: A Framework for Modeling and Analysis of Non-Volatile Memory Technologies for Deep Learning Applications. - Ahmet Fatih Inci; Mehmet Meric Isgenc; Diana Marculescu (DATE, 2020)

The Architectural Implications of Distributed Reinforcement Learning on CPU-GPU Systems. - Ahmet Fatih Inci; Evgeny Bolotin; Yaosheng Fu; Gal Dalal; Shie Mannor; David W. Nellans; Diana Marculescu (CoRR, 2020)

DeepNVM++: Cross-Layer Modeling and Optimization Framework of Non-Volatile Memories for Deep Learning. - Ahmet Inci; Mehmet Meric Isgenc; Diana Marculescu (CoRR, 2020)

QAPPA: Quantization-Aware Power, Performance, and Area Modeling of DNN Accelerators. - Ahmet Inci; Siri Garudanagiri Virupaksha; Aman Jain; Venkata Vivek Thallam; Ruizhou Ding; Diana Marculescu (CoRR, 2022)

QADAM: Quantization-Aware DNN Accelerator Modeling for Pareto-Optimality. - Ahmet Inci; Siri Garudanagiri Virupaksha; Aman Jain; Venkata Vivek Thallam; Ruizhou Ding; Diana Marculescu (CoRR, 2022)

Efficient Deep Learning Using Non-Volatile Memory Technology. - Ahmet Inci; Mehmet Meric Isgenc; Diana Marculescu (CoRR, 2022)

DeepNVM++: Cross-Layer Modeling and Optimization Framework of Nonvolatile Memories for Deep Learning. - Ahmet Inci; Mehmet Meric Isgenc; Diana Marculescu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

QUIDAM: A Framework for Quantization-aware DNN Accelerator and Model Co-Exploration. - Ahmet Inci; Siri Garudanagiri Virupaksha; Aman Jain; Ting-Wu Chin; Venkata Vivek Thallam; Ruizhou Ding; Diana Marculescu (ACM Trans. Embed. Comput. Syst., 2023)

Nonuniform-Tensor-Parallelism: Mitigating GPU failure impact for Scaled-up LLM Training. - Daiyaan Arfeen; Dheevatsa Mudigere; Ankit More; Bhargava Gopireddy; Ahmet Inci; Gregory R. Ganger (CoRR, 2025)