Shadowcatcher ftw:zeitmeister wrote:You choose a 3D model, you choose a backplate hdri, you choose the materials, AND IT almost FITS VERY CLOSE TO REALITY.
Never seen that before.
http://www.youtube.com/watch?v=msI-MObRAIg
Shadowcatcher ftw:zeitmeister wrote:You choose a 3D model, you choose a backplate hdri, you choose the materials, AND IT almost FITS VERY CLOSE TO REALITY.
Never seen that before.
Monte Carlo Light Transport algorithms such as Path Tracing (PT), Bi-Directional Path Tracing (BDPT) and Metropolis Light Transport (MLT) make use of random walks to sample light transport paths. When parallelizing these algorithms on the GPU the stochastic termination of random walks results in an uneven workload between samples, which reduces SIMD efficiency. In this paper we propose to combine stream compaction and sample regeneration to keep SIMD efficiency high during random walk construction, in spite of stochastic termination. Furthermore, for BDPT and MLT, we propose to evaluate all bidirectional connections of a sample in parallel in order to balance the workload between GPU threads and improve SIMD efficiency during sample evaluation. We present efficient parallel GPU-only implementations for PT, BDPT, and MLT in CUDA.We show that our GPU implementations outperform similar CPU implementations by an order of magnitude.
Already reported it to Glare via eMail on the 20.07.2011CoolColJ wrote:He posted another paper
Users browsing this forum: No registered users and 43 guests