
FPGA Acceleration of Convolutional Neural Networks (CNNs)
White Paper FPGA Acceleration of Convolutional Neural Networks Overview Convolutional Neural Networks (CNNs) have been shown to be extremely effective at complex image recognition problems.
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This is an obsolete product and is no longer available for purchase. Contact BittWare for a recommended newer product.
BittWare’s A10PL4 is a low-profile PCIe x8 card based on the Intel Arria 10 GX FPGA. The Arria 10 boasts high densities and a power-efficient FPGA fabric married with a rich feature set including high-speed transceivers, hard floating-point DSP blocks, and embedded Gen3 PCIe x8. The board offers over 32 GB of memory, sophisticated clocking and timing options, and two front panel QSFP cages, each supporting 40 Gbps.
The A10PL4 also incorporates a Board Management Controller (BMC) for advanced system monitoring, which greatly simplifies platform management. All of these features combine to make the A10PL4 ideal for a wide range of applications, including network processing and security, compute and storage, instrumentation, broadcast, and SigInt.
The HRG gives you much more detail about the card such as block diagrams, tables and descriptions.
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White Paper FPGA Acceleration of Convolutional Neural Networks Overview Convolutional Neural Networks (CNNs) have been shown to be extremely effective at complex image recognition problems.
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Go Back to IP & Solutions Dynamic Neural Accelerator ML Framework EdgeCortix Dynamic Neural Accelerator (DNA), is a flexible IP core for deep learning inference