  In this work, we present a new benchmarking suite with new real-life inspired
skewed workloads to test the performance of concurrent index data structures.
We started this project to prepare workloads specifically for self-adjusting
data structures, i.e., they handle more frequent requests faster, and, thus,
should perform better than their standard counterparts. We looked over the
commonly used suites to test performance of concurrent indices trying to find
an inspiration: Synchrobench, Setbench, YCSB, and TPC - and we found several
issues with them.
  The major problem is that they are not flexible: it is difficult to introduce
new workloads, it is difficult to set the duration of the experiments, and it
is difficult to change the parameters. We decided to solve this issue by
presenting a new suite based on Synchrobench.
  Finally, we highlight the problem of measuring performance of data
structures. We show that the relative performance of data structures highly
depends on the workload: it is not clear which data structure is best. For
that, we take three state-of-the-art concurrent binary search trees and run
them on the workloads from our benchmarking suite. As a result, we get six
experiments with all possible relative performance of the chosen data
structures.
