63 citations · 154 across the 14 of their papers we have counts for
14 papers
How Many Shots Does It Take? A Noise-Aware Quantum Resource Allocation Framework
Prateek P. Kulkarni, Sumit K. Mandal
Any algorithm execution on quantum computers requires several repeated and costly executions (known as shots) to obtain reliable results. In this work, we propose a closed-form acc…
DISHA: Low-Energy Sparse Transformer at Edge for Outdoor Navigation for the Visually Impaired Individuals
Praveen Nagil, Sumit K. Mandal
Assistive technology for visually impaired individuals is extremely useful to make them independent of another human being in performing day-to-day chores and instill confidence in…
Machine Learning-based Low Overhead Congestion Control Algorithm for Industrial NoCs
Shruti Yadav Narayana, Sumit K. Mandal, Raid Ayoub +2
Network-on-Chip (NoC) congestion builds up during heavy traffic load and cripples the system performance by stalling the cores. Moreover, congestion leads to wasted link bandwidth…
COIN: Communication-Aware In-Memory Acceleration for Graph Convolutional Networks
Sumit K. Mandal, Gokul Krishnan, A. Alper Goksoy +3
Graph convolutional networks (GCNs) have shown remarkable learning capabilities when processing graph-structured data found inherently in many application areas. GCNs distribute th…
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.…
Theoretical Analysis and Evaluation of NoCs with Weighted Round-Robin Arbitration
Sumit K. Mandal, Jie Tong, Raid Ayoub +3
Fast and accurate performance analysis techniques are essential in early design space exploration and pre-silicon evaluations, including software eco-system development. In particu…
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…
Impact of On-Chip Interconnect on In-Memory Acceleration of Deep Neural Networks
Gokul Krishnan, Sumit K. Mandal, Chaitali Chakrabarti +3
With the widespread use of Deep Neural Networks (DNNs), machine learning algorithms have evolved in two diverse directions -- one with ever-increasing connection density for better…
Online Adaptive Learning for Runtime Resource Management of Heterogeneous SoCs
Sumit K. Mandal, Umit Y. Ogras, Janardhan Rao Doppa +3
Dynamic resource management has become one of the major areas of research in modern computer and communication system design due to lower power consumption and higher performance d…
Runtime Task Scheduling using Imitation Learning for Heterogeneous Many-Core Systems
Anish Krishnakumar, Samet E. Arda, A. Alper Goksoy +4
Domain-specific systems-on-chip, a class of heterogeneous many-core systems, are recognized as a key approach to narrow down the performance and energy-efficiency gap between custo…
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…
Analytical Performance Modeling of NoCs under Priority Arbitration and Bursty Traffic
Sumit K. Mandal, Raid Ayoub, Michael Kishinevsky +2
Networks-on-Chip (NoCs) used in commercial many-core processors typically incorporate priority arbitration. Moreover, they experience bursty traffic due to application workloads. H…
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…
Analytical Performance Models for NoCs with Multiple Priority Traffic Classes
Sumit K. Mandal, Raid Ayoub, Michael Kishinevsky +1
Networks-on-chip (NoCs) have become the standard for interconnect solutions in industrial designs ranging from client CPUs to many-core chip-multiprocessors. Since NoCs play a vita…