SIGMOD 2020 Best Paper Award
BIFOLD Researchers Receive SIGMOD 2020 Best Paper Award
Database systems researchers at TU Berlin, HPI and DFKI were highly successful this year. Four of their papers were accepted at the 2020 ACM SIGMOD/PODS International Conference on the Management of Data. And, in particular, one of the paper’s received the 2020 ACM SIGMOD Best Paper Award. The paper entitled “Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects,” by Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, and Volker Markl explores the use of GPUs to accelerate database query processing. GPUs are generally ill-suited for large-scale data processing for two reasons: (1) the on-board memory capacity is too small to store large datasets, and (2) the interconnect bandwidth to CPU main-memory is insufficient for ad-hoc data transfers. As a result, GPU-based systems face data transfer bottlenecks and do not scale to large datasets. In the paper, the authors demonstrate how a fast interconnect, such as NVLink 2.0 (linking dedicated GPUs to a CPU) can overcome the two scalability issues for a no-partitioning hash join. Consequently, the experiments achieved a speed-up of up to 18x over PCI-e 3.0 and up to 7.3x over an optimized CPU implementation. To download a preprint of the paper visit: https://bit.ly/3bHb3XO.
 TU Berlin Database Systems & Information Management Group, https://www.dima.tu-berlin.de/.
 Hasso Plattner Institute, Data Engineering Systems Group, https://hpi.de/rabl/home.html.
 DFKI Intelligent Analytics for Massive Data Group, https://bit.ly/2LKoY4Y.
 Four papers authored by TU Berlin and DFKI researchers have been accepted at SIGMOD 2020, https://bifold.berlin/sigmod-2020/
 The 2020 ACM SIGMOD / PODS International Conference on the Management of Data, https://sigmod2020.org/.
 “Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects,” Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, and Volker Markl,https://bit.ly/3bHb3XO.
 A blog posting by Clemens Lutz, https://e2data.eu/blog/fast-gpu-interconnects.