High-Performance Big Data and AI; Logo designed by PADSYS. All rights reserved!

High-Performance Big Data and AI

Managing and processing large volumes of data, or Big Data, and gaining meaningful insights is a significant challenge facing the parallel and distributed computing community. This has significant impact in a wide range of domains including health care, bio-medical research, Internet search, finance and business informatics, and scientific computing. Designing and building high-performance Big Data and AI systems are of significant importance to both research communities and industry.

(Note: Logo is designed by PADSYS Lab. All rights reserved.)

As data-gathering technologies and data sources witness an explosion in the amount of input data, it is expected that in the future massive quantities of data in the order of hundreds or thousands of petabytes will need to be processed. Thus, it is critical that distributed computing systems for Big Data and AI (such as Hadoop, Spark, Flink, TensorFlow, PyTorch, etc.) are diligently designed, with high performance and scalability, in order to meet the growing demands of such Big Data applications.

PADSYS Lab members design and develop high-performance Big Data and AI systems and libraries for the emerging HPC and datacenter architectures. Our proposed designs and research studies aim to bring HPC, Big Data processing, AI, and Cloud Computing into a convergent trajectory.


Thanks a lot for NSF's support on this research direction!

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