SPIDER: An Effective, Efficient and Robust Load Scheduler for Real-time Split Frame Rendering

Bingzheng Ma, Ziqiang Zhang, Yusen Li, Wentong Cai, Gang Wang, Xiaoguang Liu

Abstract: Interactive graphics applications are generally latency-critical, while using multiple GPUs to accelerate such applications becomes possible recently with support from both hardware and software. Split frame rendering (SFR) is a popular approach for multi-GPU rendering, which splits a frame into disjoint regions and assigns the regions to different GPUs. Load scheduling of SFR is a crucial but challenging issue for achieving maximum rendering performance in real-time rendering, which is not well addressed by the existing solutions. In this paper, we propose SPIDER, a load scheduler which leverages fuzzy PID (proportional integral derivative) controller to schedule the rendering workload among GPUs. SPIDER has several distinguished properties: it is a feedback based mechanism which does not need a full knowledge of the dynamic system; it is very computationally efficient and easy to implement; it is highly robust to dynamic workload changes. Extensive experiments are conducted to evaluate SPIDER and the results show that SPIDER always achieves near-optimal performance for various workload patterns, which outperforms the state-of-the-art baselines signif-icantly.