Cross-Platform Acceleration of Holographic Rendering in IoT Devices Using Open CL-Based Heterogeneous Computing
Abstract
The integration of holographic technology into IoT-enabled consumer electronics offers transformative opportunities for immersive visualization and real-time interaction. However, the high computational demand of digital holographic reconstruction algorithms poses significant challenges for real-time deployment and cross-platform scalability, limiting their broader application in IoT ecosystems. To address these challenges, this paper presents an OpenCL-based heterogeneous acceleration framework that enhances the performance and portability of digital holographic reconstruction. By leveraging the parallel computing capabilities of CPU+GPU collaboration and data-parallel programming under the OpenCL architecture, the proposed method achieves significant improvements in computational efficiency. Experimental results across various hologram resolutions and GPU platforms demonstrate up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$54.2 \times $ </tex-math></inline-formula> overall speedup and a parallel acceleration ratio of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$94.7 \times $ </tex-math></inline-formula> compared to CPU-only execution. Furthermore, the approach exhibits excellent scalability and cross-platform compatibility, making it well-suited for the real-time and embedded requirements of next-generation holographic IoT consumer devices.