79 citations · 253 across the 16 of their papers we have counts for
5 papers · 1 filter
DeepNVM++: Cross-Layer Modeling and Optimization Framework of Non-Volatile Memories for Deep Learning
Ahmet Inci, Mehmet Meric Isgenc, Diana Marculescu
Non-volatile memory (NVM) technologies such as spin-transfer torque magnetic random access memory (STT-MRAM) and spin-orbit torque magnetic random access memory (SOT-MRAM) have sig…
The Architectural Implications of Distributed Reinforcement Learning on CPU-GPU Systems
Ahmet Inci, Evgeny Bolotin, Yaosheng Fu +4
With deep reinforcement learning (RL) methods achieving results that exceed human capabilities in games, robotics, and simulated environments, continued scaling of RL training is c…
One Weight Bitwidth to Rule Them All
Ting-Wu Chin, Pierce I-Jen Chuang, Vikas Chandra +1
Weight quantization for deep ConvNets has shown promising results for applications such as image classification and semantic segmentation and is especially important for applicatio…
Workshops on Extreme Scale Design Automation (ESDA) Challenges and Opportunities for 2025 and Beyond
R. Iris Bahar, Alex K. Jones, Srinivas Katkoori +3
Integrated circuits and electronic systems, as well as design technologies, are evolving at a great rate -- both quantitatively and qualitatively. Major developments include new in…
Renofeation: A Simple Transfer Learning Method for Improved Adversarial Robustness
Ting-Wu Chin, Cha Zhang, Diana Marculescu
Fine-tuning through knowledge transfer from a pre-trained model on a large-scale dataset is a widely spread approach to effectively build models on small-scale datasets. In this wo…