ARMONK, N.Y., April 25, 2017 /PRNewswire/ -- IBM
(NYSE: IBM) and Stone Ridge Technology today announced a
performance milestone in reservoir simulation designed to help
improve efficiency and lower the cost of production. Working with
NVIDIA, the companies shattered previous published results using
one-tenth the power and 1/100th of the space. The news
demonstrates the ability of NVIDIA GPUs to simulate one billion
cell models in a fraction of the published time, while delivering
10x the performance and efficiency than legacy CPU codes.
The breakthrough achievement used 60 Power processors and 120 GPU
accelerators shattering the previous supercomputer
record which used over a 700,000 processors. The results aim
to transform the price and performance for business critical High
Performance Computing (HPC) applications for simulation and
exploration.
Energy companies use reservoir modeling to predict the flow of oil,
water and natural gas in the subsurface of the earth before they
drill to figure out how to more efficiently extract the most oil. A
billion-cell simulation is extremely challenging due to the level
of detail it seeks to provide. Stone Ridge Technology, maker of the
ECHELON petroleum reservoir simulation software, completed the
billion-cell reservoir simulation in 92 minutes using 30 IBM Power
Systems S822LC for HPC servers equipped with 60 POWER processors
and 120 NVIDIA® Tesla™ P100 GPU accelerators.
"This calculation is a very salient demonstration of the
computational capability and density of solution that GPUs offer.
That speed lets reservoir engineers run more models and 'what-if'
scenarios than previously so they can have insights to produce oil
more efficiently, open up fewer new fields and make responsible use
of limited resources" said Vincent
Natoli, President of Stone Ridge Technology. "By increasing
compute performance and efficiency by more than an order of
magnitude, we're democratizing HPC for the reservoir simulation
community."
"This milestone calculation illuminates the advantages of the IBM
POWER architecture for data intensive and cognitive workloads."
said Sumit Gupta, IBM Vice
President, High Performance Computing, AI & Analytics. "By
running ECHELON on IBM Power Systems, users can achieve faster
run-times using a fraction of the hardware. The previous record
used more than 700,000 processors in a supercomputer installation
that occupies nearly half a football field. Stone Ridge did this calculation on two racks
of IBM Power Systems machines that could fit in the space of half a
ping-pong table."
This latest advance challenges perceived misconceptions that
GPUs could not be efficient on complex application codes like
reservoir simulators and are better suited to simple, more
naturally parallel applications such as seismic imaging. The scale,
speed and efficiency of the reported result disprove this
preconception. The milestone calculation with a relatively small
server infrastructure enables small and medium-size oil and energy
companies to take advantage of computer-based reservoir modeling
and optimize production from their asset portfolio.
Billion cell simulations in the industry are rare in practice,
but the calculation was accomplished to highlight the performance
differences between new fully GPU based codes like the ECHELON
reservoir simulator and equivalent legacy CPU codes. ECHELON scales
from the cluster to the workstation and while it can simulate a
billion cells on 30 servers, it can also run smaller models on a
single server or even on a single NVIDIA P100 board in a desktop
workstation, the latter two use cases being more in the sweet spot
for the energy industry.
"The energy industry was among the first to adopt GPUs for
numerical modeling, using them to accelerate seismic processing,"
said Marc Hamilton, Vice President
of Solutions Architecture and Engineering at NVIDIA. "They are
now making a powerful impact on reservoir simulation, and we expect
this to drive further efforts to utilize GPUs for other
computationally intense workflows in the oil and gas sector."
This latest breakthrough showcases the ability of IBM Power Systems
with NVIDIA GPUs to achieve similar performance leaps in other
fields such as computational fluid dynamics, structural mechanics,
climate modeling and others that are critically used throughout the
manufacturing and scientific community.
Contact:
Courtney Lowell
IBM Media Relations
Courtney.lowell@ibm.com
512-599-1676
Kristin Bryson
NVIDIA Media Relations
kbryson@nvidia.com
203-241-9190
Vincent Natoli
Stone Ridge Technology
vnatoli@stoneridgetechnology.com
443-299-7927
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SOURCE IBM