36 citations · 71 across the 7 of their papers we have counts for
9 papers
MoCA: Memory-Centric, Adaptive Execution for Multi-Tenant Deep Neural Networks
Seah Kim, Hasan Genc, Vadim Vadimovich Nikiforov +3
Driven by the wide adoption of deep neural networks (DNNs) across different application domains, multi-tenancy execution, where multiple DNNs are deployed simultaneously on the sam…
AutoCkt: Deep Reinforcement Learning of Analog Circuit Designs
Keertana Settaluri, Ameer Haj-Ali, Qijing Huang +2
Domain specialization under energy constraints in deeply-scaled CMOS has been driving the need for agile development of Systems on a Chip (SoCs). While digital subsystems have desi…
Optimizing the LO Distribution Architecture of mm-Wave Massive MIMO Receivers
Greg LaCaille, Antonio Puglielli, Elad Alon +2
Wireless networks at millimeter wavelengths have significant implementation difficulties. The path loss at these frequencies naturally leads us to consider antenna arrays with many…
Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration
Hasan Genc, Seah Kim, Alon Amid +16
DNN accelerators are often developed and evaluated in isolation without considering the cross-stack, system-level effects in real-world environments. This makes it difficult to app…
Wireless Channel Dynamics and Robustness for Ultra-Reliable Low-Latency Communications
Vasuki Narasimha Swamy, Paul Rigge, Gireeja Ranade +2
Interactive, immersive and critical applications demand ultra-reliable low-latency communication (URLLC). To build wireless communication systems that can support these application…
Network Coding for Real-time Wireless Communication for Automation
Vasuki Narasimha Swamy, Paul Rigge, Gireeja Ranade +2
Real-time applications require latencies on the order of a millisecond with very high reliabilities, paralleling the requirements for high-performance industrial control. Current w…