Fast CSV Loading Using GPUs – TUB and DFKI Paper Accepted at BTW 2021

A paper on the accelerated loading of CSV data using GPUs and RDMA by researchers from the Database Systems and Information Management Group (DIMA) at TU Berlin and the Intelligent Analytics for Massive Data (IAM) research group at DFKI was accepted at the 19th symposium "Datenbanksysteme für Business, Technologie und Web" [1] (BTW 2021), which will take place from September 20 - 24, 2021. The publication was awarded with the BTW 2021 Reproducibility Badge.

In their Paper „Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing“ Alexander Kumaigorodski, Clemens Lutz and Volker Markl devise a new CSV parsing approach that streamlines the control flow while correctly handling context-sensitive CSV features. By offloading I/O and parsing to the GPU, their approach enables databases to load CSVs at high throughput from main memory with NVLink 2.0, as well as directly from the network with RDMA.

> „Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing“ [PDF] [2]