63 citations · 74 across the 4 of their papers we have counts for
7 papers
SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks
Gokul Krishnan, Sumit K. Mandal, Manvitha Pannala +4
In-memory computing (IMC) on a monolithic chip for deep learning faces dramatic challenges on area, yield, and on-chip interconnection cost due to the ever-increasing model sizes.…
FLASH: Fast Neural Architecture Search with Hardware Optimization
Guihong Li, Sumit K. Mandal, Umit Y. Ogras +1
Neural architecture search (NAS) is a promising technique to design efficient and high-performance deep neural networks (DNNs). As the performance requirements of ML applications g…
Transfer Learning for Human Activity Recognition using Representational Analysis of Neural Networks
Sizhe An, Ganapati Bhat, Suat Gumussoy +1
Human activity recognition (HAR) research has increased in recent years due to its applications in mobile health monitoring, activity recognition, and patient rehabilitation. The t…
Performance Analysis of Priority-Aware NoCs with Deflection Routing under Traffic Congestion
Sumit K. Mandal, Anish Krishnakumar, Raid Ayoub +2
Priority-aware networks-on-chip (NoCs) are used in industry to achieve predictable latency under different workload conditions. These NoCs incorporate deflection routing to minimiz…
An Energy-Aware Online Learning Framework for Resource Management in Heterogeneous Platforms
Sumit K. Mandal, Ganapati Bhat, Janardhan Rao Doppa +2
Mobile platforms must satisfy the contradictory requirements of fast response time and minimum energy consumption as a function of dynamically changing applications. To address thi…
Power and Thermal Analysis of Commercial Mobile Platforms: Experiments and Case Studies
Ganapati Bhat, Suat Gumussoy, Umit Y. Ogras
State-of-the-art mobile processors can deliver fast response time and high throughput to maximize the user experience. However, high performance comes at the expense of larger powe…