Visualization of very large data sets is an important part of many data scientists workflows. The ability to make sense of the terabytes of data that a simulation can produce leads to new insights and ...

Conventional wisdom says that choosing between a GPU versus CPU architecture for running scientific visualization workloads or irregular code is easy. GPUs have long been the go-to solution, although ...

Embedded software designs such as those for avionics and automotive systems have become highly complex to develop, test and certify. As a result, the traditional document driven environments, without ...

Software Defined Visualization (SDVis) has become a mainstream idea: visualization on processors (CPUs) has enormous advantages in flexibility, cost, and performance for large visualizations. While ...