English

GAPP: A Fast Profiler for Detecting Serialization Bottlenecks in Parallel Linux Applications

Performance 2020-04-14 v1 Distributed, Parallel, and Cluster Computing

Abstract

We present a parallel profiling tool, GAPP, that identifies serialization bottlenecks in parallel Linux applications arising from load imbalance or contention for shared resources . It works by tracing kernel context switch events using kernel probes managed by the extended Berkeley Packet Filter (eBPF) framework. The overhead is thus extremely low (an average 4% run time overhead for the applications explored), the tool requires no program instrumentation and works for a variety of serialization bottlenecks. We evaluate GAPP using the Parsec3.0 benchmark suite and two large open-source projects: MySQL and Nektar++ (a spectral/hp element framework). We show that GAPP is able to reveal a wide range of bottleneck-related performance issues, for example arising from synchronization primitives, busy-wait loops, memory operations, thread imbalance and resource contention.

Keywords

Cite

@article{arxiv.2004.05628,
  title  = {GAPP: A Fast Profiler for Detecting Serialization Bottlenecks in Parallel Linux Applications},
  author = {Reena Nair and Tony Field},
  journal= {arXiv preprint arXiv:2004.05628},
  year   = {2020}
}

Comments

8 pages

R2 v1 2026-06-23T14:48:33.945Z