37 citations · 112 across the 10 of their papers we have counts for
10 papers
Modeling and Analysis of Application Interference on Dragonfly+
Yao Kang, Xin Wang, Neil McGlohon +3
Dragonfly class of networks are considered as promising interconnects for next-generation supercomputers. While Dragonfly+ networks offer more path diversity than the original Drag…
Union: An Automatic Workload Manager for Accelerating Network Simulation
Xin Wang, Misbah Mubarak, Yao Kang +2
With the rapid growth of the machine learning applications, the workloads of future HPC systems are anticipated to be a mix of scientific simulation, big data analytics, and machin…
Q-adaptive: A Multi-Agent Reinforcement Learning Based Routing on Dragonfly Network
Yao Kang, Xin Wang, Zhiling Lan
High-radix interconnects such as Dragonfly and its variants rely on adaptive routing to balance network traffic for optimum performance. Ideally, adaptive routing attempts to forwa…
MRSch: Multi-Resource Scheduling for HPC
Boyang Li, Yuping Fan, Matthew Dearing +4
Emerging workloads in high-performance computing (HPC) are embracing significant changes, such as having diverse resource requirements instead of being CPU-centric. This advancemen…
Study of Workload Interference with Intelligent Routing on Dragonfly
Yao Kang, Xin Wang, Zhiling Lan
Dragonfly interconnect is a crucial network technology for supercomputers. To support exascale systems, network resources are shared such that links and routers are not dedicated t…
Hybrid Workload Scheduling on HPC Systems
Yuping Fan, Paul Rich, William Allcock +2
Traditionally, on-demand, rigid, and malleable applications have been scheduled and executed on separate systems. The ever-growing workload demands and rapidly developing HPC infra…
DRAS-CQSim: A Reinforcement Learning based Framework for HPC Cluster Scheduling
Yuping Fan, Zhiling Lan
For decades, system administrators have been striving to design and tune cluster scheduling policies to improve the performance of high performance computing (HPC) systems. However…
Deep Reinforcement Agent for Scheduling in HPC
Yuping Fan, Zhiling Lan, Taylor Childers +3
Cluster scheduler is crucial in high-performance computing (HPC). It determines when and which user jobs should be allocated to available system resources. Existing cluster schedul…
Scheduling Beyond CPUs for HPC
Yuping Fan, Zhiling Lan, Paul Rich +4
High performance computing (HPC) is undergoing significant changes. The emerging HPC applications comprise both compute- and data-intensive applications. To meet the intense I/O de…
Performance and Power Modeling and Prediction Using MuMMI and Ten Machine Learning Methods
Xingfu Wu, Valerie Taylor, Zhiling Lan
In this paper, we use modeling and prediction tool MuMMI (Multiple Metrics Modeling Infrastructure) and ten machine learning methods to model and predict performance and power and…