![]() CMB is a framework that simplifies developing simulation frameworks, enabling scientists and engineers to focus on their domain expertise rather than worrying about the integration of disparate software and simulation codes. However such simulation workflows are typically highly specific to a domain, requiring complex combinations of sophisticated computing tools to implement. Modeling and simulation are tasks pervasive to the design and manufacturing of modern, high-quality products. Contact: Utkarsh Ayachit CMB: Computational Model Builder We expect a public prototype to be available for comment and experimentation by early summer, with an early release available for SuperComputing 2022. With a concerted effort now underway, the major objectives are designing and implementing concurrent pipelines, in which rendering and data processing pipelines do not block one another and supporting pervasive interruptibility, ensuring that filters can be interrupted or aborted at any time to provide application responsiveness. Over the past couple of years the Scientific Computing Team has envisioned an improved ParaView that is more interactive and responsive no matter the computational load. Contact: Berk Geveci Next Generation ParaView: ParaView async We hope to demonstrate the use of VTK-m in end-to-end simulation workflows through the Catalyst and Ascent in situ libraries on next generation supercomputers. We are also pushing tighter integration of VTK-m into VTK and ParaView where users will be able to choose a runtime option to replace certain filters with their VTK-m counterparts. In 2022, our focus will be on continuing the port of VTK-m to new GPU architectures including AMD and Intel GPUs. It provides the building blocks for portable algorithm development and a number of core visualization algorithm implementations. VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures, especially GPUs. Adding support for meshes used in simulations based on discontinuous Galerkin methods.Improving accuracy for statistical filters when operating on point fields by adding support for ghost points.VTK’s ongoing performance improvements due to CPU threading (vtkSMPTools) and GPU accelerators (vtk-m).ParaView 5.10.0 was released in January, and we expect to release 5.11.0 in May and 5.12.0 in October. The next VTK 9.2 release is expected in the spring of 2022 and 9.3 in the fall of 2022. ParaView / VTKĭevelopment of VTK and ParaView continues at a ferocious pace. Throughout the year, we’ll be announcing these tools as they arrive, in many cases we will be looking for help from the community to test, evaluate, and guide our development efforts. In the following, we provide high-level summaries of a small subset of the work we are undertaking this year, with contact information if you’d like to learn more. Building off of the success our world class open source platforms VTK and ParaView, we will be introducing new capabilities that dramatically increase performance and ease of use significantly improve end-to-end workflows for large-scale simulation and experimental science support ongoing advances in AR/VR hardware and rendering and introduce a new Python-based, web integration framework that weaves together visual analytics tools for large scale data analysis. Kitware’s Scientific Computing Team is looking forward to another year of groundbreaking technical advances.
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