Browsing by Author "Yuksel, Cem"

Now showing 1 - 4 of 4
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    Deferred Adaptive Compute Shading
    (ACM, 2018) Mallett, Ian; Yuksel, Cem; Patney, Anjul and Niessner, Matthias
    A primary advantage of deferred shading is eliminating wasted shading operations due to overdraw. We present a new algorithm that we call Deferred Adaptive Compute Shading, for providing further reduction in shading computations. Our method hierarchically shades the image while reducing the number of required shading operations to below one shading computation per pixel on average. We determine whether to shade a pixel or approximate it using previously shaded pixels around it, based on an estimate of the image variance at the pixel location. The algorithm is designed to dynamically reconfigure itself to achieve optimal warp coherence and measurable performance gain. We extensively evaluate our algorithm, demonstrating that it produces high-quality results and is robust and highly scalable while providing significant performance improvements in complex scenes.
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    Mach-RT: A Many Chip Architecture for Ray Tracing
    (The Eurographics Association, 2019) Vasiou, Elena; Shkurko, Konstantin; Brunvand, Erik; Yuksel, Cem; Steinberger, Markus and Foley, Tim
    We propose an unconventional solution to high-performance ray tracing that combines a ray ordering scheme that minimizes access to the scene data with a large on-chip buffer acting as near-compute storage that is spread over multiple chips. We demonstrate the effectiveness of our approach by introducing Mach-RT (Many chip - Ray Tracing), a new hardware architecture for accelerating ray tracing. Extending the concept of dual streaming, we optimize the main memory accesses to a level that allows the same memory system to service multiple processor chips at the same time. While a multiple chip solution might seem to imply increased energy consumption as well, because of the reduced memory traffic we are able to demonstrate, performance increases while maintaining reasonable energy usage compared to academic and commercial architectures.
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    Rethinking Texture Mapping
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Yuksel, Cem; Lefebvre, Sylvain; Tarini, Marco; Giachetti, Andrea and Rushmeyer, Holly
    The intrinsic problems of texture mapping, regarding its difficulties in content creation and the visual artifacts it causes in rendering, are well-known, but often considered unavoidable. In this state of the art report, we discuss various radically different ways to rethink texture mapping that have been proposed over the decades, each offering different advantages and trade-offs. We provide a brief description of each alternative texturing method along with an evaluation of its strengths and weaknesses in terms of applicability, usability, filtering quality, performance, and potential implementation related challenges.
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    Stochastic Lightcuts
    (The Eurographics Association, 2019) Yuksel, Cem; Steinberger, Markus and Foley, Tim
    We introduce stochastic lightcuts by combining the lighting approximation of lightcuts with stochastic sampling for efficiently rendering scenes with a large number of light sources. Our stochastic lightcuts method entirely eliminates the sampling correlation of lightcuts and replaces it with noise. To minimize this noise, we present a robust hierarchical sampling strategy, combining the benefits of importance sampling, adaptive sampling, and stratified sampling. Our approach also provides temporally stable results and lifts any restrictions on the light types that can be approximated with lightcuts. We present examples of using stochastic lightcuts with path tracing as well as indirect illumination with virtual lights, achieving more than an order of magnitude faster render times than lightcuts by effectively approximating direct illumination using a small number of light samples, in addition to providing temporal stability. Our comparisons to other stochastic sampling techniques demonstrate that we provide superior sampling quality that matches and improves the excellent convergence rates of the lightcuts approach.