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

  • Published:2018-08-27 Issue:24 Volume:30 Page:e4909
  • ISSN:1532-0626
  • Container-title:Concurrency and Computation: Practice and Experience
  • language:en
  • Short-container-title:Concurrency Computat Pract Exper

Author:

Valero-Lara Pedro1ORCID,Martínez-Pérez Ivan1,Sirvent Raül1,Martorell Xavier12,Peña Antonio J.1

Affiliation:

1. Barcelona Supercomputing Center (BSC); Barcelona Spain

2. Universitat Politècnica de Catalunya; Barcelona Spain

Funder

European Union's Horizon 2020 research and innovation programme

Spanish Ministry of Economy and Competitiveness under the project Computación de Altas Prestaciones VII

Departament d'Innovació, Universitats i Empresa de la Generalitat de Catalunya, under project MPEXPAR

Models de Programació i Entorns d'Execució Paral-lels

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference18 articles.

1. Many-task computing on many-core architectures;Valero-Lara;Scalable Comput: Pract Exp,2016

2. The design and performance of batched BLAS on modern high-performance computing systems;Dongarra;Procedia Comput Sci,2017

3. cuHinesBatch: solving multiple hines systems on GPUs human brain project;Valero-Lara;Procedia Comput Sci,2017

4. Energy-efficient scheduling algorithms for batch-of-tasks (BoT) applications on heterogeneous computing systems;Sajid;Concurrency Computat Pract Exper,2016

5. Optimizing tridiagonal solvers for alternating direction methods on Boolean cube multiprocessors;Ho;SIAM J Sci Stat Comput,1990

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5. LaRIS: Targeting Portability and Productivity for LAPACK Codes on Extreme Heterogeneous Systems by Using IRIS;2022 IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures Workshop (RSDHA);2022-11
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