71 citations · 101 across the 8 of their papers we have counts for
8 papers
Improved Online Scheduling of Moldable Task Graphs under Common Speedup Models
Lucas Perotin, Hongyang Sun
We consider the online scheduling problem of moldable task graphs on multiprocessor systems for minimizing the overall completion time (or makespan). Moldable job scheduling has be…
Multi-Resource List Scheduling of Moldable Parallel Jobs under Precedence Constraints
Lucas Perotin, Hongyang Sun, Padma Raghavan
The scheduling literature has traditionally focused on a single type of resource (e.g., computing nodes). However, scientific applications in modern High-Performance Computing (HPC…
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…
Scalable Hierarchical Scheduling for Malleable Parallel Jobs on Multiprocessor-based Systems
Yangjie Cao, Hongyang Sun, Depei Qian +1
The proliferation of multi-core and multiprocessor-based computer systems has led to explosive development of parallel applications and hence the need for efficient schedulers. In…