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Research Spending & Results

Award Detail

Doing Business As Name:University of Wisconsin-Madison
  • Xiangyao Yu
  • (608) 262-5618
  • Aditya Akella
  • Ming Liu
Award Date:05/10/2021
Estimated Total Award Amount: $ 1,200,000
Funds Obligated to Date: $ 588,560
  • FY 2021=$588,560
Start Date:10/01/2021
End Date:09/30/2025
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:CNS Core: Medium: SmartNIC-Accelerated Database Systems
Federal Award ID Number:2106199
DUNS ID:161202122
Parent DUNS ID:041188822
Program:CSR-Computer Systems Research
Program Officer:
  • Erik Brunvand
  • (703) 292-2767

Awardee Location

Street:21 North Park Street
Awardee Cong. District:02

Primary Place of Performance

Organization Name:University of Wisconsin-Madison
Cong. District:02

Abstract at Time of Award

Databases power many of the largest and most commonly used Internet services and applications in the world. Today, these systems are run in a distributed fashion across multiple machines or even across data centers, driven by the growing volumes of data and the growing scale of Internet services. The network communication is becoming a severe bottleneck in distributed databases. Recently, a new technology, SmartNIC, has been invented to add intelligence into the network interface card (NIC) to reduce the computation overhead of host processor. This new hardware device has great potential in accelerating distributed database operations. The goal of this project is to explore opportunities in this design space. The proposed work will develop SmartNIC-accelerated high performance distributed databases for both online-analytical processing (OLAP) and online-transactional processing (OLTP) workloads. The work can improve both on-premise and cloud distributed databases and add significant value to society at large. The proposal work can potentially be integrated into commercial distributed databases, leading to high performance and low latency for internet services and applications which can bring benefits to individual customers. The software developed through this project will be incorporated into existing open source big data stacks and database systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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