Abstract
In this paper, we propose an OpenCL framework for GPU clusters. The target cluster architecture consists of a single host node and multiple compute nodes. They are connected by an interconnection network, such as Gigabit and InfiniBand switches. Each compute node consists of multiple GPUs. Each GPU becomes an OpenCL compute device. The host node executes the host program in an OpenCL application. Our OpenCL framework provides an illusion of a single system for the user. It allows the application to utilize GPUs in a compute node as if they were in the host node. No communication API, such as the MPI library, is required in the application source. We show that the original OpenCL semantics naturally fits to the GPU cluster environment, and the framework achieves both high performance and ease of programming. We implement the OpenCL framework and evaluate its performance on a GPU cluster that consists of one host and eight compute nodes using six OpenCL benchmark applications.
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Kim, J., Seo, S., Lee, J., Nah, J., Jo, G., Lee, J. (2013). OpenCL as a Programming Model for GPU Clusters. In: Rajopadhye, S., Mills Strout, M. (eds) Languages and Compilers for Parallel Computing. LCPC 2011. Lecture Notes in Computer Science, vol 7146. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36036-7_6
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DOI: https://doi.org/10.1007/978-3-642-36036-7_6
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