The NVIDIA CUDA-Q platform is designed to streamline software and hardware development for hybrid, accelerated quantum supercomputers. Users can write code once, test it on any QPU or simulator, and accelerate all parts of the workflow. This liberates time for achieving scientific breakthroughs rather than waiting for results. CUDA-Q v0.10 has more features and increased performance…
]]>NVIDIA’s vision of accelerated quantum supercomputers integrates quantum hardware and AI supercomputing to turn today’s quantum processors into tomorrow’s useful quantum computing devices. At Supercomputing 2024 (SC24), NVIDIA announced a wave of projects with partners that are driving the quantum ecosystem through those challenges standing between today’s technologies and this accelerated…
]]>NVIDIA CUDA-Q is an open-source programming model for building quantum-classical applications. Useful quantum computing workloads will run on heterogeneous computing architectures such as quantum processing units (QPUs), GPUs, and CPUs in tandem to solve real-world problems. CUDA-Q enables the acceleration of such applications by providing the tools to program these computing architectures…
]]>Heterogeneous computing architectures—those that incorporate a variety of processor types working in tandem—have proven extremely valuable in the continued scalability of computational workloads in AI, machine learning (ML), quantum physics, and general data science. Critical to this development has been the ability to abstract away the heterogeneous architecture and promote a framework that…
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