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Intel® Open Volume Kernel Library

This is release v0.7.0 of Intel® Open VKL. For changes and new features see the changelog. Visit for more information.


Intel® Open Volume Kernel Library (Intel® Open VKL) is a collection of high-performance volume computation kernels, developed at Intel. The target users of Open VKL are graphics application engineers who want to improve the performance of their volume rendering applications by leveraging Open VKL’s performance-optimized kernels, which include volume traversal and sampling functionality for a variety of volumetric data formats. The kernels are optimized for the latest Intel® processors with support for SSE, AVX, AVX2, and AVX-512 instructions. Open VKL is part of the Intel® oneAPI Rendering Toolkit and is released under the permissive Apache 2.0 license.

Open VKL provides a C API, and also supports applications written with the Intel® SPMD Program Compiler (ISPC) by also providing an ISPC interface to the core volume algorithms. This makes it possible to write a renderer in ISPC that automatically vectorizes and leverages SSE, AVX, AVX2, and AVX-512 instructions. ISPC also supports runtime code selection, thus ISPC will select the best code path for your application.

In addition to the volume kernels, Open VKL provides tutorials and example renderers to demonstrate how to best use the Open VKL API.

Version History

Open VKL 0.7.0 (alpha)

  • Initial public alpha release, with support for structured, unstructured, and AMR volumes.

Support and Contact

Open VKL is under active development, and though we do our best to guarantee stable release versions a certain number of bugs, as-yet-missing features, inconsistencies, or any other issues are still possible. Should you find any such issues please report them immediately via Open VKL’s GitHub Issue Tracker (or, if you should happen to have a fix for it, you can also send us a pull request); you may also contact us via email at

Join our mailing list to receive release announcements and major news regarding Open VKL.

Intel® Open VKL API

To access the Open VKL API you first need to include the Open VKL header. For C99 or C++:

#include <openvkl/openvkl.h>

For the Intel SPMD Program Compiler (ISPC):

#include <openvkl/openvkl.isph>

This documentation will discuss the C99/C++ API. The ISPC version has the same functionality and flavor. Looking at the headers, the vklTutorialISPC example, and this documentation should be enough to figure it out.

Initialization and shutdown

To use the API, one of the implemented backends must be loaded. Currently the only one that exists is the ISPC driver. ISPC in the name here just refers to the implementation language – it can also be used from the C99/C++ APIs. To load the module that implements the ISPC driver:


The driver then needs to be selected:

VKLDriver driver = vklNewDriver("ispc");

Open VKL provides vector-wide versions for several APIs. To determine the native vector width for the given driver, call:

int width = vklGetNativeSIMDWidth();

When the application is finished with Open VKL or shutting down, call the shutdown function:


Basic data types

Open VKL defines 3-component vectors of integer and vector types:

typedef struct
  int x, y, z;
} vkl_vec3i;

typedef struct
  float x, y, z;
} vkl_vec3f;

Vector versions of these are also defined in structure-of-array format for 4, 8, and 16 wide types.

  typedef struct
    float x[WIDTH];
    float y[WIDTH];
    float z[WIDTH];
  } vkl_vvec3f##WIDTH;

  typedef struct
    float lower[WIDTH], upper[WIDTH];
  } vkl_vrange1f##WIDTH;

1-D range and 3-D ranges are defined as ranges and boxes, with no vector versions:

typedef struct
  float lower, upper;
} vkl_range1f;

typedef struct
  vkl_vec3f lower, upper;
} vkl_box3f;

Object model

Objects in Open VKL are exposed to the APIs as handles with internal reference counting for lifetime determination. Objects are created with particular type’s vklNew... API entry point. For example, vklNewData and vklNewVolume.

In general, modifiable parameters to objects are modified using vklSet... functions based on the type of the parameter being set. The parameter name is passed as a string. Below are all variants of vklSet....

void vklSetBool(VKLObject object, const char *name, int b);
void vklSetFloat(VKLObject object, const char *name, float x);
void vklSetVec3f(VKLObject object, const char *name, float x, float y, float z);
void vklSetInt(VKLObject object, const char *name, int x);
void vklSetVec3i(VKLObject object, const char *name, int x, int y, int z);
void vklSetData(VKLObject object, const char *name, VKLData data);
void vklSetString(VKLObject object, const char *name, const char *s);
void vklSetVoidPtr(VKLObject object, const char *name, void *v);

The exception to this rule is the VKLValueSelector object (described in the iterators section below), which has object-specific set methods. The reason for this is to align the C99/C++ API with the ISPC API, which can’t use a parameter method due to language limitations.

After parameters have been set, vklCommit must be called on the object to make them take effect.

Open VKL uses reference counting to manage the lifetime of all objects. Therefore one cannot explicitly “delete” any object. Instead, one can indicate the application does not need or will not access the given object anymore by calling

void vklRelease(VKLObject);

This decreases the object’s reference count. If the count reaches 0 the object will automatically be deleted.

Managed data

Large data is passed to Open VKL via a VKLData handle created with vklNewData:

VKLData vklNewData(size_t numItems,
                   VKLDataType dataType,
                   const void *source,
                   VKLDataCreationFlags dataCreationFlags);

Types accepted are listed in VKLDataType.h; basic types (UCHAR, INT, UINT, LONG, ULONG) exist as both scalar and chunked formats. The types accepted vary per volume at the moment; read the volume section below for specifics.

Data objects can be created as Open VKL owned (dataCreationFlags = VKL_DATA_DEFAULT), in which the library will make a copy of the data for its use, or shared (dataCreationFlags = VKL_DATA_SHARED_BUFFER), which will try to use the passed pointer for usage. The library is allowed to copy data when a volume is committed.

As with other object types, when data objects are no longer needed they should be released via vklRelease.

Volume types

Open VKL currently supports structured regular volumes (with user specified spacing on axes); unstructured volumes with tetrahedral, wedge, pyramid, and hexaderal primitive types; and adaptive mesh refinement (AMR) volumes. These volumes are created with vlkNewVolume with the appropriate type string.

In addition to the usual vklSet...() and vklCommit() APIs, the volume bounding box can be queried:

vkl_box3f vklGetBoundingBox(VKLVolume volume);

Structured Volume

Structured volumes only need to store the values of the samples, because their addresses in memory can be easily computed from a 3D position. A common type of structured volumes are regular grids. Structured grids are created by passing a type string of "structured_regular" to vklNewVolume.

The parameters understood by structured volumes are summarized in the table below.

Type Name Default Description
vec3i dimensions number of voxels in each dimension ((x, y, z))
data voxelData VKLData object of voxel data, supported types are:
vec3f gridOrigin ((0, 0, 0)) origin of the grid in world-space
vec3f gridSpacing ((1, 1, 1)) size of the grid cells in world-space

Additional configuration parameters for structured volumes.

The dimensions for structured volumes are in terms units vertices, not cells. For example, a volume with dimensions ((x, y, z)) will have ((x-1, y-1, z-1)) cells in each dimension. Voxel data provided is assumed vertex-centered, so (xyz) values must be provided.

Adaptive Mesh Refinement (AMR) Volume

AMR volumes are specified as a list of blocks, which exist at levels of refinement in potentially overlapping regions. Blocks exist in a tree structure, with coarser refinement level blocks containing finer blocks. The cell width is equal for all blocks at the same refinement level, though blocks at a coarser level have a larger cell width than finer levels.

There can be any number of refinement levels and any number of blocks at any level of refinement. An AMR volume type is created by passing the type string "amr" to vklNewVolume.

Blocks are defined by four parameters: their bounds, the refinement level in which they reside, the cell widths for each refinement level, and the scalar data contained within each block.

Note that cell widths are defined per refinement level, not per block.

Type Name Default Description
VKLAMRMethod method VKL_AMR_CURRENT VKLAMRMethod sampling method. Supported methods are:
box3f[] block.bounds NULL [data] array of bounds for each AMR block
int[] block.level NULL array of each block’s refinement level
float[] block.cellWidth NULL array of each block’s cell width
VKLData[] NULL [data] array of VKLData containing the actual scalar voxel data
vec3f gridOrigin ((0, 0, 0)) origin of the grid in world-space
vec3f gridSpacing ((1, 1, 1)) size of the grid cells in world-space

Additional configuration parameters for AMR volumes.

Lastly, note that the gridOrigin and gridSpacing parameters act just like the structured volume equivalent, but they only modify the root (coarsest level) of refinement.

In particular, Open VKL’s AMR implementation was designed to cover Berger-Colella [1] and Chombo [2] AMR data. The method parameter above determines the interpolation method used when sampling the volume.

  • VKL_AMR_CURRENT finds the finest refinement level at that cell and interpolates through this “current” level
  • VKL_AMR_FINEST will interpolate at the closest existing cell in the volume-wide finest refinement level regardless of the sample cell’s level
  • VKL_AMR_OCTANT interpolates through all available refinement levels at that cell. This method avoids discontinuities at refinement level boundaries at the cost of performance

Details and more information can be found in the publication for the implementation [3].

  1. M. J. Berger, and P. Colella. “Local adaptive mesh refinement for shock hydrodynamics.” Journal of Computational Physics 82.1 (1989): 64-84. DOI: 10.1016/0021-9991(89)90035-1
  2. M. Adams, P. Colella, D. T. Graves, J.N. Johnson, N.D. Keen, T. J. Ligocki. D. F. Martin. P.W. McCorquodale, D. Modiano. P.O. Schwartz, T.D. Sternberg and B. Van Straalen, Chombo Software Package for AMR Applications - Design Document, Lawrence Berkeley National Laboratory Technical Report LBNL-6616E.
  3. I. Wald, C. Brownlee, W. Usher, and A. Knoll. CPU volume rendering of adaptive mesh refinement data. SIGGRAPH Asia 2017 Symposium on Visualization on - SA ’17, 18(8), 1–8. DOI: 10.1145/3139295.3139305

Unstructured Volumes

Unstructured volumes can have their topology and geometry freely defined. Geometry can be composed of tetrahedral, hexahedral, wedge or pyramid cell types. The data format used is compatible with VTK and consists of multiple arrays: vertex positions and values, vertex indices, cell start indices, cell types, and cell values. An unstructured volume type is created by passing the type string "unstructured" to vklNewVolume.

Sampled cell values can be specified either per-vertex (vertex.value) or per-cell (cell.value). If both arrays are set, cell.value takes precedence.

Similar to a mesh, each cell is formed by a group of indices into the vertices. For each vertex, the corresponding (by array index) data value will be used for sampling when rendering, if specified. The index order for a tetrahedron is the same as VTK_TETRA: bottom triangle counterclockwise, then the top vertex.

For hexahedral cells, each hexahedron is formed by a group of eight indices into the vertices and data values. Vertex ordering is the same as VTK_HEXAHEDRON: four bottom vertices counterclockwise, then top four counterclockwise.

For wedge cells, each wedge is formed by a group of six indices into the vertices and data values. Vertex ordering is the same as VTK_WEDGE: three bottom vertices counterclockwise, then top three counterclockwise.

For pyramid cells, each cell is formed by a group of five indices into the vertices and data values. Vertex ordering is the same as VTK_PYRAMID: four bottom vertices counterclockwise, then the top vertex.

To maintain VTK data compatibility an index array may be specified via the indexPrefixed array that allows vertex indices to be interleaved with cell sizes in the following format: (n, id_1, ..., id_n, m, id_1, ..., id_m).

Type Name Default Description
vec3f[] vertex.position [data] array of vertex positions
float[] vertex.value [data] array of vertex data values to be sampled
uint32[] / uint64[] index [data] array of indices (into the vertex array(s)) that form cells
uint32[] / uint64[] indexPrefixed alternative [data] array of indices compatible to VTK, where the indices of each cell are prefixed with the number of vertices
uint32[] / uint64[] cell [data] array of locations (into the index array), specifying the first index of each cell
float[] cell.value [data] array of cell data values to be sampled
uint8[] cell.type [data] array of cell types (VTK compatible). Supported types are:
bool hexIterative false hexahedron interpolation method, defaults to fast non-iterative version which could have rendering inaccuracies may appear if hex is not parallelepiped
bool precomputedNormals false whether to accelerate by precomputing, at a cost of 12 bytes/face

Additional configuration parameters for unstructured volumes.


Computing the value of a volume at an object space coordinate is done using the sampling API. NaN is returned for probe points outside the volume.

The scalar API just takes a volume and coordinate, and returns a float value.

float vklComputeSample(VKLVolume volume, const vkl_vec3f *objectCoordinates);

Vector versions allow sampling at 4, 8, or 16 positions at once. Depending on the machine type and Open VKL driver implementation, these can give greater performance. An active lane mask valid is passed in as an array of integers; set 0 for lanes to be ignored, -1 for active lanes.

void vklComputeSample4(const int *valid,
                       VKLVolume volume,
                       const vkl_vvec3f4 *objectCoordinates,
                       float *samples);

void vklComputeSample8(const int *valid,
                       VKLVolume volume,
                       const vkl_vvec3f8 *objectCoordinates,
                       float *samples);

void vklComputeSample16(const int *valid,
                        VKLVolume volume,
                        const vkl_vvec3f16 *objectCoordinates,
                        float *samples);

All of the above sampling APIs can be used, regardless of the driver’s native SIMD width.


In a very similar API to vlkComputeSample, vlkComputeGradient queries the value gradient at an object space coordinate. Again, a scalar API, now returning a vec3f instead of a float. NaN values are returned for points outside the volume.

vkl_vec3f vklComputeGradient(VKLVolume volume,
                             const vkl_vec3f *objectCoordinates);

Vector versions are also provided:

void vklComputeGradient4(const int *valid,
                         VKLVolume volume,
                         const vkl_vvec3f4 *objectCoordinates,
                         vkl_vvec3f4 *gradients);

void vklComputeGradient8(const int *valid,
                         VKLVolume volume,
                         const vkl_vvec3f8 *objectCoordinates,
                         vkl_vvec3f8 *gradients);

void vklComputeGradient16(const int *valid,
                          VKLVolume volume,
                          const vkl_vvec3f16 *objectCoordinates,
                          vkl_vvec3f16 *gradients);

All of the above gradient APIs can be used, regardless of the driver’s native SIMD width.


Open VKL has APIs to search for particular volume values along a ray. Queries can be for ranges of volume values (vklIterateInterval) or for particular values (vklIterateHit). The desired values are set in a VKLValueSelector, which needs to be created, filled in with values, and then committed.

VKLValueSelector vklNewValueSelector(VKLVolume volume);

void vklValueSelectorSetRanges(VKLValueSelector valueSelector,
                               size_t numRanges,
                               const vkl_range1f *ranges);

void vklValueSelectorSetValues(VKLValueSelector valueSelector,
                               size_t numValues,
                               const float *values);

To query an interval, a VKLIntervalIterator of scalar or vector width must be initialized with vklInitIntervalIterator. The iterator structure is allocated and belongs to the caller, and initialized by the following functions.

void vklInitIntervalIterator(VKLIntervalIterator *iterator,
                             VKLVolume volume,
                             const vkl_vec3f *origin,
                             const vkl_vec3f *direction,
                             const vkl_range1f *tRange,
                             VKLValueSelector valueSelector);

void vklInitIntervalIterator4(const int *valid,
                              VKLIntervalIterator4 *iterator,
                              VKLVolume volume,
                              const vkl_vvec3f4 *origin,
                              const vkl_vvec3f4 *direction,
                              const vkl_vrange1f4 *tRange,
                              VKLValueSelector valueSelector);

void vklInitIntervalIterator8(const int *valid,
                              VKLIntervalIterator8 *iterator,
                              VKLVolume volume,
                              const vkl_vvec3f8 *origin,
                              const vkl_vvec3f8 *direction,
                              const vkl_vrange1f8 *tRange,
                              VKLValueSelector valueSelector);

void vklInitIntervalIterator16(const int *valid,
                               VKLIntervalIterator16 *iterator,
                               VKLVolume volume,
                               const vkl_vvec3f16 *origin,
                               const vkl_vvec3f16 *direction,
                               const vkl_vrange1f16 *tRange,
                               VKLValueSelector valueSelector);

Intervals can then be processed by calling vklIterateInterval as long as the returned lane masks indicates that the iterator is still within the volume:

int vklIterateInterval(VKLIntervalIterator *iterator,
                       VKLInterval *interval);

void vklIterateInterval4(const int *valid,
                         VKLIntervalIterator4 *iterator,
                         VKLInterval4 *interval,
                         int *result);

void vklIterateInterval8(const int *valid,
                         VKLIntervalIterator8 *iterator,
                         VKLInterval8 *interval,
                         int *result);

void vklIterateInterval16(const int *valid,
                          VKLIntervalIterator16 *iterator,
                          VKLInterval16 *interval,
                          int *result);

The intervals returned have a t-value range, a value range, and a nominalDeltaT which is approximately the step size that should be used to walk through the interval, if desired. The number and length of intervals returned is volume type implementation dependent. There is currently no way of requesting a particular splitting.

typedef struct
  vkl_range1f tRange;
  vkl_range1f valueRange;
  float nominalDeltaT;
} VKLInterval;

typedef struct
  vkl_vrange1f4 tRange;
  vkl_vrange1f4 valueRange;
  float nominalDeltaT[4];
} VKLInterval4;

typedef struct
  vkl_vrange1f8 tRange;
  vkl_vrange1f8 valueRange;
  float nominalDeltaT[8];
} VKLInterval8;

typedef struct
  vkl_vrange1f16 tRange;
  vkl_vrange1f16 valueRange;
  float nominalDeltaT[16];
} VKLInterval16;

Querying for particular values is done using a VKLHitIterator in much the same fashion. This API could be used, for example, to find isosurfaces. Again, a user allocated VKLHitIterator of the desired width must be initialized:

void vklInitHitIterator(VKLHitIterator *iterator,
                        VKLVolume volume,
                        const vkl_vec3f *origin,
                        const vkl_vec3f *direction,
                        const vkl_range1f *tRange,
                        VKLValueSelector valueSelector);

void vklInitHitIterator4(const int *valid,
                         VKLHitIterator4 *iterator,
                         VKLVolume volume,
                         const vkl_vvec3f4 *origin,
                         const vkl_vvec3f4 *direction,
                         const vkl_vrange1f4 *tRange,
                         VKLValueSelector valueSelector);

void vklInitHitIterator8(const int *valid,
                         VKLHitIterator8 *iterator,
                         VKLVolume volume,
                         const vkl_vvec3f8 *origin,
                         const vkl_vvec3f8 *direction,
                         const vkl_vrange1f8 *tRange,
                         VKLValueSelector valueSelector);

void vklInitHitIterator16(const int *valid,
                          VKLHitIterator16 *iterator,
                          VKLVolume volume,
                          const vkl_vvec3f16 *origin,
                          const vkl_vvec3f16 *direction,
                          const vkl_vrange1f16 *tRange,
                          VKLValueSelector valueSelector);

Hits are then queried by looping a call to vklIterateHit as long as the returned lane mask indicates that the iterator is still within the volume.

int vklIterateHit(VKLHitIterator *iterator, VKLHit *hit);

void vklIterateHit4(const int *valid,
                    VKLHitIterator4 *iterator,
                    VKLHit4 *hit,
                    int *result);

void vklIterateHit8(const int *valid,
                    VKLHitIterator8 *iterator,
                    VKLHit8 *hit,
                    int *result);

void vklIterateHit16(const int *valid,
                     VKLHitIterator16 *iterator,
                     VKLHit16 *hit,
                     int *result);

Returned hits consist of the t-value and volume value at that location:

typedef struct
  float t;
  float sample;
} VKLHit;

typedef struct
  float t[4];
  float sample[4];
} VKLHit4;

typedef struct
  float t[8];
  float sample[8];
} VKLHit8;

typedef struct
  float t[16];
  float sample[16];
} VKLHit16;

For both interval and hit iterators, only the vector-wide API for the native SIMD width (determined via vklGetNativeSIMDWidth can be called. The scalar versions are always valid. This restriction will likely be lifted in the future.


Open VKL ships with simple tutorial applications demonstrating the basic usage of the API, as well as full renderers showing recommended usage.


Simple tutorials can be found in the examples/ directory. These are:

  • vklTutorial.c : usage of the C API
  • vklTutorialISPC.[cpp,ispc] : combined usage of the C and ISPC APIs

For quick reference, the contents of vklTutorial.c are shown below.

#include <openvkl/openvkl.h>
#include <stdio.h>

void demoScalarAPI(VKLVolume volume)
  printf("demo of 1-wide API\n");

  // sample, gradient
  vkl_vec3f coord = {1.f, 1.f, 1.f};
  float sample    = vklComputeSample(volume, &coord);
  vkl_vec3f grad  = vklComputeGradient(volume, &coord);
  printf("\tcoord = %f %f %f\n", coord.x, coord.y, coord.z);
  printf("\t\tsample = %f\n", sample);
  printf("\t\tgrad   = %f %f %f\n\n", grad.x, grad.y, grad.z);

  // value selector setup (note the commit at the end)
  vkl_range1f ranges[2]     = {{10, 20}, {50, 75}};
  int num_ranges            = 2;
  float values[2]           = {32, 96};
  int num_values            = 2;
  VKLValueSelector selector = vklNewValueSelector(volume);
  vklValueSelectorSetRanges(selector, num_ranges, ranges);
  vklValueSelectorSetValues(selector, num_values, values);

  // ray definition for iterators
  vkl_vec3f rayOrigin    = {0, 0, 0};
  vkl_vec3f rayDirection = {1, 0, 0};
  vkl_range1f rayTRange  = {0, 200};
  printf("\trayOrigin = %f %f %f\n", rayOrigin.x, rayOrigin.y, rayOrigin.z);
  printf("\trayDirection = %f %f %f\n",
  printf("\trayTRange = %f %f\n", rayTRange.lower, rayTRange.upper);

  // interval iteration
  VKLIntervalIterator intervalIterator;

  printf("\n\tinterval iterator for value ranges {%f %f} {%f %f}\n",

  for (;;) {
    VKLInterval interval;
    int result = vklIterateInterval(&intervalIterator, &interval);
    if (!result)
        "\t\ttRange (%f %f)\n\t\tvalueRange (%f %f)\n\t\tnominalDeltaT %f\n\n",

  // hit iteration
  VKLHitIterator hitIterator;
      &hitIterator, volume, &rayOrigin, &rayDirection, &rayTRange, selector);

  printf("\thit iterator for values %f %f\n", values[0], values[1]);

  for (;;) {
    VKLHit hit;
    int result = vklIterateHit(&hitIterator, &hit);
    if (!result)
    printf("\t\tt %f\n\t\tsample %f\n\n", hit.t, hit.sample);

void demoVectorAPI(VKLVolume volume)
  printf("demo of 4-wide API (8- and 16- follow the same pattern)\n");

  vkl_vvec3f4 coord4;  // structure-of-array layout
  int valid[4];
  for (int i = 0; i < 4; i++) {
    coord4.x[i] = coord4.y[i] = coord4.z[i] = i;
    valid[i] = -1;  // valid mask: 0 = not valid, -1 = valid

  float sample4[4];
  vkl_vvec3f4 grad4;
  vklComputeSample4(valid, volume, &coord4, sample4);
  vklComputeGradient4(valid, volume, &coord4, &grad4);

  for (int i = 0; i < 4; i++) {
    printf("\tcoord[%d] = %f %f %f\n", i, coord4.x[i], coord4.y[i], coord4.z[i]);
    printf("\t\tsample[%d] = %f\n", i, sample4[i]);
    printf("\t\tgrad[%d]   = %f %f %f\n", i, grad4.x[i], grad4.y[i], grad4.z[i]);

int main()

  VKLDriver driver = vklNewDriver("ispc");

  int dimensions[] = {128, 128, 128};

  const int numVoxels = dimensions[0] * dimensions[1] * dimensions[2];

  VKLVolume volume = vklNewVolume("structured_regular");
  vklSetVec3i(volume, "dimensions", dimensions[0], dimensions[1], dimensions[2]);
  vklSetVec3f(volume, "gridOrigin", 0, 0, 0);
  vklSetVec3f(volume, "gridSpacing", 1, 1, 1);

  float *voxels = malloc(numVoxels * sizeof(float));

  if (!voxels) {
    printf("failed to allocate voxel memory!\n");
    return 1;

  // x-grad sample volume
  for (int k = 0; k < dimensions[2]; k++)
    for (int j = 0; j < dimensions[1]; j++)
      for (int i = 0; i < dimensions[0]; i++)
        voxels[k * dimensions[0] * dimensions[1] + j * dimensions[2] + i] =

  VKLData voxelData = vklNewData(numVoxels, VKL_FLOAT, voxels, 0);
  vklSetData(volume, "voxelData", voxelData);





  return 0;

Interactive examples

Open VKL also ships with an interactive example application, vklExamples. This interactive viewer demonstrates multiple example renderers including a path tracer, isosurface renderer (using hit iterators), and ray marcher. The viewer UI supports switching between renderers interactively.

Each renderer has both a C++ and ISPC implementation showing recommended API usage. These implementations are available in the examples/interactive/renderers/ directory.

Building Open VKL from source

The latest Open VKL sources are always available at the Open VKL GitHub repository. The default master branch should always point to the latest tested bugfix release.


Open VKL currently supports Linux, Mac OS X, and Windows. In addition, before you can build Open VKL you need the following prerequisites:

  • You can clone the latest Open VKL sources via:

    git clone
  • To build Open VKL you need CMake, any form of C++11 compiler (we recommend using GCC, but also support Clang and MSVC), and standard Linux development tools. To build the examples, you should also have some version of OpenGL.

  • Additionally you require a copy of the Intel® SPMD Program Compiler (ISPC), version 1.12.0 or later. Please obtain a release of ISPC from the ISPC downloads page.

  • Open VKL depends on the OSPRay common library, ospcommon. ospcommon is available at the ospcommon GitHub repository.

Depending on your Linux distribution you can install these dependencies using yum or apt-get. Some of these packages might already be installed or might have slightly different names.

CMake Superbuild

For convenience, Open VKL provides a CMake Superbuild script which will pull down Open VKL’s dependencies and build Open VKL itself. The result is an install directory, with each dependency in its own directory.

Run with:

mkdir build
cd build
cmake [<VKL_ROOT>/superbuild]
cmake --build .

The resulting install directory (or the one set with CMAKE_INSTALL_PREFIX) will have everything in it, with one subdirectory per dependency.

CMake options to note (all have sensible defaults):

  • CMAKE_INSTALL_PREFIX will be the root directory where everything gets installed.
  • BUILD_JOBS sets the number given to make -j for parallel builds.
  • INSTALL_IN_SEPARATE_DIRECTORIES toggles installation of all libraries in separate or the same directory.

For the full set of options, run ccmake [<VKL_ROOT>/superbuild].

Standard CMake build

Assuming the above prerequisites are all fulfilled, building Open VKL through CMake is easy:

  • Create a build directory, and go into it

    mkdir openvkl/build
    cd openvkl/build

    (We do recommend having separate build directories for different configurations such as release, debug, etc.).

  • The compiler CMake will use will default to whatever the CC and CXX environment variables point to. Should you want to specify a different compiler, run cmake manually while specifying the desired compiler. The default compiler on most linux machines is gcc, but it can be pointed to clang instead by executing the following:

    cmake -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang ..

    CMake will now use Clang instead of GCC. If you are ok with using the default compiler on your system, then simply skip this step. Note that the compiler variables cannot be changed after the first cmake or ccmake run.

  • Open the CMake configuration dialog

    ccmake ..
  • Make sure to properly set build mode and enable the components you need, etc.; then type ’c’onfigure and ’g’enerate. When back on the command prompt, build it using

  • You should now have as well as the tutorial / example applications.

Projects that make use of Open VKL

This page gives a brief (and incomplete) list of other projects that make use of Open VKL, as well as a set of related links to other projects and related information.

If you have a project that makes use of Open VKL and would like this to be listed here, please let us know.

  • Intel® OSPRay, a ray tracing based rendering engine for high-fidelity visualization

Projects that are closely related to Open VKL

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