Hongbo Kang

Hongbo Kang is a PhD candidate in computer science at Tsinghua University, and his research interests include designing theoretically and practically efficient parallel algorithms, especially on new hardware.
His previous research primarily focused on processing-in-memory (PIM) systems, where he proposed a theoretical model, designed theoretically efficient parallel algorithms, and implemented these algorithms on real-world PIM systems to demonstrate their superiority.
His research demonstrates that through the collaboration of traditional central processing units (CPUs) and in-memory processors, a novel algorithm can reduce the data movement both asymptotically and in practice.
His prior work on PIM-optimized ordered index, known as PIM-tree, achieves these improvements and received the Best Paper Runner-Up Award at VLDB 2023.
His research interests also include non-volatile memory systems and learned indexes.