cuThomasBatch and cuThomasVBatch, CUDA Routines to compute batch of tridiagonal systems on NVIDIA GPUs

Summary The solving of tridiagonal systems is one of the most computationally expensive parts in many applications, so that multiple studies have explored the use of NVIDIA GPUs to accelerate such computation. However, these studies have mainly focused on using parallel algorithms to compute such sy...

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Veröffentlicht in:	Concurrency and computation 2018-12, Vol.30 (24), p.n/a
Hauptverfasser:	Valero‐Lara, Pedro, Martínez‐Pérez, Ivan, Sirvent, Raül, Martorell, Xavier, Peña, Antonio J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Coalescing Computer memory CUDA cuSPARSE parallel processing PCR scalability Thomas algorithm Transformations tridiagonal linear systems
Online-Zugang:	Volltext
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