GTC 2023 Quantum Computing Highlights
Quantum computing has the potential to offer disruptive leaps in computational capabilities, impacting a vast range of applications from drug discovery to routing optimization. However, quantum computers still have a ways to go in order to be useful for real-world applications. The ability of scientists, developers, and researchers to simulate quantum circuits on classical computers, and integrate classical supercomputers with quantum computing in a performant way is vital to getting us there. NVIDIA is working with a wide range of groups within the quantum computing space to enable just that.?
Join us at GTC on March 20-23 to explore the latest in research, and products in addition to hearing about some of the industry use cases leveraging NVIDIA technology to push the field of quantum computing toward useful applications.?
Check out our top Quantum Computing sessions ahead of you at #GTC23. You don’t want to miss out!
Simulation of quantum circuits is essential to adapt quantum algorithms toward commercial applicability. Over the last year, the BMW Group Quantum Team has set out to scale simulated quantum experiments toward industry-scale problems. We'll overview how the BMW team leverages GPUs to accelerate quantum circuit simulations based on state vector and tensor network methods for industry problems. We navigate different industry problems in quantum machine learning (e.g., sampling from complex distribution functions for generative modeling) and quantum optimization (e.g., maximum independent set problems for sensor positioning for highly automated driving functions). We show how simulation can ease the path toward commercial applicability.
Quantum computing has the potential to offer giant leaps in computational capabilities. Realizing these benefits requires pushing the boundaries of quantum information science now in developing algorithms, researching more capable quantum processors, and creating tightly integrated quantum-classical systems and tools. We'll review these challenges facing quantum computing, offer insight into how GPU supercomputing can help move industries toward quantum advantage, and discuss the latest developments in software and systems for tightly integrated quantum-classical computing.
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For the programmer who wants to do algorithm research and build hybrid applications for future quantum advantage, a bridging technology is needed to enable dynamic workflows across disparate system architectures. We'll dive into the details of QODA, the programming model for hybrid quantum-classical computing, and NVQ++, NVIDIA's C++ quantum computing compiler.
Quantum computers (QC) are still many years away from commercialization, but businesses, industries, and government agencies are already benefiting from the power of AI + Quantum (AQ) technologies using NVIDIA GPUs. Learn how SandboxAQ leverages GPUs to power its AQ solutions — quantum cybersecurity, quantum sensing, quantum simulation and optimization, and quantum secure communications — without the need for QC. We'll explore some business use cases for quantum technologies in healthcare, telecommunications, financial services, aerospace, and national security. In time, as the quantum era accelerates, GPUs will continue to play a major role in hybrid computing environments, working side-by-side with CPUs, TPUs, and QPUs.
QC promise to revolutionize drug discovery and digital biology. Unfortunately, we have to face the facts: it won't be possible to use more than 1,000 qubits on a daily basis during the next five years. We have to rethink the current standalone approach and replace it with a hybrid HPC-QC approach, where more than 90% of the workflow is managed by high performance computing, the rest being delegated to QC. This working method will let us benefit very quickly from both the unmatched precision and computational power of QC and from the massive acceleration of calculations brought by HPC.
Register Now >> and join developers, innovators, researchers, and scientists in shaping our world with the power of quantum computing!