Sirin, UtkuAilamaki, Anastasia2020-10-152020-10-152020-10-152020-02-0110.14778/3380750.3380755https://infoscience.epfl.ch/handle/20.500.14299/172467WOS:000573955200005Understanding micro-architectural behavior is important for efficiently using hardware resources. Recent work has shown that in-memory online transaction processing (OLTP) systems severely underutilize their core micro-architecture resources [29]. Whereas, online analytical processing (OLAP) workloads exhibit a completely different computing pattern. OLAP workloads are read-only, bandwidth-intensive, and include various data access patterns. With the rise of column-stores, they run on high-performance engines that are tightly optimized for modern hardware. Consequently, micro-architectural behavior of modern OLAP systems remains unclear.This work presents a micro-architectural analysis of a set of OLAP systems. The results show that traditional commercial OLAP systems suffer from their long instruction footprint, which results in high response times. High-performance columnstores execute tight instruction streams; however, they spend 25 to 82% of their CPU cycles on stalls both for sequential- and random-access-heavy workloads. Concurrent query execution can improve the utilization, but it creates interference in the shared resources, which results in sub-optimal performance.Computer Science, Information SystemsComputer Science, Theory & MethodsComputer Sciencecoroutinestext::journal::journal article::research article