Megakernels considered harmful

Laine, Samuli; Karras, Tero; Aila, Timo

doi:10.1145/2492045.2492060

Cited by 74 publications

(15 citation statements)

References 20 publications

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“…Rendering We use our own path tracer (PT) rendering pipeline as baseline engine. This PT uses an implementation inspired by Wavefront [VA11, LKA13], powered by Embree [WWB * 14]. We distribute render work in tiles of (25,25) pixels that perform path–tracing in usual Wavefront steps (ray generation, intersection, shading, connection), each tile using a separate CPU thread.…”

Section: Implementation Detailsmentioning

confidence: 99%

NEnv: Neural Environment Maps for Global Illumination

Rodríguez-Pardo

Fabre

Garcés

et al. 2023

Computer Graphics Forum

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Environment maps are commonly used to represent and compute far‐field illumination in virtual scenes. However, they are expensive to evaluate and sample from, limiting their applicability to real‐time rendering. Previous methods have focused on compression through spherical‐domain approximations, or on learning priors for natural, day‐light illumination. These hinder both accuracy and generality, and do not provide the probability information required for importance‐sampling Monte Carlo integration. We propose NEnv, a deep‐learning fully‐differentiable method, capable of compressing and learning to sample from a single environment map. NEnv is composed of two different neural networks: A normalizing flow, able to map samples from uniform distributions to the probability density of the illumination, also providing their corresponding probabilities; and an implicit neural representation which compresses the environment map into an efficient differentiable function. The computation time of environment samples with NEnv is two orders of magnitude less than with traditional methods. NEnv makes no assumptions regarding the content (i.e. natural illumination), thus achieving higher generality than previous learning‐based approaches. We share our implementation and a diverse dataset of trained neural environment maps, which can be easily integrated into existing rendering engines.

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Section: Implementation Detailsmentioning

confidence: 99%

NEnv: Neural Environment Maps for Global Illumination

Rodríguez-Pardo

Fabre

Garcés

et al. 2023

Computer Graphics Forum

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“…The uncoupled, highly parallel and rather simple nature of the optical physics that is sufficient to describe neutrino detectors makes optical photon propagation well suited to general purpose GPU computing techniques where high performance requires massive parallelism with minimal communication between threads and low register usage [11].…”

Section: Introductionmentioning

confidence: 99%

Opticks : GPU Optical Photon Simulation for Particle Physics using NVIDIA® OptiX™

2017

J. Phys.: Conf. Ser.

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Abstract.Opticks is an open source project that integrates the NVIDIA OptiX GPU ray tracing engine with Geant4 toolkit based simulations. Massive parallelism brings drastic performance improvements with optical photon simulation speedup expected to exceed 1000 times Geant4 when using workstation GPUs. Optical photon simulation time becomes effectively zero compared to the rest of the simulation. Optical photons from scintillation and Cherenkov processes are allocated, generated and propagated entirely on the GPU, minimizing transfer overheads and allowing CPU memory usage to be restricted to optical photons that hit photomultiplier tubes or other photon detectors. Collecting hits into standard Geant4 hit collections then allows the rest of the simulation chain to proceed unmodified. Optical physics processes of scattering, absorption, scintillator reemission and boundary processes are implemented in CUDA OptiX programs based on the Geant4 implementations. Wavelength dependent material and surface properties as well as inverse cumulative distribution functions for reemission are interleaved into GPU textures providing fast interpolated property lookup or wavelength generation. Geometry is provided to OptiX in the form of CUDA programs that return bounding boxes for each primitive and ray geometry intersection positions. Some critical parts of the geometry such as photomultiplier tubes have been implemented analytically with the remainder being tessellated. OptiX handles the creation and application of a choice of acceleration structures such as boundary volume hierarchies and the transparent use of multiple GPUs. OptiX supports interoperation with OpenGL and CUDA Thrust that has enabled unprecedented visualisations of photon propagations to be developed using OpenGL geometry shaders to provide interactive time scrubbing and CUDA Thrust photon indexing to enable interactive history selection.

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“…-Summarises the underlying split-kernel architecture [11] that is state-of-the-art for performant GPU path tracers.…”

Section: Thesis Aims and Contributionsmentioning

confidence: 99%

“…Since GPUs perform best on coherent workloads, it is often beneficial to sort the data before a GPU kernel operates on it. For example, in Megakernels Considered Harmful [11] Laine et. al.…”

Section: Gpu Radix Sortmentioning

confidence: 99%

“…al. [11], the path tracers are split into many separate kernels to maximise coherence and throughput, and make use of stream compaction between those kernels to ensure full utilisation of the GPU's SIMD groups. Since the number of paths active at each stage is unknown by the CPU, the GPU writes the active path count to a buffer at various stages, which is then read by subsequent stages and used to terminate threads whose index is greater than the path count and therefore have no work to do.…”

Section: Stream Compactionmentioning

confidence: 99%

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Interactive Generation of Path-Traced Lightmaps

Roughton¹

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<p>Indirect illumination is an important part of realistic images, and accurately simulating the complex effects of indirect illumination in real-time applications has long been a challenge for the industry. One popular approach is to use offline precomputed solutions such as lightmaps (textures containing the precomputed lighting in a scene) to efficiently approximate these effects. Unfortunately, these offline solutions have historically enforced long iteration times that come at a cost to artist productivity. These solutions have additionally either supported only the low-frequency diffuse component of indirect lighting, yielding poor visual results for glossy or metallic materials, or have used overly expensive approximations. In recent years, the state of the art lightmap precomputation pipeline has shifted to using highly vectorised path tracing, often on GPU hardware, to compute the indirect illumination effects. The use of path tracing enables progressive rendering, wherein an approximation to the full solution is found and then refined as opposed to solving for the final result in a single step. Progressive rendering through path tracing thereby helps to provide rapid iteration for artists. This thesis describes a system that can progressively path-trace indirect illumination lightmaps on the GPU.Contributing to this system, itintroduces a new gather-based method for sample accumulation, enhances algorithms from prior work, and presents a range of encoding methods, including a novel progressive method for non-negative least-squares encoding of spherical basis functions. In addition, it presents a novel, efficient solution for high-quality precomputed diffuse and low-frequency specular indirect illumination that extends the Ambient Dice family of spherical basis functions. This solution provides comparable or better specular reconstruction to prior work at lower runtime cost and has potential for widespread use in real-time applications.</p>

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Megakernels considered harmful

Cited by 74 publications

References 20 publications

NEnv: Neural Environment Maps for Global Illumination

NEnv: Neural Environment Maps for Global Illumination

Opticks : GPU Optical Photon Simulation for Particle Physics using NVIDIA® OptiX™

Interactive Generation of Path-Traced Lightmaps

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