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FlexInstru: A flexible instrumentation framework for tracing long-running native workloads

  • East China Normal University

科研成果: 期刊稿件文章同行评审

摘要

Understanding program runtime characteristics is crucial for tasks such as optimization and workload characterization. For long-running server-side workloads that execute as native binaries, effective profiling is essential to trace their complex runtime behaviors, enabling further optimizations to improve the reliability and efficiency of the delivered services. Widely adopted techniques for profiling these workloads include binary instrumentation and hardware-based profiling. Binary instrumentation is typically accurate but incurs high overhead and lacks flexibility for tracing long-running native workloads. Hardware-based profiling brings low overhead while requiring hardware support. To overcome these limitations, we present FlexInstru, a hardware-independent dynamic instrumentation framework based on the process attachment/detachment mechanism. FlexInstru can flexibly instrument a native application at any time and for any duration when the application is running, and achieve a good balance between instrumentation accuracy and overhead, which makes it particularly effective in tracing long-running native workloads. FlexInstru provides a process attachment/detachment mechanism on Linux, allowing attaching an instrumentation engine to a long-running native workload and detaching it at any time. To mitigate overhead, FlexInstru also enables flexible control of instrumentation through multiple attachments/detachments, allowing the workload to alternate between instrumented execution and native execution. Moreover, during instrumented execution, FlexInstru supports a sampling mechanism to collect data only during the sampling period, further reducing the overhead. We evaluate FlexInstru on AArch64 and X86-64 using real-world workloads. For MySQL's branch recording tasks, FlexInstru substantially reduces instrumentation overhead, with reductions of 415.60 × on AArch64 and 1223.02 × on X86-64 compared to traditional dynamic instrumentation, while maintaining sufficient accuracy.

源语言英语
文章编号112739
期刊Journal of Systems and Software
234
DOI
出版状态已出版 - 4月 2026

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