Purpose The purpose of this paper is to achieve the acceleration of 3D object transformation using parallel techniques such as multi-core central processing unit (MC CPU) or graphic processing unit (GPU) or even both. Generating 3D animation scenes in computer graphics requires applying a 3D transformation on the vertices of the objects. These transformations consume most of the execution time. Hence, for high-speed graphic systems, acceleration of vertex transform is very much sought for because it requires many matrix operations (need) to be performed in a real time, so the execution time is essential for such processing. Design/methodology/approach In this paper, the acceleration of 3D object transformation is achieved using parallel techniques such as MC CPU or GPU or even both. Multiple geometric transformations are concatenated together at a time in any order in an interactive manner. Findings The performance results are presented for a number of 3D objects with paralleled implementations of the affine transform on the NVIDIA GPU series. The maximum execution time was about 0.508 s to transform 100 million vertices using LabVIEW and 0.096 s using Visual Studio. Other results also showed the significant speed-up compared to CPU, MC CPU and other previous work computations for the same object complexity. Originality/value The high-speed execution of 3D models is essential in many applications such as medical imaging, 3D games and robotics.

The voxelization process is an essential stage in three dimensional (3D) graphics pipeline. Its implementation should precede displaying objects in the pipeline. In this paper, different Voxelization algorithms are modified and parallelized to accelerate the operation of this stage. The 3D Digital Differential Analyzer (DDA) algorithm is used for line voxelization. This algorithm is utilized in triangle filling using the scan-line and the edge-function algorithms. The first one is designed to produce lines in parallel while the second can produce voxels. All these algorithms are parallelized using CUDA architecture and implemented on GPU processor. The actual implementation of these algorithms is examined and optimized according to the occupancy and block size metrics. The experimental results show that the acceleration amount of 3D DDA was about 4352x max compared to the OpenGL implementation, and the edge function implementation has been executed at a higher speed than the scan-line for object triangles voxelization.

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Generating 3D animation scenes in computer graphics requires applying a 3D transformation on the vertices of the objects. These transformations consume most of the execution time. Hence, for high-speed graphics systems, acceleration of vertex transform is very much sought for because it requires many matrices operations that to be performed at a real-time, so the execution time is essential for such processing. In this paper, the acceleration of 3D object transformation is achieved using parallel techniques such as Multicore Core Central Processing Unit (MC CPU) or Graphic Processing Unit (GPU) or even both. Multiple geometric transformations are concatenated together at a time in any order with interactive manner. The performance results are presented for a number of 3D objects with paralleled implementations of the affine transform on the NVIDIA GPU series. The maximum execution time was about 0.508 seconds to transform 100 million vertices. Other results also showed the significant speedup compared to (CPU and MC CPU) computations for the same object complexity.