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Offline symbolic analysis to infer Total Store Order

机译:离线符号分析以推断总商店订单

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摘要

Ability to record and replay an execution can significantly help programmers debug their programs, especially parallel programs. De-terministically replaying a multiprocessor's execution under a relaxed memory model has remained a challenging problem. This is an important problem as most modern processors only support a relaxed memory model to enable many performance critical optimizations. The most common consistency model implemented in processors is the Total Store Order (TSO). We present an efficient and low-complexity processor based solution for recording and replaying under the Total Store Order (TSO) memory model. Processor provides support for logging data fetched on cache misses. Using this information each thread can be de-terministically replayed. A TSO-compliant casual order between the shared-memory accesses executed in different threads is then inferred using an offline algorithm based on Satisfiability Modulo Theory (SMT) solver. We also discuss methods to bound the search space during offline analysis and several optimizations to reduce the offline analysis time.
机译:记录和重放执行的能力可以极大地帮助程序员调试其程序,尤其是并行程序。在宽松的内存模型下确定性地重播多处理器的执行仍然是一个具有挑战性的问题。这是一个重要的问题,因为大多数现代处理器仅支持宽松的内存模型以实现许多性能关键的优化。在处理器中实现的最常见的一致性模型是总存储订单(TSO)。我们提出了一种基于高效且低复杂度的处理器的解决方案,用于在总存储订单(TSO)内存模型下进行记录和重放。处理器支持对由于缓存未命中而获取的数据进行记录。使用此信息,可以确定性地重播每个线程。然后使用基于满意度模理论(SMT)求解器的脱机算法来推断在不同线程中执行的共享内存访问之间符合TSO的临时顺序。我们还将讨论在脱机分析期间限制搜索空间的方法,以及一些减少脱机分析时间的优化方法。

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