NUMA-Aware Image Compositing on Multi-GPU Platform

Pan Wang, Zhi-Quan Cheng, Ralph Martin, Huahai Liu, Xun Cai, Sikun Li
Visual Computer (Special Issue of CGI 2013), 2013


   title={NUMA-Aware Image Compositing on Multi-GPU Platform},

   author={Wang, Pan and Cheng, Zhi-Quan and Martin, Ralph and Liu, Huahai and Cai, Xun and Li, Sikun},



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Sort-last parallel rendering is widely used. Recent GPU developments mean that a PC equipped with multiple GPUs is a viable alternative to a high-cost supercomputer: the Fermi architecture of s single GPU supports uniform virtual addressing, providing a foundation for non-uniform memory access (NUMA) on multi-GPU platforms. Such hardware changes require the user to reconsider the parallel rendering algorithms. In this paper, we thoroughly investigate the NUMA-aware image compositing problem, which is the key final stage in sort-last parallel rendering. Based on a proven radix-k strategy, We find one optimal compositing algorithm, which takes advantage of NUMA architecture on the multi-GPU platform. We qualitatively analyze different image compositing modes for practical image compositing, taking into account peer-to-peer communication costs between GPUs. Our experiments on various datasets show that our image compositing method is very fast, an image of a few megapixels can be composited in about 10ms by eight GPUs.
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