Energy efficiency and portability of oil and gas simulations on multicore and graphics processing unit architectures. (1st February 2021)

• Record Type: Journal Article
• Authors: Serpa, Matheus S.; Pavan, Pablo J.; Cruz, Eduardo H. M.; Machado, Rodrigo L.; Panetta, Jairo; Azambuja, Antônio; Carissimi, Alexandre S.; Navaux, Philippe O. A.
• Other Names: Oh Sangyoon guestEditor.; de Camargo Raphael Y. guestEditor.; Marozzo Fabrizio guestEditor.; Martins Wellington guestEditor.; Kołodziej Joanna guestEditor.; Jaatun Martin Gilje guestEditor.
• Is Part Of: Concurrency and computation. Volume 33:Number 18(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-02-01
• Subjects: code portability -- HPC -- oil and gas simulation -- performance optimization -- reverse time migration; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.6212
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Reverse time migration (RTM) simulation is the basis of the seismic imaging tools used by the oil and gas industry. Developers have been porting their simulations to the new high‐performance computing architectures, providing faster and more accurate results at each new generation. However, several challenges arrive when trying to achieve high performance on these new architectures. The first one is to choose the architecture that best fits the kind of simulation. After that, researchers should choose the API used to implement the simulation code. These two decisions are strongly related to the effort, performance, and energy efficiency of the simulations. In this article, we propose three optimizations for an oil and gas application, which reduce the floating‐point operations by changing the equation derivatives. We evaluate these optimizations in different multicore and GPU architectures, investigating the impact of different APIs on the performance, energy efficiency, and portability of the code. Our experimental results show that the dedicated CUDA implementation running on the NVIDIA Volta architecture has the best performance and energy efficiency for RTM on GPUs, while the OpenMP version is the best for Intel Broadwell in the multicore. Also, the OpenACC version, which has a lower programming effort and executes on both architectures, has an up to 20% better performance and energy efficiency than the nonportable ones.