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HeapMon: A helper-thread approach to programmable, automatic, and low-overhead memory bug detection

机译:HeapMon:一种辅助线程方法,用于可编程,自动和低开销的内存错误检测

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The ability to detect and pinpoint memory-related bugs in production runs is important because in-house testing may miss bugs. This paper presents HeapMon, a heap memory bug-detection scheme that has a very low performance overhead, is automatic, and is easy to deploy. HeapMon relies on two new techniques. First, it decouples application execution from bug monitoring, which executes as a helper thread on a separate core in a chip multiprocessor system. Second, it associates a filter bit with each cached word to safely and significantly reduce bug checking frequency—by 95% on average. We test the effectiveness of these techniques using existing and injected memory bugs in SPEC~®2000 applications and show that HeapMon effectively detects and identifies most forms of heap memory bugs. Our results also indicate that the HeapMon performance overhead is only 5%, on average—orders of magnitude less than existing tools. Its overhead is also modest: 3.1% of the cache size and a 32-KB victim cache for on-chip filter bits and 6.2% of the allocated heap memory size for state bits, which are maintained by the helper thread as a software data structure.
机译:在生产过程中检测和查明与内存相关的错误的能力非常重要,因为内部测试可能会漏掉错误。本文介绍了HeapMon,这是一种堆内存错误检测方案,它具有非常低的性能开销,自动且易于部署。 HeapMon依赖于两种新技术。首先,它将应用程序的执行与错误监视分离开来,该错误监视在芯片多处理器系统中的单独内核上作为帮助线程执​​行。其次,它将过滤器位与每个高速缓存的字相关联,以安全且显着地减少错误检查频率-平均降低95%。我们使用SPEC〜®2000应用程序中现有的和注入的内存错误来测试这些技术的有效性,并证明HeapMon有效地检测和识别了大多数形式的堆内存错误。我们的结果还表明,HeapMon的性能开销平均仅为5%,比现有工具少几个数量级。它的开销也很适中:片上过滤器位的高速缓存大小的3.1%和32-KB牺牲者高速缓存,状态位的高速缓存的大小为6.2%的已分配堆内存大小,它们由帮助程序线程作为软件数据结构进行维护。 。

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