Quantum Computing

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Article

As quantum computing threatens traditional encryption, embedded systems must evolve. This article shows how iWave, in partnership with Xiphera, enables hardware-accelerated Post-Quantum Cryptography on the Altera Agilex™ 5 System on Module, delivering low-latency, quantum-resistant security for defense, telecom, automotive, and industrial applications.

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Case Study

Quantum computing demands ultra-low latency, precise timing, and real-time signal processing. This case study shows how iWave ZU11EG MPSoC System on Module, powered by AMD Zynq™ UltraScale+™ MPSoC, enables deterministic FPGA acceleration, qubit state analysis, and high-speed data transfer—delivering a production-ready platform for next-generation quantum computing systems.

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Case study

Photonic computing demands ultra-fast, low-latency electronic interfaces to match optical parallelism. This case study shows how iWave ZU49DR RFSoC System on Module and PCIe ADC-DAC card, powered by AMD Zynq™ UltraScale+™ RFSoC, enable precise RF signal capture, generation, and synchronization—bridging electronic and photonic domains for next-generation AI and HPC accelerators.

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Article

Choosing the right RFSoC doesn’t have to be complex. This Article helps you select the ideal iWave’s Zynq™ UltraScale+™ RFSoC powered by AMD and comparing variants, SD FEC features, and application trade offs showing how iWave simplifies RF and wireless system design with production-ready SoMs and RF expertise.

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Article

High-performance systems demand massive bandwidth with low latency. This article explains how iWave Versal™ Premium SoM, powered by AMD Versal™ Premium Adaptive SoC, leverages hardened CPM5 Gen5 PCIe to deliver up to 32 GB/s throughput, efficient DMA, and scalable endpoint/root-port designs for data center, networking, and storage acceleration.

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Video

This demo showcases high-performance Edge AI using iWave iW-RainboW-G57D SoM powered by AMD Versal™ AI Edge VE2302. With Mipsology NPU Stack, the platform delivers low-latency, power-efficient object detection—enabling seamless GPU-to-FPGA AI deployment for real-time edge applications.

 

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