Processor-Level Selective Replication

Nithin Nakka, Karthik Pattabiraman and Ravishankar Iyer, Proceedings of the International Conference on Dependable Systems and Networks (DSN), 2007.
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Abstract: Full duplication of an entire application (through spatial or temporal redundancy) would detect many errors that are benign to the application from the perspective of the end-user. It has also been seen that duplication has upto 30% performance overhead and needs significant introduction of hardware to synchronize the replicas. In order to overcome the drawbacks of performance overhead and detection of “benign” faults, we propose a processor-level technique called Selective Replication, which provides the application the capability to choose where in its application stream and to what degree it requires replication. Recent work on static analysis and fault-injection based experiments on applications reveals that certain variables in the application are critical to its crash- and hang-free execution. If it can be ensured that the computation of these variables is error-free, then a high degree of crash/hang coverage can be achieved at a low performance overhead to the application. The Selective Replication technique provides an ideal platform for validating this claim. The technique is compared against complete duplication as provided in current architectural level techniques. The results show that with about 59% less overhead than full duplication selective replication detects 97% of the data errors and 87% of the instruction errors that were covered by full duplication. It also reduces the detection of errors benign to the final outcome of the application by 17.8% as compared to full duplication.

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