High Performance Volume Kernels

Intel® Open Volume Kernel Library (Intel® Open VKL) is a collection of high performance volume computation kernels.

With Open VKL, you can improve your volume rendering application using a wide variety of volumetric data structures, as well as performance-optimized traversal and sampling algorithms.

We optimize Open VKL for the latest Intel® processors with support for SSE, AVX, AVX2, and AVX-512 instructions, and for ARM processors with support for the NEON instruction set.

Open VKL is available as open source under the Apache 2.0 license.

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Current Release: v1.3.0

This release adds support for new VDB volume packed data layouts, improves memory efficiency and performance for particle volumes, and adds a new AVX512 8-wide CPU device mode.

Algorithms

Point Sampling

Open VKL provides highly optimized sampling routines for all data structures.

Hit Iterators

Directly ray trace isosurfaces in your data - no meshing required!

Interval Iterators

Walk along a ray in segments, skipping empty space and getting value ranges for delta tracking or step sizes for ray marching.

Open Standards

The permissive Apache 2.0 license won't lock you in! Download the Open VKL source code on GitHub and modify it to fit your needs.

Open VKL is built with open source software such as the vectorizing Intel® ISPC compiler and Intel® Embree. Open VKL understands data stored with Open VDB, and can access it without conversion. This is a great way to enable lighting fast vectorized code in your pipeline!

Data Structures

Structured Regular

Structured regular volumes are blazingly fast, and a great option for small to medium sized data sets.

Structured Spherical

Some problems have a spherical structure. Use structured spherical volumes for efficient storage in this case!

VDB

The de facto standard in studio pipelines around the world, VDB is a sparse, hierarchical grid structure.

Adaptive Mesh Refinement

Popular in the scientific visualization community, AMR volumes provide great empty space culling and near infinite detail.

Unstructured

Unstructured volumes adapt perfectly to polygonal surface meshes, and are often used in finite element simulations.

Particle

Disintegrate your data! Particle volumes represent field data using RBF kernels centered around points in space.