CAT: Context Aware Tracing for Rust Asynchronous Programs

Tsung Yen Wang, Shao Hua Wang, Chia Heng Tu, Wen Yew Liang

研究成果: Conference contribution

摘要

Modern programming languages, such as Rust, have adopted the coroutine concept to better utilize computation resources and to improve program execution efficiency by allowing the overlap of the execution for asynchronous tasks. These programming languages often use the concept of userland thread library to dispatch the asynchronous tasks defined by the programmers. Nevertheless, it is often the case that the task scheduling on a user-space library is non-preemptive and would lead to unbounded execution time of a task.In this work, we aim to develop a tracing methodology to capture unbounded execution time of asynchronous tasks in Rust programs. Based on the analyses of the Rust standard library, we identify several execution contexts of asynchronous computation in Rust, and develop a portable context aware tracing methodology that is able to trace the execution time of nested asynchronous computation work across different Rust runtimes. We develop a framework, called CAT, to collect and visualize the asynchronous runtime activities. The results show that CAT can help pinpoint the asynchronous computation exhibiting prolonged execution time. We believe that CAT is a complement of existing tools to improve the execution efficiency of asynchronous operations in Rust.

原文English
主出版物標題Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, SAC 2023
發行者Association for Computing Machinery
頁面483-492
頁數10
ISBN(電子)9781450395175
DOIs
出版狀態Published - 2023 3月 27
事件38th Annual ACM Symposium on Applied Computing, SAC 2023 - Tallinn, Estonia
持續時間: 2023 3月 272023 3月 31

出版系列

名字Proceedings of the ACM Symposium on Applied Computing

Conference

Conference38th Annual ACM Symposium on Applied Computing, SAC 2023
國家/地區Estonia
城市Tallinn
期間23-03-2723-03-31

All Science Journal Classification (ASJC) codes

  • 軟體

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