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@@ -116,12 +116,14 @@ developed a high-performance DMA engine based on Xilinx's PCIe Gen3 Core.To
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process the data, we encapsulated the DMA setup and memory mapping in a plugin
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for our scalable GPU processing framework~\cite{vogelgesang2012ufo}. This
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framework allows for an easy construction of streamed data processing on
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-heterogeneous multi-GPU systems. The framework is based on OpenCL, and
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+heterogeneous multi-GPU systems. Because the framework is based on OpenCL,
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integration with NVIDIA's CUDA functions for GPUDirect technology is not
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-possible. We therefore integrated direct FPGA-to-GPU communication into our
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-processing pipeline using AMD's DirectGMA technology. In this paper we report
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-the performance of our DMA engine for FPGA-to-CPU communication and some
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-preliminary measurements about DirectGMA's performance in low-latency applications.
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+possible at the moment. Thus, we used AMD's DirectGMA technology to integrate
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+direct FPGA-to-GPU communication into our processing pipeline. In this paper we
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+report the performance of our DMA engine for FPGA-to-CPU communication and some
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+preliminary measurements about DirectGMA's performance in low-latency
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+applications.
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+
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\section{Architecture}
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@@ -143,7 +145,7 @@ they are not directly involved in the data transfer anymore.
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In a traditional DMA architecture (a), data are first written to the main
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system memory and then sent to the GPUs for final processing. By using
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GPUDirect/DirectGMA technology (b), the DMA engine has direct access to
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- GPU's internal memory.
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+ the GPU's internal memory.
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}
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\label{fig:trad-vs-dgpu}
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\end{figure}
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