Butterfly analysis: adapting dataflow analysis to dynamic parallel monitoring

Online program monitoring is an effective technique for detecting bugs and security attacks in running applications. Extending these tools to monitor parallel programs is challenging because the tools must account for inter-thread dependences and relaxed memory consistency models. Existing tools assume sequential consistency and often slow down the monitored program by orders of magnitude. In this paper, we present a novel approach that avoids these pitfalls by not relying on strong consistency models or detailed inter-thread dependence tracking. Instead, we only assume that events in the distant past on all threads have become visible; we make no assumptions on (and avoid the overheads of tracking) the relative ordering of more recent events on other threads. To overcome the potential state explosion of considering all the possible orderings among recent events, we adapt two techniques from static dataflow analysis, reaching definitions and reaching expressions, to this new domain of...

• Type: Conference
• Year: 2010
• Where: ASPLOS
• Authors: Michelle L. Goodstein, Evangelos Vlachos, Shimin Chen, Phillip B. Gibbons, Michael A. Kozuch, Todd C. Mowry
• Keywords: ASPLOS 2010, Consistency Models, Inter-thread Dependence, Memory Consistency Models, Programming Languages