Agreement with R Systems gives FieldView™ users flexible, affordable capacity to maximize productivity and results.
Rutherford, N.J — Intelligent Light is enabling computational fluid dynamics on the cloud, announcing an agreement to make FieldView™, its market-leading CFD post-processing software, available on the cloud computing capability offered by R Systems, a leader in HPC resources on demand.
Providing immediate access to flexible computing capacity, the arrangement gives FieldView users the ability to scale up using parallel processing or scale out with concurrent batch processing in order to meet their needs for more compute capacity during peak loads, special projects, or tight deadlines. FieldView's client-server architecture enables data to remain on the cloud while interactive work can be performed from the user's desktop. In addition, any CFD users who compute on the R Systems cloud can access FieldView for post-processing.
"Everyone is talking about cloud computing, but very few people are talking about successfully using it for CFD simulation," says Steve Legensky, founder and general manager of Intelligent Light. "Our arrangement with R Systems securely and efficiently addresses the challenges that large, complicated datasets can pose on the cloud. Our intention is to enable engineers and researchers to use FieldView-based post-processing as an integral part of the infrastructure of a cloud-based CFD workflow."
"R Systems' high performance computational resources combined with Intelligent Light's FieldView post-processing software provides clients an innovative tool suite that allows for maximum productivity. We see FieldView as an key enabler for CFD users wishing to leverage cloud-based resources," states Brian Kucic, R Systems' business principal. "R Systems is pleased to partner with leading independent software vendors (ISVs) such as Intelligent Light to help increase widespread adoption of HPC resources."
Testing the process
In order to test the viability of CFD post-processing on the cloud, Intelligent Light launched a pilot study, selecting R Systems as the cloud provider. The study, a wind turbine aerodynamics problem with more than 40 cases, encompassed both steady cases for power generation and unsteady cases for wake propagation. The resulting 1.4 terabytes of data were post-processed by FieldView on the cloud in both parallel and concurrent batch modes using FieldView client-server operation. The data remained on the cloud machine in all cases and was remotely accessed from a laptop. With 77,000 core hours of computation, the results proved that cloud-enabled CFD is not only possible, but valuable in terms of time and cost savings.
Accurate 'pay as you go' answers
Organizations with their own HPC resources will find cloud computing useful during peak workloads or for testing out new tools and processes without impacting their production machines, and Legensky believes small and medium size engineering enterprises will also gain significant benefits from cloud-enabled CFD.
"With relatively inexpensive HPC cloud resources and the flexibility and capabilities of FieldView, users can get the exact answers they need on a 'pay as you go' basis," he explains. "We're removing the barriers of cost, infrastructure and specialization, and leveling the CFD playing field for all users."
Legensky notes that, while the high cost of HPC equipment and the significant time and costs related to CFD solvers tend to attract the majority of management attention, the need for robust, reliable post-processing should not be overlooked. In fact, a reliable remote post-processing capability should be considered a critical component of CFD in the cloud. "Post-processing is the critical time when decisions get made," he says. "It's really the most important time in engineering - raw data has become something actionable, something you can learn from. One of FieldView's greatest strengths is its ability to quickly get users from data to decisions."
Automation, batch keys to efficiency
The advent of HPC may mean that ever larger datasets can be run, but without a highly efficient, automated post-processing workflow, "you're exposing yourself to a data tsunami," Legensky says. "You can compute really big solutions in client-server or local modes, but if you have to read the whole file every time, or have too much data to handle, you're losing valuable time. Automation and data management are key."
Automating tasks such as repeating the same set of calculations for hundreds of design variations, or creating images and animations, means increased efficiency, better accuracy, and faster results. Complete backward compatibility ensures that automated routines can be extended for use with newer datasets and future versions of FieldView, thus protecting the investments made in developing automation routines.
FieldView's feature set allows users to easily bridge the gap from interactive to fully automated and reliable batch post-processing. Earlier this year Intelligent Light introduced an innovative batch-only licensing option called FieldView Batch Packs which enable the use of multiple instances of FieldView on an HPC server for concurrent processing at a fraction of the cost of standard FieldView licenses. Concurrent batch processing reduces turnaround time and enables high throughput for transient simulations, both key to streamlining the CFD workflow. Batch operation will be supported on the R Systems cloud service.
Reaping the benefits
The power of a highly efficient CFD workflow is readily apparent in Formula 1 at Red Bull Racing, where more than 80% of their aerodynamic design is driven through CFD and FieldView. With thousands of cores running concurrently, the team's compute requirements are massive, as are the resultant datasets. While in general post-processing can take twice the time of a single solver run, nearly 90% of Red Bull Racing's post-processing tasks are automated via batch processing. Every morning, engineers receive automatically generated FieldView PDF reports, which can run to several hundred pages and include hundreds of animations. By interacting with reports rather than software, the engineering team is free to focus on results, not the process itself. A detailed case study (PDF) is available at the Intelligent Light website.
Recent research conducted by Intelligent Light on simulating the aerodynamics of a bicycle wheel also illustrates the challenges presented by large, complex data and how FieldView’s automation tools help solve them.
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