Almost sure fault tolerance in random graphs
SIAM Journal on Computing
Built-In Testing of Integrated Circuit Wafers
IEEE Transactions on Computers
Diagnosing Arbitrarily Connected Parallel Computers with High Probability
IEEE Transactions on Computers - Special issue on fault-tolerant computing
Efficient Diagnosis of Multiprocessor Systems Under Probabilistic Models
IEEE Transactions on Computers
The consensus problem in fault-tolerant computing
ACM Computing Surveys (CSUR)
A Diagnosis Algorithm for Constant Degree Structures and Its Application to VLSI Circuit Testing
IEEE Transactions on Parallel and Distributed Systems
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Almost Sure Diagnosis of Almost Every Good Element
IEEE Transactions on Computers
Self diagnosis of processor arrays using a comparison model
SRDS '95 Proceedings of the 14TH Symposium on Reliable Distributed Systems
CorrectandAlmostCompleteDiagnosisofProcessorGrids
CorrectandAlmostCompleteDiagnosisofProcessorGrids
Evaluation of a Diagnosis Algorithm for Regular Structures
IEEE Transactions on Computers
(t, k) - Diagnosis for Matching Composition Networks under the MM* Model
IEEE Transactions on Computers
Worst-Case Diagnosis Completeness in Regular Graphs under the PMC Model
IEEE Transactions on Computers
Fast and efficient submesh determination in faulty tori
HiPC'04 Proceedings of the 11th international conference on High Performance Computing
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A new diagnosis algorithm for square grids is introduced. The algorithm always provides correct diagnosis if the number of faulty processors is below $T$, a bound with $T\in\Theta(n^{2/3})$, which was derived by worst-case analysis. A more effective tool to validate the diagnosis correctness is the syndrome dependent bound $T_\sigma$, with $T_\sigma\geq T$, asserted by the diagnosis algorithm itself for every given diagnosis experiment. Simulation studies provided evidence that the diagnosis is complete or almost complete if the number of faults is below $T$. The fraction of units which cannot be identified as either faulty or nonfaulty remains relatively small as long as the number of faults is below $n/3$ and, as long as the number of faults is below $n/2$, the diagnosis is correct with high probability.