Toward cost-effective reservoir simulation solvers on GPUs

Zheng Li, Shuhong Wu, Jinchao Xu, Chensong Zhang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


In this paper, we focus on graphical processing unit (GPU) and discuss how its architecture affects the choice of algorithm and implementation of fully-implicit petroleum reservoir simulation. In order to obtain satisfactory performance on new many-core architectures such as GPUs, the simulator developers must know a great deal on the specific hardware and spend a lot of time on fine tuning the code. Porting a large petroleum reservoir simulator to emerging hardware architectures is expensive and risky. We analyze major components of an in-house reservoir simulator and investigate how to port them to GPUs in a cost-effective way. Preliminary numerical experiments show that our GPU-based simulator is robust and effective. More importantly, these numerical results clearly identify the main bottlenecks to obtain ideal speedup on GPUs and possibly other many-core architectures.
Original languageEnglish (US)
Pages (from-to)971-991
Number of pages21
JournalAdvances in Applied Mathematics and Mechanics
Issue number6
StatePublished - Dec 1 2016
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15

ASJC Scopus subject areas

  • Applied Mathematics
  • Mechanical Engineering


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