Heterogeneous many-core optimization for Monte Carlo path-tracing on new generation Sunway HPC system
Xinjie Wang, Guanghao Ma, Jiaying Song, Mingyao Geng, Wenhui Hu, Xi Duan, Zhigang Wang, Jiali Xu, Xiaogang Jin, Fang Li, Dexun Chen, Maoxue Yu · CCF Transactions on High Performance Computing · 2024
Abstract We present swRender, a new parallel rendering pipeline based on the new Sunway many-core architecture (SW26010P) for the Monte Carlo path-tracing algorithm. Previous parallel rendering schemes are unsuitable for our task due to issues such as vast differences in hardware architectures and bottlenecks in I/O communication efficiency. To that end, we create a new two-level parallel tile rendering framework to fully utilize the Sunway computing resources, a practical tile-grouping load-balancing method to maintain the framework’s stability, and a novel many-core acceleration optimization to improve the rendering performance at the pixel level. Our method achieves (1) an average speedup of 16x in multiple benchmarks when compared to the baseline path-tracing model on the Sunway architecture, and (2) an average speedup of 2x when compared to state-of-the-art CPU, co-processor, and GPU-based parallel rendering approaches. Moreover, we scale swRender to run on 15 million cores and obtain high scalable parallel efficiency of 92%.