IEEE Transactions on Parallel and Distributed Systems · 2011 · 85 citations · 40 references
ComputingComputer ScienceHigh-performance ComputingComputer GraphicsParallel AlgorithmsParallel ComputingData ParallelismGraphics Processing Unit ArchitectureGraphics Processing Unit ComputingGraphics Processing UnitsParallel ArchitecturesParallel Computer ArchitectureElectrical Power SystemsGpu ArchitectureGpu Parallel AlgorithmsParallel ProcessingParallel Processing ArchitecturesParallel ProgrammingSparse Linear AlgebraTransient Stability
This paper proposes large-scale transient stability simulation based on the massively parallel architecture of multiple graphics processing units (GPUs). A robust and efficient instantaneous relaxation (IR)-based parallel processing technique which features implicit integration, full Newton iteration, and sparse LU-based linear solver is used to run the multiple GPUs simultaneously. This implementation highlights the combination of coarse-grained algorithm-level parallelism with fine-grained data-parallelism of the GPUs to accelerate large-scale transient stability simulation. Multithreaded parallel programming makes the entire implementation highly transparent, scalable, and efficient. Several large test systems are used for the simulation with a maximum size of 9,984 buses and 2,560 synchronous generators all modeled in detail resulting in matrices that are larger than 20, 000 × 20, 000.
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