Abstract

Shared-memory parallel programs can be highly nondeterministic due to the unpredictable order in which shared references are satisfied. However, deterministic execution is extremely important for debugging ’ and can also be used for fault-tolerance and other replay-based algorithms. We present a hardware/software design that allows the order of memory references in a parallel program to be logged efficiently by recording a subset of the cache traffic between memory and the CPU ‘s. This log can then be used along with hardware and software control to replay execution. Simulation of several parallel programs shows that our device records no more than 1.17 MB/second for an application exhibiting fine-grained sharing behavior on a 16-way multiprocessor consisting of 12 MIP CPU’S. In addition, no probe effect or performance degradation is introduced. This represents several orders of magnitude improvement in both performance and log size over purely software-based methods proposed previously. 1

Citations

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