SCOZ: A system-wide causal profiler for multicore systems

Minwoo Ahn, Donghyun Kim, Taekeun Nam, Jinkyu Jeong

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The increased complexity of hardware and software makes it difficult to analyze programs with conventional profilers. The causal profiling technique is introduced to solve the problem of conventional profilers. The causal profiling technique finds the bottleneck of the program and shows the effect of optimizing it. COZ, the newest causal profiler, exploits a technique called virtual speedup to perform causal profiling without actually optimizing program codes. However, it can only profile multithreaded applications, and cannot profile multiprogram applications and operating system (OS) kernel codes, thereby limiting the use of causal profiling. This article introduces SCOZ, a system-wide causal profiler that addresses these limitations. The proposed profiler changes the target of virtual speedup from threads to CPU cores, thereby expanding the profiling coverage to diverse applications as well as OS kernel codes. To verify our profiler, we profiled multithreaded and OS kernel-intensive applications. For multithread applications, our profiler shows identical results to what COZ provides. For the OS kernel-intensive applications, our profiler identifies identical bottlenecks that previous OS scalability studies have pinpointed. Finally, we verified the profiling capability of the proposed profiler by profiling and optimizing multiprocess applications in the NAS parallel benchmark suite.

    Original languageEnglish
    Pages (from-to)1043-1058
    Number of pages16
    JournalSoftware - Practice and Experience
    Volume51
    Issue number5
    DOIs
    Publication statusPublished - 2021 May

    Bibliographical note

    Funding Information:
    Korea Institute for Advancement of Technology (KIAT), Korea Government (MOTIE), The Competency Development Program for Industry Specialist, N0001883; Samsung Electronics, National Research Foundation of Korea (NRF), NRF‐2020R1A2C2102406 Funding information

    Funding Information:
    This work was supported partly by Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE) (N0001883, The Competency Development Program for Industry Specialist) and by Samsung Electronics.

    Publisher Copyright:
    © 2020 The Authors. Software: Practice and Experience published by John Wiley & Sons Ltd.

    All Science Journal Classification (ASJC) codes

    • Software

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