Figure three. Streaming Architecture. Every CNN layer is mapped right into a hardware block, as well as components blocks are connected to every Other individuals by way of stream channels. The bitwidth of every stream is proven on this determine.
CNN Implementation on FPGA: Venieris et al. confirmed within their study [fourteen] that hardware architecture for CNN implementation on FPGA can be classified into two major types: streaming architectures and single computation engine.
Determine 8 displays the architecture on the integrated procedure on chip. AXI-Lite interface offers the interconnection concerning the PS along with the PL. The DMA module is integrated within the PL. This module is responsible for converting the memory mapped input to AXI stream CNN input, as well as converting the AXI stream CNN output to the memory mapped output.
In this segment, we clarify the look with the components streaming architecture for your hand pose estimation CNN plus the components architecture for different CNN layers.
In the same way to Figure 9, the figures to the arrows illustrate the variables by which the performance differs for various implementations.
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Desk three offers different operate-time delays for our FPGA implementation when compared to various GPU implementations. In all scenarios, the typical run-time hold off for every graphic Δ T i m a g e
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