71 citations · 137 across the 8 of their papers we have counts for
9 papers
Physical Design Automation for Planar Superconducting Quantum Chips
Michael Feldmeier, Marcel Walter, Gerhard B. P. Huber +3
Superconducting circuits have emerged as one of the most promising and scalable platforms for quantum com- puting, with substantial industrial adoption driving qubit counts steadil…
Best arm identification in rare events
Anirban Bhattacharjee, Sushant Vijayan, Sandeep K Juneja
We consider the best arm identification problem in the stochastic multi-armed bandit framework where each arm has a tiny probability of realizing large rewards while with overwhelm…
A scalable spectral Stokes solver for simulation of time-periodic flows in complex geometries
Chenwei Meng, Anirban Bhattacharjee, Mahdi Esmaily
Simulation of unsteady creeping flows in complex geometries has traditionally required the use of a time-stepping procedure, which is typically costly and unscalable. To reduce the…
City-Scale Agent-Based Simulators for the Study of Non-Pharmaceutical Interventions in the Context of the COVID-19 Epidemic
Shubhada Agrawal, Siddharth Bhandari, Anirban Bhattacharjee +14
We highlight the usefulness of city-scale agent-based simulators in studying various non-pharmaceutical interventions to manage an evolving pandemic. We ground our studies in the c…
Deep-Edge: An Efficient Framework for Deep Learning Model Update on Heterogeneous Edge
Anirban Bhattacharjee, Ajay Dev Chhokra, Hongyang Sun +4
Deep Learning (DL) model-based AI services are increasingly offered in a variety of predictive analytics services such as computer vision, natural language processing, speech recog…
FECBench: A Holistic Interference-aware Approach for Application Performance Modeling
Yogesh D. Barve, Shashank Shekhar, Ajay Dev Chhokra +5
Services hosted in multi-tenant cloud platforms often encounter performance interference due to contention for non-partitionable resources, which in turn causes unpredictable behav…
BARISTA: Efficient and Scalable Serverless Serving System for Deep Learning Prediction Services
Anirban Bhattacharjee, Ajay Dev Chhokra, Zhuangwei Kang +3
Pre-trained deep learning models are increasingly being used to offer a variety of compute-intensive predictive analytics services such as fitness tracking, speech and image recogn…
CloudCAMP: Automating Cloud Services Deployment and Management
Anirban Bhattacharjee, Yogesh Barve, Aniruddha Gokhale +1
Users of cloud platforms often must expend significant manual efforts in the deployment and orchestration of their services on cloud platforms due primarily to having to deal with…
Stratum: A Serverless Framework for Lifecycle Management of Machine Learning based Data Analytics Tasks
Anirban Bhattacharjee, Yogesh Barve, Shweta Khare +3
With the proliferation of machine learning (ML) libraries and frameworks, and the programming languages that they use, along with operations of data loading, transformation, prepar…