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+ Current generation GPUs are capable of processing TFLOP/s which in turn makes
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+ application with large bandwidth requirements and simple algorithms
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+ I/O-bound. Applications that receive data from external data sources are hit
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+ twice because data first has to be transferred into system main memory before
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+ being moved to the GPU in a second transfer.
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+
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+ To remedy this problem, we designed and implemented a system architecture
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+ comprising a custom FPGA board with a flexible DMA transfer policy and a
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+ heterogeneous compute framework receiving data using AMD's DirectGMA
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+ OpenCL extension.
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+
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+ With our proposed system architecture we are able to sustain the bandwidth
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+ requirements of various applications such as real-time tomographic image
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+ reconstruction and signal analysis with a peak FPGA-GPU throughput of XXX GB/s.
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