
二進位加權神經網路推理的 FPGA 加速
White Paper FPGA Acceleration of Binary Weighted Neural Network Inference One of the features of YOLOv3 is multiple-object recognition in a single image. We used
At the heart of RFX products is the revolutionary AMD RFSoC chip, giving you a range of advantages over discreet systems. However, BittWare has leveraged our analog and digital design heritage to bring you more than expected from a typical RF card:
RFX cards and modules are built around the powerful AMD RFSoC devices. We bring analog signals in, but it’s the direct RF chip approach that packs so much analog and digital functionality that many racks of previous equipment are no longer necessary!
The RFX family is designed as standalone cards or as modules in servers. We recommend the WaveBox family of enclosures and servers for the optimum mix of features and the advantage of purchasing an integrated system. Learn more on the WaveBox product page.
At the heart of RFX cards and modules is the AMD RFSoC chip. It combines many of the traditionally discreet RF analog and digital components into a compact, configurable device. Applications including Satcom and test/measurement can benefit from these revolutionary devices.
But with RFX we’ve gone further—bringing to the PCIe form factor optional mixers, amplifiers, and filters. The RFX is configurable too, with up to four inputs/outputs and first/second/third Nyquist filters.
Choose from on-card filtering and amplification targeting first, second, or third (partial) Nyquist. Or choose “wideband” and bring your own external filtering. Here’s the input ADC:
There are four of these ADC channels, each factory configurable (talk to us for pricing and availability).
Four DACs provide 30 to 6 GHz with low-pass filtering. This transmit side diagram is below:
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White Paper FPGA Acceleration of Binary Weighted Neural Network Inference One of the features of YOLOv3 is multiple-object recognition in a single image. We used
PCIe FPGA 卡 250-SoC 薄型 UltraScale+ MPSoC 卡需要報價嗎?跳轉到定價表 準備好購買了嗎?概述 250-SoC 具有
用於 AI 金融交易模型的 MAU 加速器參考設計 超低延遲、高輸送量的機器學習推理 非常適合金融領域的一系列應用
PCIe FPGA Card 520NX Stratix 10 AI-optimized FPGA with HBM2 AI-Optimized for High-Bandwidth, Low-Latency AI Acceleration Obsolete Product Notice: This is an obsolete product and