FieldView Parallel addresses the bottleneck caused by ever-larger volumes of increasingly complex CFD data by maximizing the use of HPC resources for reduced turnaround time and increased throughput. While FieldView's standard license supports the use of up to 8 processor cores, affordable upgrades are available for unlimited processor counts.
Scale with Ease: For large, multi-grid solutions, FieldView Parallel enables you to scale up using 64, or unlimited cores on an HPC server or multi-core workstation (Standard FieldView supports up to eight cores and options for 64 or unlimited cores are available at 1.5 or 2x the base price). Post-processing occurs in a fraction of the time a traditional, single-processor approach would require – jobs that once required hours can now be completed in minutes.
Save Time: FieldView Parallel eliminates the time and hassle of moving data by leaving data where the solution was run. Using FieldView in client-server mode allows you to work at your desktop while the solution data remains on the server. Parallel ensures fully interactive performance and a productive computing environment: FieldView will never overburden your network because it passes small amounts of data to the workstation and maintains lightweight network communication with the server when new data is required.
Share Files with Ease: FieldView XDB files can be generated in batch and these smaller files can be downloaded, shared, and archived for further review.
FieldView Parallel works with both multi-grid Plot3D (structured) and FV-UNS (unstructured) files, and several commercial solvers will directly export multi-grid FV-UNS files. FieldView also supports multi-core (shared memory) or cluster architectures.
“FieldView is the best product I have found for interpreting large datasets. The client/server architecture of FieldView means we can analyze huge datasets without copying files around on the network. Ultimately, that means better utilization of our server resources."
Dr. Kenneth S. Brentner, Professor of Aerospace Engineering, Penn State University