Blog Posts

April 2nd, 2019
Intel Rendering Framework.png

Scalable Simulation, Scientific Visualization and Professional Rendering with Atipa Polaris Select HPCV Clusters

Massive data sets generated in scientific computing, big data analytics, and machine learning are overwhelmingly complex and difficult to comprehend without visual analysis. Visualizing data sets enhances the scientist’s understanding of complex ideas while also facilitating peer-to-peer communication and public outreach of scientific results – sharing raw data tables is not as effective as colorful, photorealistic visualizations that appeal to business stakeholders as well as scientists and engineers.

Traditional simulation and data analysis workflows are based on an ad-hoc model where scientific simulations are performed on a high-performance compute cluster and the results are subsequently transferred to disk for eventual visual analysis on a dedicated GPU-based workstation or cluster. For truly big data, this data movement is inefficient, time consuming, and, at scale, simply impossible.