English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Realistic reservoir simulation is known to be prohibitively expensive interms of computation time when increasing the accuracy of the simulation or byenlarging the model grid size. One method to address this issue is toparallelize the computation by dividing the model in several partitions andusing multiple CPUs to compute the result using techniques such as MPI andmulti-threading. Alternatively, GPUs are also a good candidate to acceleratethe computation due to their massively parallel architecture that allows manyfloating point operations per second to be performed. The numerical iterativesolver takes thus the most computational time and is challenging to solveefficiently due to the dependencies that exist in the model between cells. Inthis work, we evaluate the OPM Flow simulator and compare severalstate-of-the-art GPU solver libraries as well as custom developed solutions fora BiCGStab solver using an ILU0 preconditioner and benchmark their performanceagainst the default DUNE library implementation running on multiple CPUprocessors using MPI. The evaluated GPU software libraries include a manuallinear solver in OpenCL and the integration of several third party sparselinear algebra libraries, such as cuSparse, rocSparse, and amgcl. To performour bench-marking, we use small, medium, and large use cases, starting with thepublic test case NORNE that includes approximately 50k active cells and endingwith a large model that includes approximately 1 million active cells. We findthat a GPU can accelerate a single dual-threaded MPI process up to 5.6 times,and that it can compare with around 8 dual-threaded MPI processes.

An Evaluation and Comparison of GPU Hardware and Solver Libraries for Accelerating the OPM Flow Reservoir Simulator