This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program Project Grant award of $599,084 to The Research Foundation for The State University of New York (RF SUNY) aims to enhance the timeliness and power-efficiency of real-time data services. The 3-year project, beginning October 1, 2023, will investigate novel methodologies to improve the capabilities of cost-efficient real-time embedded databases supporting data-intensive applications like smart...
This $547,584 National Science Foundation project grant supports research at Arizona State University to redesign analytics databases for machine learning model serving. The goal is to develop methods bridging machine learning inference and relational algebra processing through a unified intermediate representation. This will allow native deep neural network model inferences directly from databases, eliminating cross-system latency in applications like supply chain prediction, fraud detection,...
This $167,158 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a customizable, privacy-preserving database analytics system compatible with existing SQL databases. The key products to be delivered under this 4-year award include: Automated tools for analyzing a database schema and interactively developing a flexible privacy model to determine which data elements require differential...
The National Science Foundation (NSF) Division of Computing and Communication Foundations awarded a $400,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Virginia. The award supports collaborative research to develop a hardware-software co-design approach for high-performance in-memory analytic data processing, addressing challenges in analyzing large volumes of data. The research focuses on designing...
The National Science Foundation (NSF) awarded a $399,998 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Cornell University for a collaborative research project titled "A Hardware-Software Co-Design Approach for High-Performance In-Memory Analytic Data Processing". The project aims to redesign both hardware and software components of an analytics pipeline to enable high-performance in-memory data processing and faster data-driven...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program project grant award (CFDA 47.070) provides $249,867 to New York University (NYU) from October 1, 2023 to September 30, 2027. Under this award, NYU will develop a prototype distributed database called VDDB and a new verification framework called PHLOX to formally specify and verify the correctness of VDDB. The goal is to demonstrate the feasibility of using formal verification to improve the...
This $400,000 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE, CFDA 47.070) program supports a collaborative research effort led by Carnegie Mellon University (CMU). The project aims to develop a hardware-software co-design approach for high-performance in-memory analytic data processing. Key technical thrusts include mechanisms for in-place data analytics on dynamic random-access memory (DRAM), processing-in-memory (PIM)...
This National Science Foundation Project Grant of $399,999 supports research at New York University from October 1, 2022 to September 30, 2026 under the Computer and Information Science and Engineering program. The research aims to develop an automated system for discovering and verifying database query transformation strategies to improve query performance. Existing databases rely on manually specified strategies to optimize queries, but often miss opportunities. The project will model...
This $275,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop and test new scheduling algorithms for improving the performance of modern database systems. The goal is to create models and policies that can efficiently allocate limited hardware resources, such as compute and memory, to handle a stream of parallelizable database queries with varying levels of parallelizability and service...
This National Science Foundation Project Grant award of $349,998 provides funding from October 1, 2022 through September 30, 2026 to support research into automatically discovering and verifying database query transformations. The award is made under the Computer and Information Science and Engineering program (CFDA 47.070), which aims to advance computer science and engineering research and education. Specifically, the awardee Yale University will develop a system capable of automatically...