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This is a demonstration rather than a benchmark: Quandela showed a photonic QPU exchanging data with an NVIDIA DGX Spark system over NVQLink and CUDA-Q, but the article gives no latency figures, performance comparisons, or results from the reservoir-computing workload. The practical signal is the integration pattern, with the CPU orchestrating, the GPU handling AI pre-processing, and the QPU called for specific subroutines, which matters for anyone designing hybrid HPC workflows. Readers should treat the "low-latency" claims as architectural intent until independent measurements appear.
Surse care acoperăQuantum Computing Report, The Quantum Insider
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Quandela Demonstrates Live Hybrid Photonic GPU-QPU Architecture via NVIDIA NVQLink at GTC Berlin

Quantum Computing Report2 min de cititArticolul și perspectiva sunt în engleză.

Quandela demonstrated a live hybrid AI-quantum computing system at NVIDIA GTC Berlin, showcasing photonic quantum processing units (QPUs) as integrated accelerators within HPC and AI infrastructure. The demonstration highlighted a low-latency interconnect between NVIDIA accelerated computing nodes and Quandela's photonic hardware using NVIDIA NVQLink, enabling a hybrid workflow for a quantum reservoir-computing algorithm. This development underscores Quandela's role in advancing European quantum computing infrastructure and its collaboration with partners in Germany and France. The post Quandela Demonstrates Live Hybrid Photonic GPU-QPU Architecture via NVIDIA NVQLink at GTC Berlin appeared first on Quantum Computing Report.

Photonic quantum computing developer Quandela showcased a live hybrid AI–quantum computing demonstrator at NVIDIA GTC Berlin, highlighting how photonic quantum processing units (QPUs) can function as integrated accelerators within High-Performance Computing (HPC) and…

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