GPU + In-Memory Data Management for Big Data Analytics

This project studies how GPU acceleration and in-memory computing can boost performance for large-scale data analytics. It focuses on the intersection of hardware acceleration and database technologies.

Integrate GPUs into in-memory database systems. Accelerate analytic queries for large-scale, real-time data. Benchmark GPU vs CPU trade-offs for data-intensive workloads.

Investigates combined hardware–software optimization. Part of TECO’s data engineering and analytics research. Explores open-source in-memory DBMS extensions.

Improves throughput and latency in big-data analytics systems. Informs architecture design for hybrid CPU–GPU computing. Enables real-time analytics for industrial and scientific data.