LSU, Ohio St., and RPI Faculty Combine for Project on Computational Storage

June 28, 2022

Headshot of Feng ChenBATON ROUGE, LA – Faculty from LSU, The Ohio State University and Rensselaer Polytechnic Institute have each been awarded a $400,000 grant from the National Science Foundation to solve the widening gap between computational processing and storage, thereby increasing high-speed data processing and enabling computational storage to address critical challenges in increasingly more data-centric applications.

The project—“A New Direction of Research and Development to Fulfill the Promise of Computational Storage”—is led by Ohio State Computer Science Professor Xiaodong Zhang, who is joined by LSU Computer Science Associate Professor Feng Chen and RPI Electrical, Computer & Systems Engineering Professor Tong Zhang. 

“The main research issues we will study focus on how to effectively exploit the computing capabilities and efficiently utilize the limited resources on device hardware,” Chen said. “We will adopt a system-oriented methodology to investigate these issues. The key is to consider the system as a whole, rather than trying to optimize each component individually.”

Indeed, their project takes a cohesive approach to turn computational storage into a cooperative component in the system as a whole. Specifically, it will examine multiple aspects in order to systematically integrate computational storage into existing computing ecosystems (i.e., users, applications, operating systems, and device hardware), such as designing an interface that makes on-device features available to applications, optimizing system-level resource utilization, leveraging proximity and mitigating memory resource contention in device hardware, and adapting core data structures and algorithms of applications to fully exploit various computing resources.

The project will also provide LSU students with opportunities to be involved in the related research.

“We’d like to provide students some early experience in academic research and attract them to this domain,” Chen said. “We plan to introduce advanced topics related to this project in classroom teaching, invite interested students to visit our lab, and encourage them to participate in research via activities such as independent studies, undergraduate projects, etc.”

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