Wang earns NSF CAREER award
07-19-2024
Assistant Professor Jianguo Wang earned an NSF CAREER Award for his proposed work titled, “The Case for Disaggregated Database Systems.”
Enhancing Database Efficiency Through Resource Disaggregation
Database efficiency is vital for the productivity and profitability of organizations. In the landscape of the cloud, the demand for robust and scalable database systems has never been greater. Enterprising companies grapple with the challenges of managing colossal amounts of data while striving to deliver seamless user experiences.
Resource disaggregation could provide a solution- improving companies’ performance, scalability and elasticity while reducing operational costs. As architecture in modern data centers evolves the clouds towards disaggregated data centers (DDCs), there is movement away from aggregation in monolithic servers.
Resource disaggregation provides independent elasticity for scaling compute, memory and storage and facilitates higher reliability, provides users the illusion of a near-infinite pool of resources for applications and enables higher resource utilization and less resource fragmentation due to hardware decoupling and pooling.
Jianguo Wang, assistant professor in the Department of Computer Science won a National Science Foundation (NSF) CAREER Award for his proposed work titled, “The Case for Disaggregated Database Systems.” His project aims to drive innovation in database technology for the next-generation cloud by redefining the way businesses manage their data infrastructure.
Disaggregated Database Systems
Wang’s project explores the impact of resource disaggregation on database systems, addressing the challenges posed by the separation of hardware resources such as compute, memory, and storage. Traditional databases designed for monolithic servers struggle to meet the demands of elasticity, scalability, and cost-effectiveness, particularly in cloud environments.
The project aims to develop a new, optimized database system tailored for resource disaggregation, focusing on improving performance, scalability, and elasticity while reducing costs. It will investigate three key areas: efficient management of database logs and transactions for storage disaggregation, optimization of database indexes and buffer management for memory disaggregation, and the development of a distributed database architecture for memory disaggregation.
“Ideally, this approach will advance the frontier of database systems to unprecedented levels of performance, scalability, and elasticity. The expected improvement is substantial and could be an order of magnitude,” said Wang.
NSF CAREER Awards
NSF CAREER awards are the organization’s most prestigious awards given to junior faculty who embody the role of teacher-scholars through research, education and the integration of those concepts within the mission of their organizations. CAREER awards support promising and talented researchers in building a foundation for a lifetime of leadership. Receiving this award reflects this project’s merit of the NSF statutory mission and its worthiness of financial support.
Jianguo Wang is an assistant professor of computer science at Purdue University. His research interests include disaggregated database systems for the cloud and vector database systems for Large Language Models (LLMs). Before joining Purdue CS, he worked at Ziliz on Milvus, a purpose-built vector database system and at Amazon Web Services (AWS) on Amazon Aurora, a cloud-native database system. Wang earned his PhD from the University of California, San Diego.
About the Department of Computer Science at Purdue University
Founded in 1962, the Department of Computer Science was created to be an innovative base of knowledge in the emerging field of computing as the first degree-awarding program in the United States. The department continues to advance the computer science industry through research. US News & Reports ranks Purdue CS #8 in computer engineering and #19 and #18 overall in graduate and undergraduate computer science. Additionally the program is ranked 6th in cybersecurity, 8th in software engineering, 13th in systems, 15th in programming languages and data analytics, and 18th in theory. Graduates of the program are able to solve complex and challenging problems in many fields. Our consistent success in an ever-changing landscape is reflected in the record undergraduate enrollment, increased faculty hiring, innovative research projects, and the creation of new academic programs. The increasing centrality of computer science in academic disciplines and society, and new research activities—centered around foundations and applications of artificial intelligence and machine learning, such as natural language processing, human computer interaction, vision, and robotics, as well as systems and security—are the future focus of the department. cs.purdue.edu
Writer: Molly Walker, walke598@purdue.edu
Source: Jianguo Wang, csjgwang@purdue.edu