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“…Convolution is a computationally-intensive task that can be accelerated using the concurrent processors [26]. Mathematically, it can be expressed as the sum of the products of mask/filter coefficients with the input function/image.…”
Section: Convolutional Layermentioning
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“…Convolution is a computationally-intensive task that can be accelerated using the concurrent processors [26]. Mathematically, it can be expressed as the sum of the products of mask/filter coefficients with the input function/image.…”
Section: Convolutional Layermentioning
“…In half of the studies we consider here, the FPGA outperforms the GPU—at least for some of the reported problems and problem sizes . This is also true if we only examine applications which require real‐time performance (GPU as winner: ; FPGA as winner: ). In the only comparison addressing truly embedded devices , the FPGA has the lead (GPU Nvidia ION 2 vs. FPGA Xilinx Spartan–3).…”
Section: Introductionmentioning
“…In half of the studies we consider here, the FPGA outperforms the GPU-at least for some of the reported problems and problem sizes [16,17,19,21,23,24,27,30,31]. This is also true if we only examine applications which require real-time performance (GPU as winner: [22,25,26]; FPGA as winner: [27,30]). In the only comparison addressing truly embedded devices [27], the FPGA has the lead (GPU Nvidia ION 2 vs. FPGA Xilinx Spartan-3).A rather small number of these studies also includes considerations regarding energy consumption based on power specifications supplied by the manufacturers [7,21,24,27]; studies with actual power measurements [8,19,22,31,32] are even more rare.…”
mentioning
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