In-memory parallelism for database workloads

Abstract

In this work we analyze the parallelization of database workloads for an emerging memory technology: Processing-In-Memory (PIM) chips. While most previous studies have used scientific workloads to evaluate PIM architectures, we focus on database applications as they are a dominant class of applications. For our experiments we built a simple DBMS prototype, which contains modified parallel algorithms, an in-chip data movement algorithm, and a simple query optimizer. Compared to the single processing execution, the average speedup for a PIM with 32 processing elements is 43 times. Other results show that an n-way multiprocessor of similar cost cannot perform as well. Overall, the results obtained indicate that PIM chips are an architecture with large potential for database workloads. © Springer-Verlag Berlin Heidelberg 2002.