Work

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

Year: 2020

Type: conference-paper

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% runtime 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.

Source: ACM/SPEC International Conference on Performance Engineering (ICPE)

DOI: 10.1145/3358960.3379136

Authors: Reena Nair, Tony Field

Institution: Imperial College London

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Commonwealth Scholarship Commission

Award: G8942358466