Zobrazeno 1 - 10
of 154
pro vyhledávání: '"Wald, Ingo"'
Autor:
Wald, Ingo, Zellmann, Stefan, Amstutz, Jefferson, Wu, Qi, Griffin, Kevin, Jaros, Milan, Wesner, Stefan
We propose and discuss a paradigm that allows for expressing \emph{data-parallel} rendering with the classically non-parallel ANARI API. We propose this as a new standard for data-parallel sci-vis rendering, describe two different implementations of
Externí odkaz:
http://arxiv.org/abs/2407.00179
Autor:
Usher, Will, Wald, Ingo, Amstutz, Jefferson, Günther, Johannes, Brownlee, Carson, Pascucci, Valerio
Image- and data-parallel rendering across multiple nodes on high-performance computing systems is widely used in visualization to provide higher frame rates, support large data sets, and render data in situ. Specifically for in situ visualization, re
Externí odkaz:
http://arxiv.org/abs/2305.07083
Adaptive Mesh Refinement (AMR) is becoming a prevalent data representation for scientific visualization. Resulting from large fluid mechanics simulations, the data is usually cell centric, imposing a number of challenges for high quality reconstructi
Externí odkaz:
http://arxiv.org/abs/2211.09997
Autor:
Wald, Ingo
We present an algorithm that allows for building left-balanced and complete k-d trees over k-dimensional points in a trivially parallel and GPU friendly way. Our algorithm requires exactly one int per data point as temporary storage, and uses O(log N
Externí odkaz:
http://arxiv.org/abs/2211.00120
Autor:
Wald, Ingo
We present an algorithm that allows for find-closest-point and kNN-style traversals of left-balanced k-d trees, without the need for either recursion or software-managed stacks; instead using only current and last previously traversed node to compute
Externí odkaz:
http://arxiv.org/abs/2210.12859
Autor:
Sahistan, Alper, Demirci, Serkan, Wald, Ingo, Zellmann, Stefan, Barbosa, João, Morrical, Nathan, Güdükbay, Uğur
Computational fluid dynamic simulations often produce large clusters of finite elements with non-trivial, non-convex boundaries and uneven distributions among compute nodes, posing challenges to compositing during interactive volume rendering. Correc
Externí odkaz:
http://arxiv.org/abs/2209.14537
Autor:
Wald, Ingo, Parker, Steven G
We investigate the concept of rendering production-style content with full path tracing in a data-distributed fashion -- that is, with multiple collaborating nodes and/or GPUs that each store only part of the model. In particular, we propose a new ap
Externí odkaz:
http://arxiv.org/abs/2204.10170
Autor:
Zellmann, Stefan, Seifried, Daniel, Morrical, Nate, Wald, Ingo, Usher, Will, Law-Smith, Jamie A. P., Walch-Gassner, Stefanie, Hinkenjann, André
Modern GPUs come with dedicated hardware to perform ray/triangle intersections and bounding volume hierarchy (BVH) traversal. While the primary use case for this hardware is photorealistic 3D computer graphics, with careful algorithm design scientist
Externí odkaz:
http://arxiv.org/abs/2202.12020
Autor:
Wald, Ingo
We describe a simple yet highly parallel method for re-indexing "indexed" data sets like triangle meshes or unstructured-mesh data sets -- which is useful for operations such as removing duplicate or un-used vertices, merging different meshes, etc. I
Externí odkaz:
http://arxiv.org/abs/2109.09812
Autor:
Morrical, Nathan, Tremblay, Jonathan, Lin, Yunzhi, Tyree, Stephen, Birchfield, Stan, Pascucci, Valerio, Wald, Ingo
We present a Python-based renderer built on NVIDIA's OptiX ray tracing engine and the OptiX AI denoiser, designed to generate high-quality synthetic images for research in computer vision and deep learning. Our tool enables the description and manipu
Externí odkaz:
http://arxiv.org/abs/2105.13962