GPU芯片的图形渲染引擎设计及实现

Design and Implementation of a Graphics Rendering Engine Based on GPU Chips

在当前视觉呈现领域,提高极致渲染的效率与降低延迟成为该领域的核心挑战。分割帧渲染(Scissor Frame Rendering,SFR)技术虽能提升效率,但冗余计算与图形处理器(Graphics Processing Unit,GPU)间的顺序同步限制了其在多GPU环境下的程序扩展。本研究创新性地提出了针对多GPU系统的SFR优化方案,它利用图像合成并行性,通过精细任务分配与协同机制消除了传统性能障碍。优化GPU间的数据交换,减少等待时间,智能调度最大化计算资源利用,避免冗余计算。实验证明,新方案在多GPU环境下显著提升了性能与扩展性。当GPU数量增加时,渲染效率提升,延迟保持极低,有效验证了其在大规模并行渲染中的优势。

In the current field of visual presentation,improving the efficiency of extreme rendering and reducing latency are the core challenges in this field.Although traditional split frame rendering(SFR)technology improves efficiency,redundant computation and sequential synchronization between Gpus limit program expansion in multi-GPU environments.In this study,an innovative SFR optimization scheme for multi-GPU systems is proposed,which takes advantage of image synthesis parallelism and eliminates traditional performance barriers through fine task assignment and collaboration mechanism.Optimize data exchange between Gpus,reduce waiting time,and optimize intelligent scheduling to maximize computing resource utilization and avoid redundant computing.Experiments show that the new scheme significantly improves performance and scalability in multi-GPU environment.When the number of Gpus increases,rendering efficiency increases and latency remains extremely low,effectively verifying its advantages in massively parallel rendering.