26 citations · 75 across the 14 of their papers we have counts for
14 papers
ICGMM: CXL-enabled Memory Expansion with Intelligent Caching Using Gaussian Mixture Model
Hanqiu Chen, Yitu Wang, Luis Vitorio Cargnini +7
Compute Express Link (CXL) emerges as a solution for wide gap between computational speed and data communication rates among host and multiple devices. It fosters a unified and coh…
Residual-INR: Communication Efficient On-Device Learning Using Implicit Neural Representation
Hanqiu Chen, Xuebin Yao, Pradeep Subedi +1
Edge computing is a distributed computing paradigm that collects and processes data at or near the source of data generation. The on-device learning at edge relies on device-to-dev…
Exploring the Role of Machine Learning in Scientific Workflows: Opportunities and Challenges
Azita Nouri, Philip E. Davis, Pradeep Subedi +1
In this survey, we discuss the challenges of executing scientific workflows as well as existing Machine Learning (ML) techniques to alleviate those challenges. We provide the conte…
Scalable Graph Embedding LearningOn A Single GPU
Azita Nouri, Philip E. Davis, Pradeep Subedi +1
Graph embedding techniques have attracted growing interest since they convert the graph data into continuous and low-dimensional space. Effective graph analytic provides users a de…
Strategies for Democratization of Supercomputing: Availability, Accessibility and Usability of High Performance Computing for Education and Practice of Big Data Analytics
Jim Samuel, Margaret Brennan-Tonetta, Yana Samuel +2
There has been an increasing interest in and growing need for high performance computing (HPC), popularly known as supercomputing, in domains such as textual analytics, business do…
Exploring Trade-offs in Dynamic Task Triggering for Loosely Coupled Scientific Workflows
Zhe Wang, Pradeep Subedi, Shaohua Duan +5
In order to achieve near-time insights, scientific workflows tend to be organized in a flexible and dynamic way. Data-driven triggering of tasks has been explored as a way to suppo…