Optimization of Forward Wave Modeling on Contemporary HPC Architectures

Krueger, Jens¹  Micikevicius, Paulius²  Williams, Samuel³ 

[1] Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States);NVIDIA, Santa Clara, CA (United States);Fraunhofer ITWM, Kaiserslautern (Germany)

关键词: Reverse Time Migration;    forward wave modeling;    multicore;    GPU;   

DOI  :  10.2172/1223018
RP-ID  :  LBNL--5751E
PID  :  OSTI ID: 1223018

学科分类：数学（综合）

美国|英语

来源: SciTech Connect

【 摘 要 】

Reverse Time Migration (RTM) is one of the main approaches in the seismic processing industry for imaging the subsurface structure of the Earth. While RTM provides qualitative advantages over its predecessors, it has a high computational cost warranting implementation on HPC architectures. We focus on three progressively more complex kernels extracted from RTM: for isotropic (ISO), vertical transverse isotropic (VTI) and tilted transverse isotropic (TTI) media. In this work, we examine performance optimization of forward wave modeling, which describes the computational kernels used in RTM, on emerging multi- and manycore processors and introduce a novel common subexpression elimination optimization for TTI kernels. We compare attained performance and energy efficiency in both the single-node and distributed memory environments in order to satisfy industry???s demands for fidelity, performance, and energy efficiency. Moreover, we discuss the interplay between architecture (chip and system) and optimizations (both on-node computation) highlighting the importance of NUMA-aware approaches to MPI communication. Ultimately, our results show we can improve CPU energy efficiency by more than 10?? on Magny Cours nodes while acceleration via multiple GPUs can surpass the energy-efficient Intel Sandy Bridge by as much as 3.6??.