5 Questions About Reservoir Simulation Software for Stone Ridge Technology
We answer some of the most frequent questions we get about ECHELON and reservoir simulation software.
We answer some of the most frequent questions we get about ECHELON and reservoir simulation software.
Posted in: ECHELON Software
Dr. Karthik Mukundakrishnan (SRT Director of R&D) recently presented a webinar hosted by NVIDIA, highlighting the strengths and features of ECHELON, our ultra-fast, ultra-scaleable GPU-based reservoir simulation software.
This varies by model complexity and the GPU being used, but up to a 10 million active cells can be run on a single NVIDIA A100 and up to 6 million active cells can fit on most low cost workstation GPUs.
ECHELON reservoir simulation software works with legacy simulator and industry-standard input and output and can be used with Petrel, RE-Studio, S3, Tecplot, Tempest View and more.
Yes absolutely! Their small hardware footprint makes GPUs a perfect solution for simulations being performed on workstations. By using a single low cost GPU workstation, ECHELON reservoir simulation software easily outperforms other modern simulators using just the CPU.
Marathon Oil has been utilizing ECHELON software for the simulation of unconventionals for about 6 years, routinely running models in the tens of millions of cells on a modest number of GPU-based cluster nodes.
Yes! Multi-GPU and multi-node support was designed into ECHELON software from its very inception in order to handle the largest of simulation models. ECHELON software can utilize all the GPUs in a server and can run across multiple nodes using MPI communication. Performance is maximized when using Infiniband from Mellanox which allows data to be transferred between nodes without passing through CPU memory.
If you missed our webinar with NVIDIA, you can access it here.
Written by Vincent Natoli
Vincent Natoli is the president and founder of Stone Ridge Technology. He is a computational physicist with 30 years experience in the field of high-performance computing. He holds Bachelors and Masters degrees from MIT, a PhD in Physics from the University of Illinois Urbana-Champaign and a Masters in Technology Management from the Wharton School at the University of Pennsylvania.
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