78 citations · 194 across the 14 of their papers we have counts for
15 papers
SET: Stream-Event-Triggered Scheduling for Efficient CUDA Graph Pipelines
Zhengxiong Li, Tsung-Wei Huang, Umit Ogras
Achieving peak GPU performance remains a significant challenge as the system throughput is constrained by host-device synchronization delays and kernel scheduling overheads, even w…
LEXI: Lossless Exponent Coding for Efficient Inter-Chiplet Communication in Hybrid LLMs
Miao Sun, Alish Kanani, Kaushik Shroff +1
Data movement overheads increase the inference latency of state-of-the-art large language models (LLMs). These models commonly use the bfloat16 (BF16) format for stable training. F…
DUET: Disaggregated Hybrid Mamba-Transformer LLMs with Prefill and Decode-Specific Packages
Alish Kanani, Sangwan Lee, Han Lyu +3
Large language models operate in distinct compute-bound prefill followed by memory bandwidth-bound decode phases. Hybrid Mamba-Transformer models inherit this asymmetry while addin…
K-PACT: Kernel Planning for Adaptive Context Switching -- A Framework for Clustering, Placement, and Prefetching in Spectrum Sensing
H. Umut Suluhan, Jiahao Lin, Serhan Gener +3
Efficient wideband spectrum sensing requires rapid evaluation and re-evaluation of signal presence and type across multiple subchannels. These tasks involve multiple hypothesis tes…
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…
PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning Algorithm
Toygun Basaklar, Suat Gumussoy, Umit Y. Ogras
Multi-objective reinforcement learning (MORL) approaches have emerged to tackle many real-world problems with multiple conflicting objectives by maximizing a joint objective functi…
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…
REAP: Runtime Energy-Accuracy Optimization for Energy Harvesting IoT Devices
Ganapati Bhat, Kunal Bagewadi, Hyung Gyu Lee +1
The use of wearable and mobile devices for health monitoring and activity recognition applications is increasing rapidly. These devices need to maximize their accuracy and active t…
Online Human Activity Recognition using Low-Power Wearable Devices
Ganapati Bhat, Ranadeep Deb, Vatika Vardhan Chaurasia +2
Human activity recognition~(HAR) has attracted significant research interest due to its applications in health monitoring and patient rehabilitation. Recent research on HAR focuses…
Power-Temperature Stability and Safety Analysis for Multiprocessor Systems
Ganapati Bhat, Suat Gumussoy, Umit Y. Ogras
Modern multiprocessor system-on-chips (SoCs) integrate multiple heterogeneous cores to achieve high energy efficiency. The power consumption of each core contributes to an increase…