Zhou Receives Funding For Novel Performance Profiling & Analysis Infrastructure For Scientific Deep Learning Workloads
Keren Zhou, Assistant Professor, Computer Science, College of Engineering and Computing (CEC), received funding for the project: “Collaborative Research: Elements: DLToolkit: A Novel Performance Profiling and Analysis Infrastructure for Scientific Deep Learning Workloads.”
The rapid adoption of deep learning (DL)-driven artificial intelligence (AI) applications makes it more crucial than ever to fully exploit available computational power to accelerate AI innovation. He is developing innovative performance measurement and analysis techniques tailored for scientific DL workloads and encapsulating these techniques into a profiling infrastructure (i.e., DLToolkit).
Building upon existing open-source performance tools, Zhou holds the DLToolkit will offer scalable analysis, aggregation, and visualization of scientific DL workloads, and provide invaluable insights to domain scientists. Zhou holds the toolkit will thus foster expedited innovation in scientific applications using DL.
Zhou received $274,265 from the National Science Foundation for this project. Funding began in June 2025 and will end in late May 2028.
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