Hasso-Plattner-Institut
Prof. Dr. Tilmann Rabl
  
 

Lawrence Benson

Ph.D. Student
Room: F-1.05
Phone: +49-(0)331 5509-4857
E-Mail: lawrence.benson(at)hpi.de

Full Profile

Research Interests

  • Data Processing on Modern Hardware
  • Persistent Memory (PMem)
  • Efficient Stream Processing

Check out my personal website for some more information.

Publications

  • Viper: An Efficient Hybrid PMem-DRAM Key-Value Store @ VLDB 2021
    Lawrence Benson, Hendrik Makait, Tilmann Rabl
    > Paper  > Code (external)
  • Maximizing Persistent Memory Bandwidth Utilization for OLAP Workloads @ SIGMOD 2021
    Björn Daase, Lars Jonas Bollmeier, Lawrence Benson, Tilmann Rabl
    > Paper  > Code (external) 
  • Drop It In Like It's Hot: An Analysis of Persistent Memory as a Drop-in Replacement for NVMe SSDs @ DaMoN 2021
    Maximilian Böther, Otto Kißig, Lawrence Benson, Tilmann Rabl
    > Paper  > Code (external)
  • Disco: Efficient Distributed Window Aggregation @ EDBT 2020
    Lawrence Benson, Phillip M. Grulich, Steffen Zeuch, Volker Markl, Tilmann Rabl
    > Paper (external)   > Poster (external)   > Code (external)   > Talk (external, YouTube)

 

Students

If you would like to work together on a general research project or your master thesis, please just reach out. You can propose your own ideas, but I usually also have some project ideas lying around. You can also check out our open theses page for a few suggestions. I'm happy to assist you if you want to write a research paper. This can be extracurricular and does not have to be part of a seminar or thesis. I'm currently supervising a few student papers and theses. 

Student Paper Supervision:

Thesis Supervision:

  • R-Tree Data Placement on Persistent Memory, Nils Thamm, Master Thesis, 2021

Teaching

Lectures:

Projects/Seminars:

  • Data Management on Modern Storage Technologies (Master, Winter 2020/21)
  • Open Source Data Processing (Master, Winter 2020/21)
  • Data Processing on Modern Hardware (Master, Summer 2020)

Master Project Supervision:

  • Processor-Specific Stream Processing Query Compilation (Summer 2021)
  • Compilation Techniques for Dynamic Stream Processing (Summer 2020)
  • Dynamic Stream Processing (Winter 2019/20)