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TOD-Tree: Task-Overlapped Direct Send Tree Image Compositing for Hybrid MPI Parallelism and GPUs.
IEEE Trans Vis Comput Graph ; 23(6): 1677-1690, 2017 06.
Article in En | MEDLINE | ID: mdl-26992102
ABSTRACT
Modern supercomputers have thousands of nodes, each with CPUs and/or GPUs capable of several teraflops. However, the network connecting these nodes is relatively slow, on the order of gigabits per second. For time-critical workloads such as interactive visualization, the bottleneck is no longer computation but communication. In this paper, we present an image compositing algorithm that works on both CPU-only and GPU-accelerated supercomputers and focuses on communication avoidance and overlapping communication with computation at the expense of evenly balancing the workload. The algorithm has three stages a parallel direct send stage, followed by a tree compositing stage and a gather stage. We compare our algorithm with radix-k and binary-swap from the IceT library in a hybrid OpenMP/MPI setting on the Stampede and Edison supercomputers, show strong scaling results and explain how we generally achieve better performance than these two algorithms. We developed a GPU-based image compositing algorithm where we use CUDA kernels for computation and GPU Direct RDMA for inter-node GPU communication. We tested the algorithm on the Piz Daint GPU-accelerated supercomputer and show that we achieve performance on par with CPUs. Last, we introduce a workflow in which both rendering and compositing are done on the GPU.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: IEEE Trans Vis Comput Graph Journal subject: INFORMATICA MEDICA Year: 2017 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: IEEE Trans Vis Comput Graph Journal subject: INFORMATICA MEDICA Year: 2017 Document type: Article