The High-Performance Data Analytics (HPDA) Lab exploits emerging hardware — such as Graphics Processing Unit (GPU), Field-Programmable Gate Array (FPGA), high-end CPU and Solid-State Drive (SSD) — to build high-performance systems for graph computing, machine learning, computational omics, numerical simulation and cloud computing.
We have won the Best Dissertation Award and are the Champion of 2018 Graph Challenge. Our papers have appeared at top-tier conferences, such as, HPDC '19, DAC '19, SIGMOD '19, SC '18, FAST ’18, FAST '17, SIGMOD ’16, SC ’15 and SC '12. Particularly, our graph traversal systems are ranked highly in both Graph500 and Green Graph500 organizations, which measure the performance and energy efficiency of the most powerful supercomputers in the world.
For prospective students: if you are interested in conducting research within our group, please read our Prospective Students requirements webpage.
Read about past news on our news page.