Low-Latency Transaction Execution on Graphics Processors: Dream or Reality?

In this paper we take a close look into the role of GPUs for executing OLTP workloads, with a focus on CRUD operatorbased processing, as opposed to more complex OLTP transactions. To this end we develop a prototype system supporting GPU and CPU variants of DSM and NSM processing, with a delegation-based approach that uses a singlethread scheduler to manage concurrency control, enabling reads with guaranteed bounded staleness. We evaluate our prototype using workloads from the Yahoo! cloud serving benchmark. We report the impact of layout choices, batching configuration and concurrency control designs. Through our study we are able to pinpoint that the contradicting needs in GPU processing for small batches to reduce waiting time, but large batches to reduce execution time, is the essential challenge for OLTP on these processors, affecting all design choices we study. Hence, we propose two preconditions for supporting OLTP with GPUs, aiming to guide researchers in finding scenarios for extending the applicability of GPUs in supporting data management tasks.