While part 1 focused on the usage of the new NVIDIA cuTENSOR 2.0 CUDA math library, this post introduces a variety of usage modes beyond that, specifically usage from Python and Julia. We also demonstrate the performance of cuTENSOR based on benchmarks in a number of application domains. This post explores applications and performance benchmarks for cuTENSOR 2.0. For more information��
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NVIDIA cuTENSOR is a CUDA math library that provides optimized implementations of tensor operations where tensors are dense, multi-dimensional arrays or array slices. The release of cuTENSOR 2.0 represents a major update��in both functionality and performance��over its predecessor. This version reimagines its APIs to be more expressive, including advanced just-in-time compilation capabilities all��
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NVIDIA cuQuantum is an SDK of optimized libraries and tools for accelerating quantum computing workflows. With NVIDIA Tensor Core GPUs, developers can use it to speed up quantum circuit simulations based on state vector and tensor network methods by orders of magnitude. cuQuantum aims to deliver at the speed of light on NVIDIA GPUs and CPUs for quantum circuit simulations.
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High-performance computing (HPC) powers applications in simulation and modeling, healthcare and life sciences, industry and engineering, and more. In the modern data center, HPC synergizes with AI, harnessing data in transformative new ways. The performance and throughput demands of next-generation HPC applications call for an accelerated computing platform that can handle diverse workloads��
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QHack is an educational conference and the world��s largest quantum machine learning (QML) hackathon. This year at QHack 2023, 2,850 individuals from 105 different countries competed for 8 days to build the most innovative solutions for quantum computing applications using NVIDIA quantum technology. The event was organized by Xanadu, with NVIDIA sponsoring the QHack 2023 NVIDIA Challenge.
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As of March 21, 2023, QODA is now CUDA Quantum. For up-to-date information, see the CUDA Quantum page. Quantum circuit simulation is the best means to design quantum-ready algorithms so you can take advantage of powerful quantum computers as soon as they are available. NVIDIA cuQuantum is an SDK that enables you to leverage different ways to perform quantum circuit simulation. cuStateVec��
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Quantum computing aspires to deliver more powerful computation in faster time for problems that cannot currently be addressed with classical computing. NVIDIA recently announced the cuQuantum SDK, a high-performance library for accelerating the development of quantum information science. cuQuantum recently was used to break the world record for the MaxCut quantum algorithm simulation running on��
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