Publication | Open Access
Optimal Multistage Algorithm for Adjoint Computation
25
Citations
5
References
2016
Year
Large-scale Global OptimizationEngineeringComputational ComplexityAdjoint ComputationsDiscrete OptimizationFormal VerificationParallel Complexity TheoryConcurrency (Computer Science)Systems EngineeringParallel ComputingCombinatorial OptimizationAdjoint ComputationComputer ScienceOptimal AlgorithmExternal-memory AlgorithmOptimization ProblemOptimal Multistage AlgorithmConcurrency TheoryParallel ProgrammingConcurrent Data Structure
We reexamine the work of Stumm and Walther on multistage algorithms for adjoint computation. We provide an optimal algorithm for this problem when there are two levels of checkpoints, in memory and on disk. Previously, optimal algorithms for adjoint computations were known only for a single level of checkpoints with no writing and reading costs; a well-known example is the binomial checkpointing algorithm of Griewank and Walther. Stumm and Walther extended that binomial checkpointing algorithm to the case of two levels of checkpoints, but they did not provide any optimality results. We bridge the gap by designing the first optimal algorithm in this context. We experimentally compare our optimal algorithm with that of Stumm and Walther to assess the difference in performance.
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