An Analysis for the Performance of Reservoir Simulations on a Multicore CPU

Abstract

Reservoir simulations have been widely used in engineering applications in many industries. Computational performance of simulations is also important. The faster the results are obtained, the better it is for the company in terms of time and cost. This study aims at analyzing the performance of a reservoir simulation on Intel KNL, a multicore CPU, using different data formats, problem sizes, and vectorization modes. A dual porosity model with 3D single phase flow was used to carry out the simulations, implemented using PETSc library. Four fundamental cases in terms of problem sizes were simulated on KNL with varying data formats namely CSR and SELL and with four different vectorization modes such as AVX, AVX2, AVX512, and no vectorization mode. In the simulated cases, the best performance was achieved with the number of processes equal to the number of KNL cores for all configurations. Also, SELL with AVX-512 vectorization mode yielded the best performance for problem sizes occupying less than 50% of High Bandwidth Memory (HBM), followed by AVX2 and AVX. The performance of both SELL and CSR deteriorated with the problem size approaching to the memory of HBM. On the other hand, CSR AVX-512 was the best among CSR with all vectorization modes and marginally better than SELL AVX. With further usage of HBM, the best performance was obtained using CSR with AVX vectorization mode. However, generally, the performance of both CSR and SELL with any vectorization mode went down as problem size increased, but the rate of decline in performance was more for SELL than CSR. Among CSR with different vectorization modes, the performance of CSR-AVX degraded the least with increasing problem sizes. Finally, this study investigates, to the best of our knowledge, for the first time, the performance of SELL and CSR with different vectorization modes for numerical simulations with big problem sizes approaching and exceeding the size of the HBM.