Reduce the complexity of programming around GPUs. Develop high-performance, photorealistic, extensible, and cost-effective visualization applications through open source libraries that are optimized on Intel® Xeon® processors.

Benefits

Deliver high-performance, high-fidelity visualization solutions and applications efficiently with open source rendering libraries in Intel® Rendering Framework. The libraries are:

  • Intel® Embree, a ray tracing kernel library adopted by more than 80 independent software vendors (ISV) for its extensibility (64- and 32-bit Windows*, macOS* 10.x, Linux* support), and vast feature set for complex rendering and shading frameworks.
  • Intel® OSPRay, a cluster-capable, scalable, extendable, ray-tracing, rendering toolkit that includes path tracing and volume rendering. It efficiently uses threading and vectorization to create interactive, high-fidelity applications on CPUs from Intel.
  • Intel® OpenSWR, an OpenGL* low-level rasterization library upstreamed to the Mesa OpenGL open source project to achieve high rendering performance when GPUs are unavailable or are too limiting. Completely CPU-based and built on top of LLVM, this library provides performance advantages over Mesa llvmpipe renderers.
  • Intel® Open Image Denoise, an open source library of image denoising and filtering algorithms to improve visual quality and reduce rendering times.

Intel® Rendering Framework is a software defined visualization (SDVis) approach for supporting big data use on platforms of all sizes, including cloud and high-performance computing (HPC) clusters. This is achieved by enabling the parallelism and performance already in your CPU-based Intel® platforms without the memory limits and cost of GPU-based solutions.

To make it even easier to use this ground-breaking visual technology, Intel collaborated with hardware and software providers to design Intel® Select Solutions for Professional Visualization. These turnkey solutions provide an out-of-the-box experience for combining computationally intense codes with photorealistic rendering and visual analysis tools used in science, manufacturing, professional rendering, architecture, gaming, and more.

Rethink Visual Cloud Workload Distribution

Deploy Anywhere, Anytime, Any-Scale Visualization with Intel® Select Solution

Open Source Libraries from Intel Play a Major Role in Hollywood

Introduction to SDVis

Tech.Decoded: Moana and Pacific Rim—Rendering New Realities


Software Libraries

Enhance existing applications with rendering libraries for parallel software.

Engineers of rendering applications use these ray-tracing kernels to improve application performance. The kernels are optimized for photorealistic rendering on the latest Intel® processors with support for Intel® Streaming SIMD Extensions [4.2] and Intel® Advanced Vector Extensions 512.

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Photo credit: Courtesy of Attila Afra, Intel1

This portable ray-tracing engine delivers high-performance, high-fidelity visualization for CPUs on Intel® architecture. The rendering library allows you to create interactive, high-fidelity, rendering applications.

Intel OSPRay builds on top of Intel Embree and the Intel® MPI Library.

Intel OSPRay Overview Video

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Photo credit: Courtesy of Ingo Wald and Carson Brownlee, Intel2

This is a high-performance, scalable software rasterizer in the Mesa open source community project that's compatible with OpenGL*. Use unmodified visualization software to work with datasets when GPU hardware is unavailable or is limiting. This CPU-based product runs on laptops, workstations, and compute nodes in high-performance computing (HPC) systems.

Mesa OpenGL* Library

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Photo credit: Courtesy of Silvio Rizzi and Joe Insley, Argonne National Laboratory3

Intel® Open Image Denoise

This high-performance, open source library improves visual quality during interaction by using machine learning methods (includes Intel® Math Kernel Library for Deep Neural Networks functions) to selectively filter noise. This independent component can be used for noise reduction on 3D rendered images, with or without Intel Embree.

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Photo credit: Courtesy of Walt Disney Animation Studios

Sources

1. Data is reproduced under the Evermotion Commercial License Agreement. Visualization from Attila Afra, Intel, Mazda.

2. Data from Computational Framework for Launch, Ascent, and Vehicle Aerodynamics (LAVA), courtesy of Mike Barad and Cetin Kiris, NASA Ames. Visualization from Ingo Wald and Carson Brownlee, Intel, Landing Gear.

3. Data from courtesy of Salman Habib, Katrin Heitmann, and Hardware/Hybrid Accelerated Cosmology Code (HACC) at Argonne National Laboratory. Visualization from Silvio Rizzi and Joe Insley, Argonne Leadership Computing Facility, Dark Matter with VL3 and OpenSWR.

4. Publicly available dataset courtesy of Walt Disney Animation Studios. The image is rendered with Intel OSPRay and Intel Open Image Denoise.